Securities firm

definition

Securities firms (also known as securities companies or brokers) refer to financial institutions that specialize in providing securities trading services. They mainly assist investors in trading financial products such as stocks, bonds, ETFs, and options. It is necessary to obtain a license from a relevant regulatory agency (such as the Hong Kong SFC or the Taiwan Financial Supervisory Commission). Compared with banks, it focuses more on investment transactions and has lower fees, making it suitable for active investors.

Comparison of popular securities firms in Taiwan (2025)

Note: The handling fees of Taiwanese securities companies are mostly discounted at 0.1425% of the transaction amount. The actual discount depends on the activity and inquiries. There are often new account discounts or regular quotas starting from 1 yuan.

Comparison of popular securities firms in Hong Kong (2025)

Note: The actual fees are subject to the latest official announcement. There are often account opening discounts such as free shares or cash.

Select points

• Fees: Commission, platform fee, dividend fee, financing interest rate.
• Market scope: Hong Kong stocks, US stocks, A shares, Taiwan stocks, global ETFs, etc.
• Platform: App ease of use, quote speed, research tools.
• Safety: regulatory license, investor protection fund.
• Account opening: Most are online and require proof of identity and bank account.

stock

What are stocks?

Stocks are securities issued by a company to investors to raise funds and represent the holder's ownership of some of the company's assets. Investors who hold stocks are shareholders of the company and enjoy the right to dividends and certain participation rights in decision-making.

Type of stock

• Common stock:Shareholders have the right to vote on the company's operations and have the right to participate in the company's profit distribution, but the rights to dividends and asset liquidation come after preference shares.
• Preferred shares:Shareholders usually have no voting rights but have priority in dividends and liquidation of the company.
• Growth stocks:Companies that are growing rapidly often have higher potential returns but are more volatile.
• Income stocks:Stable dividends are suitable for investors looking for stable cash flow.

Stock buying and selling process

1. Open a securities account:Choose a securities company and open a securities account and bank debit account.
2. Deposit funds:Deposit trading funds into a securities account.
3. Place an order to buy or sell:Use the trading platform, select the stock code and quantity, set the price and complete the transaction.
4. Confirm transaction:Check the transaction record to confirm whether the transaction was successful.

Advantages of stock investing

• Capital appreciation:Increases in stock prices can result in capital gains for investors.
• Dividend Yield:Dividends distributed to shareholders after a company makes a profit provide a stable cash flow.
• Participate in company growth:Holding stocks means participating in the company's development and enjoying the dividends of corporate growth.

Risks of Stock Investment

• Market fluctuation risk:Stock prices are affected by market factors and may fluctuate significantly.
• Company business risks:If the company performs poorly, it could cause the stock price to fall.
• Systemic risk:Risks that affect the overall market, such as economic recession or policy changes.

Stock Analysis Methods

• Fundamental analysis:Evaluate the intrinsic value of a stock by studying a company's financial statements, industry trends, and operating conditions.
• Technical analysis:Determine future price trends by analyzing historical data, charts, and indicators of stock prices.
• Quantitative analysis:Use data models and algorithms to conduct quantitative research on stocks and design trading strategies.

Advice for stock investors

• Learn and master basic investment knowledge, understand market operations and stock trading rules.
• Develop an investment plan with clear goals and risk tolerance.
• Diversify your investments to reduce the risk of fluctuations in a single stock.
• Stay rational and avoid emotional operations due to short-term market fluctuations.

IPO

definition

IPO (Initial Public Offering) is the first time a company publicly issues shares to public investors and lists them on the stock exchange to raise funds and increase the company's visibility.

How it works

1. The company selects an underwriter (usually an investment bank) to help design the fundraising structure.
2. Submit a prospectus (Prospectus), explaining the company's financial status, operating model and risk factors.
3. After review and approval by the competent authorities, the shares are priced and issued to the public.
4. Stocks are listed on the exchange and investors can buy and sell them freely.

advantage

• Strong financing ability:Enterprises can obtain large-scale funds from the capital market.
• Improve brand and trust:Public companies need to disclose financial reports to increase transparency.
• Employee motivation:Employee stock ownership plans can be used to attract and retain talents.

shortcoming

• High cost:Underwriting fees, attorney fees, accounting fees and compliance costs are payable.
• Compliance pressure is high:Financial information needs to be disclosed on a regular basis and subject to inspection by supervision and investors.
• Reduced operational autonomy:Shareholders may influence company decisions, and management needs to consider market reactions.

Compare with ICO

IPOs are strictly regulated capital market activities, and investors receive equity and legal protection; ICOs mainly issue tokens, most of which are not regulated and have high risks but low participation thresholds.

in conclusion

IPO is an important milestone for companies to enter the capital market. It is suitable for companies that have established scale and want to expand their sources of funds. However, companies need to be prepared to face strict regulatory requirements and market challenges.

Stock subscription

What is stock subscription?

Stock subscription refers to investors applying to purchase newly issued stocks through the securities company platform when the company conducts an initial public offering (IPO) or capital increase. This is a way for investors to participate in the new stock issuance market.

Stock Subscription Process

1. Open a securities account:Investors need to open a securities account and bank debit account with a securities company first.
2. Inquire about new stock information:Investors should pay attention to the new stock issuance announcement to understand the subscription period, price range and subscription limit.
3. Make a subscription:During the subscription period, investors enter the subscription quantity and price through the securities company platform and complete the subscription registration.
4. Draw results:In the event of oversubscription, allocation will be determined by drawing lots. The application money of unsuccessful applicants will be refunded.
5. Withholding and listing of shares:The winner needs to pay the subscription amount and wait for the new shares to start trading after they are listed.

Advantages of stock subscription

• Potentially high rewards:New stocks usually have higher growth potential after listing, bringing considerable returns to investors.
• Low barriers to entry:The subscription price is relatively reasonable and suitable for all types of investors.
• Various options:Investors can choose suitable targets for subscription based on the industry and company fundamentals.

Risks of stock subscription

• Price fluctuation risk:Prices of new shares may fluctuate significantly after listing, resulting in short-term losses.
• Risk of not winning the lottery:If there are too many people subscribing, the winning rate in the lottery may be very low, making it more difficult to obtain stocks.
• Company performance is poor:If the company's future performance is not as good as expected, the stock price may remain depressed for a long time.

How to improve the subscription success rate?

• Select popular new stocks:Study the fundamentals and market prospects of new stocks, and select stocks with potential for subscription.
• Multi-account subscription:If regulations allow, you can use your family account to increase the number of subscriptions and increase your chances of winning.
• Prepare funds in advance:Make sure there are sufficient funds in the account during the subscription period to avoid insufficient funds affecting the subscription.

Things to note

• Understand the subscription rules and procedures to avoid disqualification due to improper operation.
• Confirm whether the subscription funds will be temporarily frozen and arrange the liquidity of funds.
• There are risks in subscribing for new shares, so you should participate rationally based on your personal risk tolerance.

Taiwan stock lottery

Real-time information query website

• HiStock Hi Investment: Public Subscription/Stock Lottery Schedule
• Taiwan Stock Exchange: Public Subscription and Lottery Announcement
• Wangu.com: Public Subscription and Winning Statistics
• Stock Lucky Draw: Free Draw Reminder Service
• KGI Securities: Stock lottery process and techniques

Information content description

• Instant announcement of the latest lottery stock subscription period, lottery date, winning rate, underwriting price, etc.
• Provide subscription reminders, historical record inquiries, and simulated winning chances.
• Some platforms support LINE or Email reminder services.

Recommended operating procedures

1. First check which stocks are currently being subscribed.
2. Complete the subscription process and fund withholding in accordance with the securities firm's regulations.
3. In the morning of the lottery day, check whether you have won the lottery through the platform or brokerage.
4. Winners please pay attention to the coupon allocation and refund schedule.

Reminders

• Each person can only subscribe once, and duplicates will be disqualified.
• If you are not successful, you still need to pay a processing fee (usually 20 yuan).
• Some brokerages support App subscription and reminder functions, which can automatically track progress.

Top 20 Taiwan stocks with the highest EPS

EPS ranking in the past four seasons (as of January 22, 2025)

warrant

Introduction to warrants

Warrant is a derivative financial product that gives investors the right to buy (call warrant) or sell (put warrant) an underlying asset (usually a stock or index) at an agreed price within a specific period of time, but has no obligation to execute the transaction. Warrants are similar to options, have leverage characteristics, and are suitable for short-term trading and speculation.

Warrant type

• Call Warrant:Investors buy when they expect the price of an underlying asset to rise, and they can make a profit when the price rises.
• Put Warrant:Investors buy when they expect the price of an underlying asset to fall, and profit from the fall in price.

Warrant characteristics

• Leverage effect:Warrant prices are usually much lower than the underlying assets, so investment costs are lower, but they are more volatile.
• Expiry date restrictions:Warrants have a fixed expiration date, and if the break-even point is not reached before expiration, the value may return to zero.
• The issuing institution provides liquidity:Brokers (issuers) usually provide buy and sell quotes to ensure market liquidity.

Important parameters

• Strike price (exercise price):The price at which investors can buy or sell the underlying asset.
• Exercise Ratio:Refers to the amount of underlying assets that can be exchanged for each unit of warrant. This ratio determines how many units of the underlying stock or asset an investor can receive when the warrant is exercised. Number of underlying assets available = number of warrants × exercise ratio
• Expiry date:The validity period of the warrant is invalid after expiration.
• Embedded value:The difference in price between the warrant and the underlying asset (when the warrant is profitable).
• Time value:As the expiration date approaches, the time value gradually decreases and eventually reaches zero.

Transaction method

• Investors can trade warrants through securities firms, similar to stock trading.
• Transactions should take into account liquidity, issuer quotes, and price movements of the underlying asset.

suitable investor

• Investors familiar with leveraged trading and market fluctuations.
• Short-term traders hope to obtain larger profits through small amounts of funds.
• Investors who have strong analytical skills in market trends.

Things to note

• High-risk characteristics, which may lead to rapid losses due to fluctuations in the underlying assets.
• Time has diminishing value, and the value may decrease the longer you hold it.
• Attention needs to be paid to the issuer's market-making ability to ensure trading liquidity.

Size of major stock exchanges

Stock exchange market capitalization overview

Sources and explanations

• The data is compiled from the official data of the World Federation of Exchanges (WFE) and various exchanges in 2024.
• Market capitalization is in U.S. dollars (100 million U.S. dollars). Values ​​are approximate and may vary with market fluctuations.
• Listed in the table are 20+ major global stock exchanges, accounting for approximately 95% of the world's total market capitalization.

US stocks

Introduction to US stock market

The U.S. stock market refers to the U.S. stock market, which is mainly composed of the New York Stock Exchange (NYSE) and the Nasdaq Exchange (NASDAQ). The U.S. stock market is one of the most important financial markets in the world, attracting investors from all over the world.

trading hours

• Regular trading hours: 9:30 am to 4:00 pm ET.
• Pre-market trading: 4:00 a.m. to 9:30 a.m. ET.
• After-hours trading: 4:00 p.m. to 8:00 p.m. ET.

major indices

• Dow Jones Industrial Average (DJIA)
• Standard & Poor's 500 Index (S&P 500)
• Nasdaq Composite

Investment method

Investors can open a U.S. stock trading account through a brokerage firm to trade stocks, ETFs, options and other products. In addition, you can also use multiple entrustment methods to invest in U.S. stocks.

Things to note

• Understand the U.S. stock trading rules, including the T+2 delivery system and tax-related regulations.
• Be aware of currency risk, as U.S. stocks are traded in U.S. dollars.
• Manage risks well and set investment goals based on your personal financial situation.

Philadelphia Semiconductor Index

What is the Philadelphia Semiconductor Index?

Philadelphia Semiconductor Index Index (SOX Index for short) is an important stock market index tracking the performance of the U.S. semiconductor industry. The index was launched by the Philadelphia Stock Exchange (PHLX) in 1993 and covers a group of leading companies in the semiconductor industry to reflect the overall performance of the industry.

The Importance of the Philadelphia Semiconductor Index

• Industry trends:The SOX index is regarded as a health indicator of the global semiconductor industry and represents the development trend and market confidence of the industry.
• Impact on technology stocks:The semiconductor industry is the core of the technology industry, and the rise and fall of the SOX index often affects the performance of other technology stocks.
• Economic indicators:Semiconductors are key components of many modern devices, and the SOX index can also reflect changes in global economic activity and demand to a certain extent.

Representative companies of the Philadelphia Semiconductor Index

• Intel Corporation:One of the world's largest semiconductor manufacturers, it focuses on the production of computer processors and other high-performance chips.
• Taiwan Semiconductor Manufacturing Company (TSMC):The world's leading semiconductor wafer foundry company provides advanced process wafer foundry services to many technology companies.
• NVIDIA:It is famous for its graphics processing unit (GPU), which is used in gaming, artificial intelligence, data centers and other fields.
• Qualcomm:Focus on wireless communication technology, especially chip design for smartphones and 5G technology.
• Advanced Micro Devices (AMD):It provides high-performance computer processors, graphics cards and other products and is one of Intel's main competitors.
• Broadcom:Designs and manufactures a variety of semiconductor and infrastructure software solutions for communications, storage and industrial applications.
• Texas Instruments:Focusing on analog and embedded processing chips, it is widely used in electronic products, industrial and automotive markets.
• Applied Materials:Provides semiconductor manufacturing equipment and services and is one of the leaders in wafer manufacturing technology.

How the Philadelphia Semiconductor Index is calculated

The SOX index adopts a modified market capitalization weighting method. The weight of the index's constituent stocks is determined by their market capitalization, but there will be a weight limit for a single company to prevent certain large market capitalization companies from excessively affecting the index trend.

in conclusion

The Philadelphia Semiconductor Index is an important indicator of the technology industry and the stock market, representing the performance of core companies in the global semiconductor industry. Investors can learn about the trends in the semiconductor industry and gain further insight into the development direction of technology stocks and the global economy by paying attention to the SOX index.

NASDAQ

Introduction to NASDAQ

NASDAQ (Nasdaq) is the second largest stock exchange in the United States. Founded in 1971, it is the world's first electronic stock trading market. NASDAQ focuses on technology stocks and gathers many world-renowned high-tech and innovative companies.

Main features

• With electronic trading as the core: NASDAQ adopts a paperless electronic trading system, which is highly efficient and transparent.
• Concentration of technology companies: Companies listed on NASDAQ are mainly technology, medical, and biotechnology, such as Apple, Microsoft, Amazon, and Google parent company Alphabet.
• Globalization: NASDAQ attracts companies from all over the world to list and is one of the most international exchanges.

major indices

• Nasdaq Composite: Covers all stocks listed on NASDAQ.
• Nasdaq-100 Index (Nasdaq-100): consists of the 100 largest non-financial companies by market capitalization and represents the performance of the high-tech industry.

trading hours

• Regular trading hours: 9:30 am to 4:00 pm ET.
• Pre-market trading: 4:00 a.m. to 9:30 a.m. ET.
• After-hours trading: 4:00 p.m. to 8:00 p.m. ET.

Investment method

Investors can purchase stocks and ETFs listed on NASDAQ by opening a US stock trading account. Many brokerages also provide multiple entrustment services to facilitate investors to participate in the NASDAQ market.

Things to note

• High-tech stocks are highly volatile, and investors need to do a good job in risk assessment.
• Familiar with trading rules and related fees, such as trading commissions and US stock tax regulations.
• Pay close attention to market trends and company financial reports to grasp investment opportunities.

VOO

Introduction to VOO

VOO is an ETF (exchange-traded fund) issued by Vanguard Group, whose full name is Vanguard S&P 500 ETF. This ETF tracks the S&P 500 Index (S&P 500), covering the 500 largest listed companies in the United States by market capitalization, and represents the overall performance of the U.S. stock market.

Main features

• Low cost: VOO is known for its low management fees, with an expense ratio of only 0.03%, making it suitable for long-term investment.
• Diversified investment: VOO covers large companies in multiple industries, reducing the risk of a single enterprise or industry.
• Stability: Tracking the S&P 500 Index, suitable for investors interested in stable market growth.

Main constituent stocks

VOO's main constituents are the top companies in the S&P 500 Index, including:

• Apple (AAPL)
• Microsoft Corporation (Microsoft, MSFT)
• Amazon, AMZN
• Google parent company Alphabet (GOOGL, GOOG)
• Tesla (TSLA)

Transaction method

• VOO is listed on the New York Stock Exchange's Arca platform (NYSE Arca) and trades in U.S. dollars.
• Investors can directly buy and sell VOO through U.S. stock brokers, or participate through multiple entrustment methods.

suitable investor

• Long-term investors looking to diversify risk.
• Retirement plan participants seeking stable income.
• Novice investors who want to participate in the performance of the overall U.S. stock market.

Things to note

• VOO's performance is highly dependent on the overall conditions of the U.S. economy and market.
• Please note that exchange rate fluctuations may affect investment returns.
• It is recommended to review the investment portfolio regularly to ensure that it meets financial goals.

QQQ

Introduction to QQQ

QQQ is an ETF (exchange-traded fund) issued by Invesco. Its full name is Invesco QQQ Trust. It mainly tracks the Nasdaq-100 Index. The index is composed of the 100 non-financial companies with the largest market capitalization, mainly covering industries such as technology, communication services and consumer goods. It is one of the representative ETFs of technology stocks.

Main features

• High-tech focus: QQQ mainly holds world-renowned technology giants, such as Apple, Microsoft and Amazon.
• High liquidity: QQQ has large trading volume and strong liquidity, making it suitable for short-term and long-term investors.
• Growth potential: Due to its focus on investing in innovative companies, QQQ has high growth potential.

Main constituent stocks

The main constituent stocks of QQQ include:

• Apple (AAPL)
• Microsoft Corporation (Microsoft, MSFT)
• Amazon, AMZN
• Google parent company Alphabet (GOOGL, GOOG)
• NVIDIA, NVDA

Transaction method

• QQQ is listed on the NASDAQ exchange and trades in US dollars.
• Investors can directly trade QQQ through U.S. stock brokers, or participate through multiple entrustment methods.

suitable investor

• Investors who want to participate in the rapid growth of technology stocks.
• Investors with higher risk tolerance.
• Investors looking to diversify their investments into innovative industries.

Things to note

• QQQ has relatively high volatility and is suitable for investors who understand market risks.
• Concentrated on technology and innovative industries, lacking coverage of other traditional industries.
• Currency fluctuations may affect returns for non-U.S. dollar investors.

Buy U.S. stocks outside the United States

Common online brokers

• Firstrade
  Provides a full Chinese interface and supports transactions in US stocks, ETFs, options, etc. Commission-free and suitable for overseas Chinese-speaking investors.
• Interactive Brokers（IBKR）
  World-renowned, it provides multiple markets and assets, high leverage flexibility, and supports US stocks, options, ETFs, etc.
• TD Ameritrade
  The interface is simple and friendly, suitable for beginners and advanced traders. It supports users from many countries and has no minimum deposit.
• Charles Schwab
  A well-established brokerage, global investors can open an account and trade U.S. stocks without commission, which is stable and safe.
• Webull
  An emerging online brokerage with no minimum capital limit, modern interface, and suitable for young people.
• eToro
  It supports US stocks, cryptocurrency, foreign exchange, etc., and has social trading functions, suitable for strategy imitation and communication.
• Moomoo
  Active in Taiwan and Southeast Asia markets, trading US and Hong Kong stocks without commission, the platform is easy to operate.

Things to note

• To open an account, you need to provide your passport, address proof and other information, and complete the KYC review.
• Different brokers may have restrictions on some countries, so you need to check local regulations and policies first.
• When it comes to tax filing (such as W-8BEN form), be sure to pay taxes legally to avoid future tax disputes.

summary

The above brokers all support non-U.S. residents to open accounts and trade U.S. stocks through the Internet. It is recommended to choose the most suitable brokerage platform based on your own trading habits, language preferences and trading variety needs.

Ranking of U.S. listed companies

Sorted by revenue, market value, employment and industry impact (as of 2024)

illustrate

• This table is based on the overall contribution to GDP, including revenue scale, employment population, industrial chain effects and domestic investment.
• Technology, energy, finance and medical care are the main industries contributing to US GDP.
• Apple, Microsoft, Amazon and Google are not only the most valuable by market value, but also at the core of innovation and exports.

U.S. Stock Market September Curse

historical performance data

• Over the past 75 years, the S&P 500 has lost an average of about 0.7% in September.
• Other statistics show that the S&P 500 fell by about 1.1% on average, while the Dow Jones and Nasdaq fell by 1.1% and 0.9% respectively.
• Since 1928, the S&P 500 has had about a 55% chance of falling in September.

possible causes

• *End-of-quarter adjustments and asset portfolio rebalancing*: Many funds adjust their portfolios or sell loss-making positions (tax loss harvesting) at the end of the third quarter, creating selling pressure.
• *Trading is sluggish in the summer, and selling pressure emerges after the start of school*: In the summer, most people are on vacation, and trading volume is low; in September, investors return to the market and make more adjustments, leading to increased volatility.
• *Fund transfers in the bond market*: September is the peak period for new issuances in the bond market, attracting capital flows to the bond market, and the stock market is facing pressure from capital outflows.
• *Investor psychological factors*: There is a widespread impression of "bad September", forming a self-fulfilling prophecy and causing continued stress.
• *Concentrated release of key economic data and policy risks*: Employment, inflation reports and Federal Reserve decisions often fall in mid-to-late September, increasing market uncertainty.

Outlook and variables for this year

• This year, the S&P 500 rose nearly 1.9% in August and continues to trade above its 200-day line, a strong performance that may offset the historically depressed trend in September.
• However, market volatility (VIX) is at a low level, and if the fear index rebounds in the fall, it may still trigger downward pressure.
• If the Federal Reserve cuts interest rates in line with market expectations, it may lead to a rebound in the stock market in the long term.

U.S. stock earnings report commentary—Take NVIDIA as an example

1. Key points of financial report (brief)

byNVIDIA（NASDAQ: NVDA）For example, financial report items that investors are concerned about include: Revenue, gross profit margin, operating profit, net profit and earnings per share (EPS). NVIDIA is a growth technology company, Investment returns come primarily from share price appreciation, not cash dividends.

2. Cost per share (take the market price of $150 as an example)

• Assuming buying price:$150.00/share
• Assume that the brokerage fee is 0.1%: 0.001 × $150.00 =$0.15/share
• Unit cost including handling fee ≈ $150.15 / share

3. Dividend distribution ($0.01 per quarter) and cash yield rate

• Quarterly cash dividends:$0.01/share
• Annual dividend distribution (4 quarters):$0.04/share
• Cash yield (Dividend Yield) calculated based on market price of $150:
  0.04 ÷ 150 × 100% = 0.0267%(approximately 0.027%)

4. Example of actual dividend amount (holding 100 shares)

5. Explanation of Payout Ratio

Payout RatioIt refers to the proportion of the company's earnings used to pay cash dividends, which is used to measure the company's "Dividend stability" and "reinvestment ability."

The calculation formula is as follows:

Payout Ratio = Dividend per share ÷ Earnings per share (EPS) × 100%

Taking NVIDIA as an example, if earnings per share (EPS) is$3.51, the annual dividend is $0.04, then:

Payout Ratio = 0.04 ÷ 3.51 × 100% ≈ 1.14%

• The payout ratio is about 1%, which means that the company reinvests almost all of its surplus into research and development and expansion.
• Growth technology stocks (such as NVIDIA, Tesla) usually have very low dividend payout ratios to preserve cash to support high research and development expenditures.
• If it is a mature industry company (such as Coca-Cola, PQ, Intel), the Payout Ratio is usually between 40% and 70%, reflecting stable cash flow and high dividend policy.

6. Examples of comprehensive returns including stock price fluctuations

Assume 100 shares are purchased for $150.15 (including fees):

• Total purchase cost = $150.15 × 100 =$15,015.00
• If the stock price rises to $200 one year later (not taking into account selling fees), capital gain = ($200 − $150) × 100 =$5,000
• Annual cash dividend (100 shares) =$4.00
• Total compensation amount = $5,004
• Total return = $5,004 ÷ $15,015.00 ≈33.3%

7. Key points organized

• NVIDIA's cash yield is about 0.03%, and the dividend is extremely low.
• The Payout Ratio is about 1.14%, indicating that almost all of the surplus is used for reinvestment and research and development.
• Investment focus should be on revenue and EPS growth, and changes in demand for AI servers and GPUs.
• Dividends have a small impact on total returns, and long-term returns mainly depend on stock price appreciation.

Top 10 U.S. stock yield rates

illustrate

The following table compiles high-yield (Dividend Yield) U.S. stocks (including REIT/MLP/financial stocks) from multiple public sources. The values ​​are approximate "before and after market capitalization/yield" observed values, which will change with stock prices and announcements. The yield rates are only listed for reference. Please be sure to check the latest yield rates and financial security one by one before investing.

Top ten yield rates (example)

Short comments and risk warnings

• Most of the tables are examples and include industries such as REIT / MLP / Mortgage-REIT. These stocks have high yields but also high risks (interest rates, leverage, cash flow).
• Common reasons for high yields: falling stock prices (raised yields), one-time special dividends, or industrial structural factors. should be viewed simultaneouslypayout ratio, free cash flow and debt structure.
• The values ​​in this table are approximate. Please check the latest "forward yield / trailing yield" with the real-time financial platform you are using (such as TradingView / Yahoo Finance / Seeking Alpha / Broker) before making an investment decision.

China stock market

Introduction

China's stock market is one of the largest capital markets in the world, mainly composed of the Shanghai Stock Exchange (Shanghai Stock Exchange) and Shenzhen Stock Exchange (Shenzhen Stock Exchange), and has the Hong Kong Stock Exchange as an important overseas market. China's stock market also includes different sectors such as A shares, B shares and H shares, attracting domestic and foreign investors to participate.

major exchanges

• Shanghai Stock Exchange: Founded in 1990, it focuses on large state-owned enterprises and financial stocks.
• Shenzhen Stock Exchange: Founded in 1990, it mainly focuses on small and medium-sized and high-tech growth enterprises.
• Hong Kong Exchange (H shares): Chinese companies are listed in Hong Kong to attract international funds.

Main sectors

• A shares: Denominated in RMB, mainly for domestic investors and qualified foreign investors (QFII) to participate.
• B shares: Priced in Shanghai B shares (USD) and Shenzhen B shares (HKD), open to foreign investors.
• H shares: Mainland Chinese companies listed in Hong Kong are priced in Hong Kong dollars.
• Science and Technology Innovation Board: The Shanghai Stock Exchange was established in 2019 and focuses on technological innovation enterprises.
• GEM: Launched by the Shenzhen Stock Exchange in 2009, it focuses on supporting small, medium and high-tech enterprises.

feature

• The investor structure is mainly retail investors, and trading activity is high.
• Government policies and regulations have a significant impact on the market.
• The constituent stocks are centered on state-owned enterprises, banks, energy, technology and manufacturing.
• It has high volatility and is easily affected by the international situation and policy regulation.

representativeness index

• Shanghai Composite Index: Reflects the overall trend of the Shanghai Stock Exchange.
• SZSE Component Index: Reflects the trend of the main constituent stocks of the Shenzhen Stock Exchange.
• CSI 300 Index: Select 300 stocks with large market capitalization and high liquidity in Shanghai and Shenzhen.
• GEM Index: Reflects the overall performance of the Shenzhen GEM market.
• Science and Technology Innovation 50 Index: Reflects the performance of representative companies on the Science and Technology Innovation Board.

Investment method

• Buy and sell stocks directly (through a brokerage firm).
• ETFs and funds, such as the CSI 300 ETF.
• Through the Shanghai-Hong Kong Stock Connect and Shenzhen-Hong Kong Stock Connect mechanisms, foreign investors can participate in the A-share market.

Risks and Challenges

• Policy risk: Government regulation and supervision policies have a significant impact.
• Market fluctuations: affected by economic data and international situations.
• Investor structure: The proportion of retail investors is high and it is prone to short-term speculative fluctuations.

Ranking of Chinese listed companies

Based on revenue, market value, industrial status and economic impact (as of 2024)

illustrate

• This table covers state-owned enterprises and some large private enterprises, sorted according to their revenue, market value and industry pillars.
• Energy, finance, infrastructure and technology are the four pillar industries of China's GDP.
• Most companies are state-owned enterprises, which have a significant impact on employment, market stability and export trade.

Japanese stock market

major exchanges

• Tokyo Stock Exchange (TSE): The world's largest exchange by market capitalization and the core of the Japanese stock market.
• Osaka Exchange (OSE): Mainly engaged in trading index futures and derivative financial products.

major stock price index

• Nikkei 225 (Nikkei 225 Index): Covers 225 representative Japanese companies with large market capitalization and good liquidity.
• TOPIX (Topix Index): Covers all companies in the Tokyo Stock Exchange Prime market and better reflects overall market performance.

Representative industries and enterprises

• Electronics and Technology：Sony、Panasonic、Keyence、Tokyo Electron
• automobile manufacturing：Toyota、Honda、Nissan、Subaru
• Financial insurance: Mitsubishi UFJ, SMFG, Nippon Life Insurance
• Mechanical heavy industry：Hitachi、Mitsubishi Heavy、Komatsu
• Consumption and retail: Fast Retailing (Uniqlo parent company), Seven & I (7-Eleven)

Characteristics of Japanese stock market

• Many enterprises have global competitiveness and technological strength.
• The economy is mature and stable, and the central bank (Bank of Japan) has great influence in participating in the market.
• In recent years, corporate governance and capital efficiency reforms have been promoted (such as the Tokyo Stock Exchange market classification reform).
• The proportion of foreign capital holdings is high, and market fluctuations are easily affected by global conditions.

Investment method

• Invest in Japanese ETFs (such as EWJ, DXJ) or individual stocks through global brokers.
• Use brokers with Japanese stock market trading channels (such as Futu, Interactive Brokers, IBKR).
• Some Japanese stock ETFs can invest indirectly in the Taiwan, Hong Kong, and U.S. markets.

Investment advantages and risks

• Advantages: The industry is complete, corporate assets are stable, and Japanese yen assets are safe havens.
• risk: The shadow of deflation has not been eliminated, weak domestic demand, aging population, and risks of exchange rate fluctuations.

Nikkei 225 Index

Index overview

The Nikkei 225 (Nikkei 225) is Japan's most representative stock index, compiled by the Nikkei News Agency and tracks 225 large companies listed on the Tokyo Stock Exchange. The index has been published since 1950 and is a core measure of Japan's overall stock market performance, similar to the Dow Jones Industrial Average in the United States.

Calculation method

Nikkei 225 uses a price-weighted method, that is, the index is calculated based on the weighted average of the stock prices of the constituent stocks, rather than market capitalization. The higher the stock price of a company, the greater its influence on the index. The methodology is the same as the Dow Jones but differs from indexes such as the market cap-weighted S&P500.

Industrial distribution

• Technology: SoftBank, Sony, Advantest
• Manufacturing and Automotive: Toyota, Honda, Komatsu
• Retail and consumer: Fast Retailing (parent company of UNIQLO), Seven & I
• Finance and Insurance: Nomura, Dai-ichi Life

Transaction method

Investors can participate in trading Nikkei 225 through ETFs (such as iShares Nikkei 225 ETF), futures (such as CME Nikkei 225 Futures), CFDs or options. Mainstream trading platforms such as MT5, TradingView, IB, and Saxo all support the analysis and trading of this index.

trading session

The Tokyo Stock Exchange's spot market trading hours are 9:00–11:30 and 12:30–15:00 Japan time. Index-related CFDs and futures are mostly traded almost around the clock, depending on the broker's regulations.

Features and Applications

• Reflect the Japanese economy and corporate competitiveness
• Very sensitive to yen fluctuations and international trade
• Highly affected by global stock market linkages, especially closely related to U.S. stocks and Asian markets
• Suitable for short-term technical trading and medium- and long-term asset allocation

investment risk

Since Nikkei 225 is price-weighted, companies with high stock prices but not necessarily large market capitalizations (such as Fast Retailing) have a great impact on index fluctuations, which may amplify the risks of a single company. In addition, Japanese economic policies, central bank movements and international trade frictions are also potential influencing factors.

Conclusion

Nikkei 225 is an important reference indicator for entering the Japanese stock market. It has high liquidity and international visibility, and is suitable for diversified trading strategies. By understanding its composition and volatility characteristics, investors can more effectively deploy the Asian market.

Buy Japanese stocks from outside Japan

Common online brokers

• Interactive Brokers（IBKR）
  Supports global markets, including Japanese stock markets (TOPIX/DSE). The platform provides low commissions and multi-currency accounts, making it suitable for advanced investors.
• Charles Schwab
  Support overseas investors to trade Japanese stocks through international accounts and provide research report assistance.
• TD Ameritrade
  Although it does not provide direct trading of Japanese stocks, it can invest in Japanese stocks indirectly through ADR (American Depository Receipts).
• Saxo Bank
  A Danish brokerage that supports direct investment in Japanese stocks. The interface has Chinese support and is suitable for market allocation in multiple countries.
• Moomoo
  It supports Japanese stock trading and has an intuitive ordering interface. It has been active in Taiwan, Hong Kong and other places in recent years.
• Huasheng Securities (Futu)
  It supports Japanese and Hong Kong stock trading, is suitable for Chinese users, and has a low threshold for opening an account.

Things to note

• When opening an account, you need to provide proof of identity (such as passport) and address, and complete the broker's KYC certification.
• Some platforms offer Japanese stock CFDs (Contracts for Difference), which are not spot stocks. You should understand the nature of the transaction before investing.
• When it comes to local tax declaration (such as dividend tax), it is recommended to understand the tax burden and regulations of Japanese stock investment in advance.

summary

If you want to invest directly in Japanese stocks outside Japan, IBKR, Saxo Bank and Futu are common choices. Based on transaction volume, currency management and platform interface friendliness, you can select a suitable broker to achieve multi-market layout.

Ranking of Japanese listed companies

Sorted by revenue, market value and economic impact (based on 2024 data)

illustrate

• This ranking comprehensively considers each company's contribution to Japan's GDP, employment opportunities, export proportion and industrial chain impact.
• Automobiles, telecommunications, banking and industrial manufacturing are the main contributors to Japan's GDP.
• Toyota has long been one of the world's largest automobile companies, contributing significantly to exports and domestic production.

GER40 Index

Index overview

The GER40 index, also known as the DAX 40, is one of Germany's most representative stock market indices, tracking the 40 largest and most liquid companies listed on the Frankfurt Stock Exchange. The index was originally DAX 30 and was expanded to 40 constituent stocks in 2021 to further enhance market representation and stability.

Index calculation method

GER40 is calculated using a free-float market capitalization weighting, which only takes into account the number of shares that are freely tradable on the market. To prevent a single company from dominating the market, its weight is capped at 15%. The index is adjusted quarterly to reflect market changes and company qualifications.

Main ingredient industries

• Cars (e.g. Mercedes-Benz, BMW, Volkswagen)
• Technology (e.g. SAP, Infineon)
• Chemical and pharmaceutical (e.g. Bayer, BASF)
• Finance (e.g. Allianz, Deutsche Bank)
• Retail and Industrial (e.g. Siemens, Adidas)

Transaction method

Investors can invest in the GER40 Index through exchange-traded funds (ETFs) or contracts for difference (CFDs). Popular platforms such as MT4, MT5, and TradingView all support this index, and it can also be traded through brokers such as XTB, IG, eToro, etc.

trading session

Standard trading hours on the Frankfurt Stock Exchange are 9:00 to 17:30 Central European Time (CET). Some CFD platforms offer longer trading hours (e.g. 8:00 am to 10:00 pm) for added flexibility.

Index characteristics

• Represents the German economy and European market trends
• Medium to high volatility, suitable for short-term and mid-term traders
• Closely related to global economy, manufacturing, and export data

Investment risk warning

Although the GER40 constituent stocks are large blue-chip companies, they are still affected by factors such as European political economy, energy prices, and export situations. When using leveraged products such as CFDs, special attention needs to be paid to the potential risks arising from market fluctuations.

Conclusion

GER40 is one of the most watched indexes in Europe, providing good reference value whether used for technical analysis, asset allocation or short-term speculative trading. By understanding its structure and trading methods, you can more effectively grasp the market trends in Germany and Europe.

Ranking of German listed companies

Sorted by revenue, market value and economic impact (based on 2024 data)

illustrate

• This table is a comprehensive ranking based on revenue, market value, market share and contribution to German exports and employment.
• Most companies are DAX 40 constituent stocks and are the main support for the industrial and service industries in Germany's GDP.
• The automobile industry accounts for a very high proportion of Germany's GDP, so Volkswagen, Mercedes-Benz and BMW rank at the top.

indian stock market

major exchanges

• BSE (Bombay Stock Exchange) Bombay Stock Exchange: Founded in 1875, it is the oldest stock exchange in Asia.
• NSE (National Stock Exchange) National Stock Exchange: Founded in 1992, it ranks first in the country in terms of transaction volume and market value.

major stock price index

• SENSEX: BSE's representative index, consisting of 30 large blue chip stocks.
• NIFTY 50: The representative index of NSE, consisting of the 50 companies with the largest market capitalization and good liquidity.

Representative industries and leading companies

• information technology：TCS、Infosys、Wipro
• Finance and Banking：HDFC Bank、ICICI Bank、SBI
• energy：Reliance Industries、ONGC、Adani Green
• consumer goods：Hindustan Unilever、ITC、Nestlé India
• Pharmaceuticals and Biotechnology：Sun Pharma、Dr. Reddy’s Labs

Features of Indian Stock Market

• The demographic dividend is huge and the middle class is rising rapidly.
• The economic structure continues to reform, and digital and manufacturing industries grow rapidly.
• Foreign investment is active, and India is regarded as an important representative of emerging markets.
• The regulatory authority is SEBI (Securities and Exchange Board of India), which ensures market stability and fairness.

Investment method

• Participate through international brokers or funds (such as MSCI India ETF).
• Use brokers with access to the Indian stock market, such as Interactive Brokers, Charles Schwab, etc.
• Opening an account in India must comply with FPI (foreign investor) regulations.

Investment advantages and risks

• Advantages: High growth potential, government-promoted infrastructure and digital transformation.
• risk: Exchange rate fluctuations, policy uncertainty, and corporate governance issues.

Ranking of listed companies in India

Sorted by revenue, market value and economic impact (based on 2024 data)

illustrate

• This table ranks companies based on market capitalization, revenue, employment contribution and export orientation.
• IT services, banking and energy are key pillar industries of India's GDP.
• Reliance Industries spans multiple key industries and is one of the largest private contributors to India's GDP.

Ranking of UK listed companies

Sorted by market value, revenue, employment and industry impact (as of 2024)

illustrate

• This table covers the most representative listed companies in the UK, ranked according to market value, industrial chain effects, domestic employment and GDP contribution.
• Energy, finance, pharmaceuticals and consumer goods are the main pillar industries of UK GDP.
• Shell and BP are global energy giants with significant contributions to UK exports and tax revenue.

Ranking of French listed companies

Based on market value, revenue, industry influence and employment contribution (as of 2024)

illustrate

• LVMH, Airbus and TotalEnergies are France's most internationally influential companies, contributing significantly to exports and employment.
• Energy, aviation, finance, luxury goods and pharmaceuticals are key industries in France's GDP.
• Most companies are CAC 40 constituents and participate extensively in global markets.

Ranking of Italian listed companies

Top ten companies by market capitalization

Other noteworthy companies

• Atlantia
• Mediobanca
• Banco BPM
• Moncler
• Unipol
• FinecoBank
• Recordati
• BPER Banca
• Banca Mediolanum
• Edison

Sources and explanations

• The ranking is based on the company's market capitalization/listed stock market capitalization, and the data is taken from websites such as CompaniesMarketCap and SimplyWallSt.
• The industry classification is a general industry classification and is for reference only.

Ranking of Canadian listed companies

Top ten companies by market capitalization

Other well-known top 20 companies

• Bank of Nova Scotia (Scotiabank)
• Canadian Natural Resources
• Canadian Imperial Bank of Commerce (CIBC)
• Canadian National Railway
• Suncor Energy
• Power Corporation of Canada
• Fairfax Financial
• TC Energy
• Magna International
• National Bank of Canada

Sources and explanations

• Ranking based on market capitalization data from CompaniesMarketCap and SimplyWallSt.
• The industry classification is the industry in which the company mainly operates and is for reference only.

Ranking of Korean listed companies

Top 20 companies by market capitalization (based on market capitalization)

Sources and explanations

• Rankings are compiled based on market capitalization data from CompaniesMarketCap.
• The company's industry classification is compiled based on public information and is for reference only.

real estate

Real estate investment considerations

Real estate supply and demand related index

definition

The real estate supply and demand related index is an important tool used to measure the supply and demand situation in the real estate market and helps analyze the market's balance and future trends.

common index

housing vacancy rate

Refers to the proportion of houses on the market that are not rented or sold during a period of time. A high vacancy rate may indicate oversupply, while a low vacancy rate may indicate undersupply.

housing stock ratio

It represents the ratio of the number of homes currently available for sale in the market relative to monthly sales and is used to measure inventory pressure in the housing market.

Buy-to-ask ratio

It measures the ratio of buyers and sellers in housing transactions in the market over a period of time. A high value indicates strong buyer demand, while a low value may indicate a deserted market.

Number of new houses built

Reflects the number of new home construction starts over a period of time and is often used to assess the future direction of housing market supply.

Applications of indices

• Analyze whether the real estate market is in a state of oversupply or undersupply.
• Predict real estate price trends.
• Provide a reference basis for policymakers to regulate the balance of market supply and demand.

Taiwan's current situation

Taiwan's housing vacancy rate has been relatively high in recent years, coupled with the high housing stock ratio, indicating that market supply exceeds demand. However, housing prices have not dropped significantly, reflecting market structural problems.

future trends

With policy controls and market adjustments, the supply and demand index may gradually stabilize. It is necessary to pay attention to the impact of demographic changes, economic development and other factors on the market.

How to buy a cheap house

Compare real estate information

• Search multiple agency websites and set filter conditions such as price and location.
• Pay attention to price changes and use historical house price records to determine whether there is room for negotiation.
• Attend an open house to speak directly with the homeowner or agent.

Become a real estate agent

• Contact the agent frequently to express your sincerity in purchasing a house and let the agent notify you of good properties first.
• Establish long-term cooperative relationships and obtain internal, unpublished property information.
• Take the initiative to ask agents during the off-season to increase your negotiating advantage.

Enter the real estate industry

• Participate in real estate lectures and forums and get to know people in the industry.
• Maintain good relationships with intermediaries and obtain inside market information through them.
• Consider working as a real estate agent to be the first to know about low-priced properties.

Take the initiative

• Contact the homeowner directly to avoid agency fees and get a better price.
• Pay attention to foreclosure houses and silver auction houses, study the process, and look for low-priced bids.
• Pay attention to properties that are for sale in a hurry or that are changing hands in a short period of time, such as those owned by immigrants or those with financial difficulties.

House renovation and value-added

• Buy a house that is ready for renovation, evaluate the renovation costs, and lower the purchase price.
• Learn house renovation techniques to reduce renovation expenses and increase return on investment.
• Create additional value by renting or reselling your remodeled home.

Attention reminder

With increasing investment, although the acquisition cost decreases, the relative capital cost and time cost increase.

We must pay attention to the trend of the general market environment. When the market is bad to a certain extent, the short-term return rate may become negative. Be very careful not to over-leverage your funds at this time.

Real estate demand group analysis

first time buyers

First-time buyers refer to the group of people purchasing real estate for the first time, usually young people and newlywed families. Their needs are mainly concentrated in small square meters, high practicality and reasonable price.

Upgraders/house-changers

Upgraders are families who already own property but want to upgrade to larger, higher-quality homes, usually because of an increase in family size or a pursuit of a better living environment. They prefer medium- to large-sized residences and prime locations.

investment family

The purpose of investors buying real estate is to pursue capital appreciation or rental income, and they mainly focus on the development potential of the location and the appreciation space of the real estate. Their choices are usually concentrated in areas with convenient transportation and crowded areas.

Generally speaking, they can be divided into those who focus on capital appreciation are called investors, and those who focus on rental income are called financial managers.

retired people

The needs of retired people are concentrated in retirement homes, which emphasize the convenience of life and the quietness and comfort of the surrounding environment. They prefer areas close to medical facilities or natural landscapes.

foreign buyers

Most foreign buyers in the real estate market are interested in the investment environment and quality of life in a region. Their needs may include high-end residences or properties in specific school districts.

Factors affecting demand

• Economic status: Economic prosperity and income level affect the ability to purchase a house.
• Policy controls: policies such as loan restrictions and home purchase subsidies.
• Demographic structure: changes in family composition, population mobility and birth rates.
• Regional development: transportation construction, business development and educational resources.

Demand trends in Taiwan

Taiwan’s real estate demand groups are becoming increasingly diversified. First-time homebuyers have an increasing demand for small square footage, retirees prefer suburban residences with convenient living conditions, and investors continue to pay attention to the potential of urban areas and emerging development areas.

house price to income ratio

definition

The house price-to-income ratio is an important indicator of the affordability of house prices in a region. It is calculated as the average house price in the region divided by the average annual household income.

Calculation formula

House price to income ratio = average house price ÷ average household annual income

significance

This indicator reflects the financial burden of residents purchasing a house. The higher the house price-to-income ratio, the longer it takes for local residents to afford a house.

international standards

According to international experience, the price-to-income ratio is within a reasonable range between 3 and 5. If it exceeds 5, it means that the house price is on the high side, which puts the pressure on most families to buy a house.

Taiwan's situation

According to data in recent years, the housing price-to-income ratio in major cities in Taiwan generally exceeds international reasonable standards, and even exceeds 10 in some areas, indicating that residents have a heavy burden to purchase houses.

Influencing factors

• Real estate market supply and demand conditions
• Economic growth and wages
• Policy impacts, such as loan interest rates and taxes

Countermeasures

The government can improve the problem of excessive housing price-to-income ratio by increasing the supply of housing, controlling real estate speculation, and raising salary levels.

Pre-sale house

definition

Features

• Payment method flexibility:Pre-sale houses usually adopt an installment payment system, with a lower down payment ratio, which can reduce initial financial pressure.
• Customizable design:Some construction plans allow the buyer to choose decoration, layout or building materials during the construction stage, which is flexible and personalized.
• Has future value-added potential:If the location or market improves, the price may rise after completion, creating potential returns for investors.
• Price transparency:Pre-sale houses are mostly open to the public, and the construction information, floor plans and prices are relatively clear.

Risks and Cautions

• The quality of the house delivered is uncertain:Actual finished results may differ from model homes or advertisements.
• Builder’s credit risk:If the builder's funds are cut off or goes bankrupt, the project may be delayed or even stopped.
• Market price fluctuations:If the economy declines or house prices correct, the price after completion may be lower than the purchase cost.
• The contract terms are complex:Pre-sale houses are "signed first, handed over later", so you should carefully review the sales contract and performance guarantee conditions.

Performance guarantee system

• The builder can complete the construction project and hand over the house on time.
• The money paid by the buyer is deposited in a special account and cannot be misappropriated at will.
• If a dispute occurs or the builder is unable to perform the contract, the guarantee agency can assist in refunding or completing the construction project.

Bank loan and payment process

1. Signing stage: Pay deposit and down payment (usually 10% to 15% of the total price).
2. Construction stage: Payment in installments according to progress, about 3 to 5 installments.
3. House completion: apply for a mortgage, handle transfer and property rights registration.

Comparison with existing houses

Summarize

Commonly used real estate information websites in Taiwan

Major builders in Taiwan

farglory construction

Famous for the large-scale landmark projects that followed Taipei 101, the product line covers residential, commercial and corporate headquarters buildings. In recent years, it has actively promoted luxury projects such as Farglory THE ONE and Farglory 95.

Xingfufa Construction

The king of case promoters in Taiwan, with the largest case volume, and its layout covers Shuangbei, Taoyuan, Hsinchu, Taichung, and Kaohsiung. His representative works include the "Xing Fu Fa Run Long", "Run Sheng", and "Bo Xue Yuan" series.

Runtai Global Construction

A subsidiary of Runtai Group, it focuses on high-end residential and commercial properties. It is famous for projects such as "Runtai Jingzhan", "Runtai Yucheng" and "Dunhua SOGO". In recent years, it has launched "Runtai Weifang" luxury homes.

Cathay Construction

Cathay Group's products are mainly medium and large square footage luxury homes such as "Cathay Fu", "Cathay Summit", "Cathay Mushan", etc. It attaches great importance to green buildings and sustainable design.

Changhong Construction

Deeply cultivated in Xindian, Zhongyonghe and Banqiao, the representative brands are "Changhong Tianxi", "Changhong Xintianmu" and "Changhong Tianrui", which are famous for their exquisite quality.

Baojia Organization

It is the largest construction agency group in Taiwan. Its brands include Jia Guilin, Kunshan, and Huaxian. It has a large case volume and focuses on first-time purchase and house replacement products.

Fubon Construction

A subsidiary of Fubon Group, it specializes in luxury homes and iconic commercial properties, with its representative projects such as "Fubon Tomorrow World", "Taipei Sky Tower" and "Fubon Art Tree".

Hongpu Construction

An index builder in Central Taiwan, Taichung Phase 7 has the most rezoning proposals, represented by the "Hongpu Star" and "Hongpu Central Park" series.

Mainland construction

Taiwan's number one luxury brand, with representative works such as "Runtai Dunren", "Crown of Mainland Xinyi" and "Tao Zhuyin Garden", famous for its architectural aesthetics and top-notch craftsmanship.

Huagu Construction

Famous for its luxury series such as "Huagu Mingzhu", "Huagu Tianzhu" and "Huagu New Generation", it focuses on the egg yolk area in the elite area of ​​​​Beijing City.

Ri Shengsheng

Well-known agency construction works in parallel with its own brands. Its representative works include "The Westin Risheng Shengjing Station Hotel" and "Happiness Praise" series. In recent years, it has launched the "Jinghua Plaza" luxury house.

Guande Construction

Deeply cultivated in Neihu, Dazhi and Chongyang sections, the representative works are "Guande Louvre", "Guande Fudu" and "Guande Yuchen", which are famous for their European architectural style.

Sakura Construction

A benchmark builder in Taichung and Kaohsiung, Taichung's representative projects are "Sakura for Happiness" and "Sakura MOMA", and Kaohsiung has the "Sakura Academy" series.

Jusheng Construction

Kaohsiung is a local construction company specializing in art museums and the 16th Agricultural Special Zone. Its representative works are "Jusheng Crystal Pan" and "Jusheng Imperial Palace".

By Ju Construction

Representatives of luxury homes in Taichung, the masterpieces "Yuju Rizhi", "Yujujuqian", and "Yujuhanbi" are famous for their ultimate craftsmanship and low construction coverage rate.

Taiwan's major real estate agency

The following are Taiwan's major national real estate agency brands, ranked according to market share, with links to their official websites:

Sumisho Real Estate

Zhushang Real Estate is the largest real estate agency brand in Taiwan, with more than 600 stores, providing professional house sales and leasing services.

Official website:https://www.hbhousing.com.tw/

Xinyi House

Xinyi Housing adopts a fully direct-operated system, emphasizing corporate governance and information transparency. It has approximately 486 directly-operated stores and provides diversified services such as buying and selling and leasing.

Official website:https://www.sinyi.com.tw/

Yongqing Real Estate Group

Yongqing Real Estate Group adopts a multi-brand strategy and owns brands such as Yongqing House, Yongqing Real Estate, Youchao House, Taiqing Real Estate, and Yongyi House, with a total of approximately 1,522 stores.

Official website:https://www.yungching.com.tw/

Taiwan Real Estate Group

Taiwan Real Estate Group adopts a business model that combines direct operation and franchising. It owns Taiwan real estate brands with a total of approximately 343 stores.

Official website:https://www.twhg.com.tw/

CITIC Housing

CITIC Housing was established in 1985. It is a full-franchise system that emphasizes safety, professionalism and dedicated service concepts. It has approximately 260 stores.

Official website:https://www.cthouse.com.tw/

Dongsen House

Dongsen House is a real estate agency brand under Dongsen Group. It adopts a franchise system and combines media resources to provide a full range of real estate services and has approximately 181 stores.

Official website:https://www.etwarm.com.tw/

pacific houses

Pacific House adopts a business model that combines direct operation and franchising to provide diversified real estate services and has approximately 176 stores.

Official website:https://www.pacific.com.tw/

21st century real estate

Century 21 Real Estate is an internationally renowned real estate agency brand that adopts a franchise system and has approximately 116 stores in Taiwan.

Official website:https://www.century21.com.tw/

The above information comes from the official websites and public information of each brand. The actual number of stores may change. Please refer to the latest announcement of each brand.

Real estate foreclosure information

court announcement

Administrative Executive Office, Ministry of Justice

Real estate auction information provided by the Legal Department, including auction date, location, reserve price and other information. Users can go to the official system to check the real estate foreclosure announcement.

Tycoon Housing Network

Juheng Housing Network aggregates foreclosure house information from various courts and provides detailed auction announcements and object information, which is suitable for general user inquiries.

Bank of Taiwan Foreclosure Platform

The Bank of Taiwan also provides a foreclosure house inquiry service, allowing users to filter suitable auction objects based on region and auction price.

Foreclosure house statistics tracking platform

Long-term tracking of legal auction data requires a combination of official macro statistics and private case history data. The following are key platforms that provide data analysis and website links:

Ministry of Interior Real Estate Information Platform

• Official website: https://pip.moi.gov.tw/
• Data highlights:Provide statistics on the number of auction transfers.
• Track value:The quarterly and annual reports for previous years can be downloaded in the statistical information area, which are important indicators for studying the long-term growth and decline of foreclosure cases across Taiwan and various counties and cities, and for judging the prosperity of the housing market.

Judicial Yuan Foreclosure House Inquiry System

• Official website: judicial
• Data highlights:The latest foreclosure cases announced by various local courts.
• Track value:Although it does not provide statistical charts, it is the source of all foreclosure data, including the most accurate bottom price, number of auctions and seizure record information.

Transparent Housing Information 104 Forensic Lawyer Network

• Official website: https://www.104woo.com.tw/
• Data highlights:Complete foreclosure history records and transaction price statistics.
• Track value:It has a huge historical database that can track the auction records of specific objects in the past decades, and provide comparative analysis of foreclosure transaction prices and real price registrations.

Broadband room news

• Official website: 54168
• Data highlights:Taiwan-wide auction information and foreclosure data map.
• Track value:Provides professional foreclosure statistical research reports, combined with geographical information systems, to facilitate users to track the distribution and price trends of foreclosure items in specific areas.

Comparison of platform data features

It is recommended that you first observe the general trends from the Ministry of the Interior platform, and then use private databases such as Transparent Housing Information or Broadband Housing Information to conduct in-depth price tracking in specific areas.

Financial management mortgage

Basic concepts

• Financial management mortgage is a kind of financial product that "combines the functions of mortgage and credit loan".
• Borrowers can flexibly withdraw funds and make repayments within the approved limit.
• Usually the house is used as security, the maximum loan amount is set, and the interest is calculated based on the actual amount used.

How it works

• The bank sets a "recyclable" mortgage limit, for example, up to 5 million.
• The borrower can use part of the amount initially, and can use it later or make partial repayments according to needs.
• Interest is only calculated on the actual amount used and can be reused after repayment.

advantage

• Flexible use of funds, suitable for those with irregular funding needs.
• The interest rate is usually lower than that of a general credit loan, reducing the interest burden.
• The repayment method is flexible and can be partially or fully repaid in advance.

shortcoming

• It is easy to cause excessive borrowing, so capital control needs to be cautious.
• If house prices fall, you may face the risk of insufficient collateral value.
• The bank may re-examine the limit and conditions every year.

Suitable for objects

• Those who have stable income and need flexible allocation of funds.
• Those who want to consolidate multiple loans into a single account and reduce interest costs.
• Those with good credit records and collateral value.

Xinqingan mortgage

Overview

"New Qing'an Mortgage" (full name: New Preferential Loan System for Young People to Start a Family with Peace of Mind) is a policy mortgage program launched by the Taiwanese government from August 2023 to assist young people in purchasing homes. Led by the Treasury Department of the Ministry of Finance and co-organized by eight public banks, it provides young first-time homebuyers with low interest rates and long-term loan programs. To reduce the financial pressure in the early stages of home buying.

Eight public banks hosted

1. bank of taiwan
2. land bank
3. Cooperative Treasury Bank
4. first bank
5. South China Bank
6. Changhua Bank
7. Mega Bank
8. Taiwan Small and Medium Enterprises Bank

Eligibility

• Age: Applicants must be over 20 years old.
• Nationality: Only nationals of the Republic of China.
• Name conditions: There is no self-owned residence in the name of the loan applicant, spouse and minor children.
• House use: limited to self-occupation, not for rental or commercial use.
• Area scope: limited to residences on the main island of Taiwan and its affiliated outlying islands.

loan terms

• Loan amount: up to NT$10 million.
• Loan ratio: up to 80% of the appraised or transaction price of the house.
• Loan term: up to 40 years.
• Grace period: In the first 5 years, you can choose to only pay interest and not repay principal.
• Interest rate discount: The fixed interest rate is 1.775% for the first two years, and the flexible interest rate starts from the third year (China Post two-year fixed deposit interest rate + 0.565% starting).
• Early settlement: Most banks waive liquidated damages or only charge handling fees.

Features and Advantages

• The government subsidizes the interest, and the interest rate is lower than that of ordinary commercial mortgages.
• It provides a repayment period and grace period of up to 40 years, with low upfront pressure.
• It can be combined with a home purchase loan guarantee fund to increase the success rate of loan approval.
• All eight public banks can apply, so the choice is highly flexible.

Limitations and Notes

• Restricted to first-time buyers, no self-owned residence is allowed under their name.
• The upper limit of the loan amount is limited. If the amount of the house purchase is too high, you will need to prepare a larger down payment.
• The interest rate is flexible. If the interest rate rises in the future, the repayment burden will increase.
• If you rent out or resell your home, you may lose your interest subsidy eligibility.

Application process

1. Confirm that you meet the qualifications (age, no house under your name, self-occupied use).
2. Prepare documents: ID card, household register, house purchase contract, financial resources or salary certificate.
3. Apply to any of the eight public banks.
4. The bank conducts credit review and appraisal.
5. After the loan is approved, the contract is signed and the appropriation and transfer procedures are completed.

in conclusion

• The New Qing'an Home Loan is an important policy of the Taiwanese government to assist young people in purchasing homes. It provides low-interest and long-term loans through public banks.
• Although interest rates are favorable, long-term repayment capabilities and housing market risks should still be carefully evaluated.
• When buying a house, you should base your purchase on the principle of "focusing on owning your own home and living within your ability", and avoid excessive leverage or speculative house buying behavior.

Mortgage limit trial calculation formula

1. Use the "monthly affordable amount" to infer the loan limit

1. The formula for equal amortization of principal and interest (monthly payment)

• r= monthly interest rate (annual interest rate ÷ 12)
• n= Total number of periods (number of years × 12)

2. Estimating the maximum loan amount based on "bank review rules"

1. Judge by “income”: DSR (debt burden ratio)

• DSR upper limit = 40% (common range 30% ~ 45%)

2. Determine based on "House Appraisal": LTV (Loan to Value)

• First purchase: 80% ~ 90%
• General loan: 70% ~ 80%
• Legal persons, investors, old houses: 40% ~ 60%

3. Sample calculation (demonstration of deducing the loanable limit)

condition:

• Annual interest rate: 2%
• Loan term: 30 years
• Monthly income: 80,000 yuan
• DSR：40%

Step 1: Calculate available monthly payment

Step 2: Use the formula to reverse the amount

4. Simplified version of trial calculation formula (quick estimate)

• Interest rate 1.7%～2.2%
• term 30 years

Summarize

• Revenue (DSR)
• House Valuation (LTV)
• Interest rate and loan period (affecting the loanability ratio)

Actual Review Factors for Mortgage Amount Receipts and Expenditures

1. What DSR (Debt Service Ratio) really covers

• monthly income(Salary, bonus, rental income...)
• all existing liabilitiesIncluding: mortgage, car loan, credit, student loan, credit card installment, revolving, policy loan, etc.
• short term liabilitiesSuch as: credit card outstanding balance, consumer loans, small installments, etc.
• Living expenses estimate(Internal bank regulations) The bank will estimate the minimum living expense threshold based on family size, age, and city and include it in the calculation.

2. Bank’s DSR calculation method in practice (simplified representation)

• Credit card revolving → The monthly payment is calculated as the revolving balance × 10%~15%
• Credit card outstanding → may be included in the liability with a fixed factor (e.g. 5%)
• Guarantor → Depending on the bank’s policy, some will be included in the calculation
• Short-term loans → always included in liabilities
• Living expenses → Although not included in DSR, it will affect "whether to approve"

3. The bank’s actual review process: whether it meets the standards, it must be approved

1. Confirm whether the source of income is stable (salary transfer, withholding vouchers, tax filing materials, etc.)
2. Calculate all liabilities and monthly payments
3. Check whether it complies with DSR (varying from 35% to 45%)
4. Estimated family living expenses → If the remaining amount after deducting living expenses is insufficient, the bank may not approve it.
5. Appraisal of house value → Determine LTV (loan to loan ratio)

4. Comprehensive formula (bank internal conceptual model)

5. Summary

• DSR not only looks at income, but also looks at the overall liability structure
• Both short-term and long-term liabilities will affect the loan limit
• The living expenses threshold will affect the loan approval, not the DSR indicator on the formula
• Even if the formula is passed, the loan will be rejected due to low appraisal value, professional risk, credit record, etc.

Disposable income multiple

Concept introduction

"Disposable income multiple" is also often called by banksRepayment ability multiple, is an additional "cash flow soundness" indicator used by some banks in addition to DSR (debt ratio) in home loan review. It is used to measure:Whether the borrower's total monthly income is sufficient to cover total expenses and leave a sufficient financial cushion.

Calculation formula

Disposable income multiple = (total monthly income) ÷ (total monthly expenses)

• Total monthly income:Salary, bonus average, fixed rental income, etc.
• Total monthly expenses:Existing loan (monthly payment), credit card fixed obligation expenditure, estimated living expenses, estimated monthly mortgage payment, etc.

Differences from DSR

DSR is "monthly payment of all liabilities/income", focusing on the proportion of liabilities; The disposable income multiple is "income/expenditure", focusing on overall living allowance.Although the two directions are opposite, they both reflect the financial pressure of borrowers.

Bank common standards

Each bank has different standards for multiples, but the common reference ranges are as follows:

• 2.0 times or more:Good financial margin and good repayment ability
• 1.5 ~ 2.0 times:Acceptable, subject to other review conditions
• 1.0 ~ 1.5 times:On the tight side, you may be asked to reduce the amount or add an insurance policy holder.
• <1.0 times:Expenses are greater than income, and in most cases the loan cannot be approved

Why do banks need this multiple?

Because DSR cannot take into account factors such as living expenses and household expenses, The disposable income multiple (repayment ability multiple) more completely reflects the actual cash flow. It can help banks reduce borrowers' future default risks.

Simple example

Monthly income: 90,000
Monthly expenditure: including existing loan + living expenses + future mortgage = 45,000

Disposable income multiple = 90,000 ÷ 45,000 = 2.0 times
→ Meets the safety standards of most public banks

redistricting

definition

Redistricting refers to the area where the government re-plans and integrates land in specific areas in accordance with relevant regulations such as the "Municipal Redistricting Regulations" or the "Section Expropriation Regulations". Its purpose is to improve the urban development structure, increase land use efficiency, improve the configuration of public facilities, and promote local construction and real estate market development.

Types of Redistricting

• City redistricting:It is carried out jointly by the government or landowners to increase the value of regional land through the rezoning of public facilities such as roads, parks, and schools.
• Sectional collection:Under the leadership of the government, the entire section of land is expropriated and then redistributed. The landowners can receive part of the rezoned land or compensation.
• Urban renewal area:It prefers the redevelopment of old urban areas and is led by private or public institutions. It is similar to the concept of redistricting but has different purposes.

Relationship with urban planning areas

development characteristics

• Land prices are low initially, but have high potential to rise as public facilities and construction are completed.
• Life functions are insufficient at the beginning, but have strong potential for growth in the future.
• It attracts more developers to promote projects and first-time homebuyers.
• The urban planning is complete, with straight roads, novel buildings and a high proportion of green space.

advantage

• The infrastructure is complete and the living quality is high.
• Roads and public facilities are well planned and the environment is tidy and novel.
• It has long-term value-added potential, especially if purchased in the early stages of construction.
• In the future, the commercial functions of the living area will gradually take shape, and housing prices will have strong support.

Disadvantages and Risks

• The initial living functions are insufficient and need to wait for construction to be completed.
• Builders are promoting concentrated projects and the short-term supply is large, so prices may fluctuate.
• If government construction is delayed, regional growth will stagnate and investment returns will decline.
• Some redistricting areas have too many lots, immature transportation, and long investment periods.

Finance and Loan Conditions

• Land and buildings in rezoned areas are generally regarded by banks as lower-risk assets due to their characteristics such as "clear legal zoning," "high ratio of public facilities," and "predictable completion of construction."
• When banks in some areas evaluate housing loans, the loan ratio, amount and interest rate conditions for properties in rezoned areas will be better than those in non-rezoned areas.
• Even in some cases, a house with the same conditions can be approved for loan if it is located in a rezoned area, but cannot be loaned if it is located in a non-rezoned or agricultural area.
• The main reasons are that the rezoning area has public facilities, complete transportation planning, high circulation, and low bank recovery risk.

Examples of major redistricting in Taiwan

• Taipei City:Neihu Phase 5 rezoning and Nangang Economic and Trade Park.
• New Taipei City:Linkou A9, Danhai New Town, Xindian Yangbei are rezoned.
• Taoyuan City:Qingpu High-speed Railway Special Zone and Middle Road Rezoning Area.
• Taichung City:The seventh phase of rezoning, Shuinan Economic and Trade Park, and the fourteenth phase of rezoning.
• Tainan City:Plain redistricting, South Coast special districting.
• Kaohsiung City:The 16th Agricultural Rezoning Area, the Art Museum Special Zone, and the Yawan New Bay Area.

Investment and home buying advice

• There is a price advantage in the initial stage, but attention should be paid to the construction progress and population introduction.
• Avoid excessive pursuit of high prices and observe actual residential demand and transportation development.
• If you live there for yourself, you can choose an area with school districts, parks and convenient transportation.
• If it is an investment, you should set up a mid- to long-term holding plan to avoid short-term fluctuation risks.
• When applying for a loan, you can compare the rezoning loan conditions of different banks and have the opportunity to obtain higher loan ratios and lower interest rates.

in conclusion

• Redistricting represents an emerging force in urban development, with both planning improvement and value-added potential.
• Banks generally have a high opinion of redistricting, and loan conditions are relatively friendly to home buyers.
• However, it is still necessary to carefully evaluate regional development progress and market supply and demand, and do not invest blindly.

Taipei City Housing Price Index

Taichung real estate

Top 10 short-term real estate crash cases in the world

1. Japan, Tokyo and other metropolitan areas (1989–1992)

• Period: from the second half of 1989 to mid-1992.
• Decline: About 70% or more, urban land and residential prices fell sharply.
• Supplement: From 1991 to 2009, Japan's housing prices showed a long-term downward trend, with the national average price falling by about 50% cumulatively, and it has not fully recovered in nearly 20 years.

2. Las Vegas, USA (2006–2010)

• Period: mid-2006 to 2009–2010.
• Drop: About 50–60%.

3. Ireland, mainly Dublin (2007–2010)

• Period: mid-2007 to mid-2010.
• Decline: Residential properties fell by about 35%, with the highest price in Dublin being 56%.

4. Spain Madrid, Barcelona, ​​etc. (2007–2013)

• Period: from 2007 to the end of 2013.
• The cumulative decline is approximately 45%, with annual declines reaching 9–10% in some areas.

5. Los Angeles and Phoenix, USA (2006–2009)

• Period: 2006 to 2008/2009.
• The decline can reach 30–40% in some urban areas.

6. San Jose, San Francisco, United States (1989–1995)

• Period: late 1989 to 1995.
• Real house prices fell by about 40%.

7. Toronto, Canada (1989–1996)

• Period: from 1989 to 1996.
• The average decline in the Greater Toronto Area is more than 27%.

8. Baltic States (Estonia, Latvia, Lithuania) (2007–2009)

• Period: from mid-2007 to 2009.
• House prices fell by more than 40%, especially in Latvia.

9. Dubai, United Arab Emirates (Q1 2009)

• Time period: Within the first quarter of 2009.
• Housing prices in some areas have fallen by approximately 40% in the short term.

10. China First-tier and some Second-tier cities (2021–2025)

• Period: 2021 to 2025.
• House prices in some cities have fallen by approximately 20-30% in four years.

Conclusion: Real estate also has risks

• Global history proves that housing prices do not always rise.
• The real estate market is affected by factors such as interest rates, policies, demographic structure, and the financial system. Severe fluctuations may cause heavy losses.
• When investing in real estate, you need to carefully assess your financial affordability, regional fundamentals and risks of future changes, and do not blindly pursue high prices or perform excessive leverage operations.

Japanese real estate

Market overview

The Japanese real estate market is known for its stability and attractiveness, especially in major cities such as Tokyo, Osaka and Kyoto. International buyers are increasingly interested in residential and commercial properties in Japan.

Major city real estate

Purchase process

1. Find the right real estate agency or website.
2. Select a property and schedule a site visit.
3. Negotiate price with seller or agent.
4. Sign the purchase contract and pay the deposit.
5. Complete tax payment and title registration.

Common taxes and fees

Investment advantages

• Stable rental income.
• Legal protection and transparent investment environment.
• Fluctuations in the Japanese yen exchange rate provide additional profit opportunities.

Common websites for real estate buying and selling in Japan

1. National real estate platform

• SUUMO（スーモ）One of the largest real estate platforms in Japan, operated by Recruit Holdings. Provides information on new construction, apartments, second-hand houses, land, rentals, etc. across the country, with many filtering conditions and frequent updates.
• LIFULL HOME'SIt has a large amount of housing information and can be searched carefully based on conditions such as region, route, school district, construction year, etc. It also provides house price trend charts and loan calculation tools.
• at homeOne of Japan's traditional real estate information websites. It has a large number of properties and is suitable for searching for second-hand apartments and houses. Support foreigners search and Japanese-English switching interface.
• Yahoo!Real EstateCooperate with multiple builders and agents to integrate new construction, apartment, land and leasing information. The website interface is intuitive and the search speed is fast.

2. Website dedicated to foreigners buying houses

• RealEstate.co.jpA Japanese-English bilingual real estate platform designed specifically for foreigners, supporting major cities such as Tokyo, Osaka, and Kyoto. Provides home buying guides, visa and loan information.
• Japan PropertyJapan’s official JLL is an English platform that cooperates with real estate developers, focusing on the foreign investor market. The information is transparent and the real estate is highly authentic.
• Rethink TokyoContains real estate news and analysis articles on the topic of life and investment for expats in Japan. Suitable for medium and long-term investors' reference.
• Mansion Global JapanThe Japanese branch of the international real estate media Mansion Global, covering high-end residential and investment properties. Provides English interface and market reports.

3. Local and high-end real estate websites

• Sumitomo Real EstateA real estate company under the Sumitomo Group, it focuses on high-end residences, apartments and commercial offices in Tokyo and Osaka. Provide services for corporate expatriates and high-net-worth individuals.
• Tokyo カンテイA housing price evaluation and market analysis website focusing on the Tokyo metropolitan area. Suitable for comparing locations and prices before investing.

4. Suggestions for use

• It is recommended to use multiple websites for cross-price comparison to confirm the authenticity of the property and the reasonableness of the price.
• Pay attention to whether it is marked "Media Company (Agent)" or "Vendor (Direct Sales)". The agency fee is approximately 3% of the house price + 60,000 yen.
• Foreigners who want to buy a house can look for an agency with English or Chinese services, or use foreigner-friendly platforms such as "RealEstate.co.jp".

Summarize

Japan mortgage

Loan Overview

Japan’s real estate loan policies are relatively friendly to foreigners, but certain conditions need to be met, including residence qualifications, income sources and credit records. Foreign buyers can usually apply for a property loan ratio of 50%-70%.

Loan type

Application conditions

• Age limit: Usually 20-65 years old.
• Stable income: Provide proof of income, such as salary or self-employed income records.
• Credit Assessment: Good credit history.
• Residency qualifications: Japanese residency status helps improve the loan approval rate, but some banks accept non-residents.

Application process

1. Choose the right bank or financial institution.
2. Submit loan application and relevant documents (passport, income certificate, real estate information, etc.).
3. The bank conducts credit assessment and property review.
4. Get loan approval and sign contract.
5. Complete property purchase and loan disbursement.

loan interest rate

Things to note

• Foreign currency loans: Some banks provide foreign currency loans, but you need to pay attention to exchange rate risks.
• Early repayment: Learn about early repayment fees and conditions.
• Insurance requirements: Loans often require mortgage or fire insurance.

Apply for a Japanese mortgage loan from a Taiwanese bank

Loan Overview

In Taiwan, some banks provide loan services specifically for purchasing Japanese real estate, which is suitable for buyers who do not have Japanese residence status or who want to take advantage of Taiwan's financial resources. Such loans usually need to be secured by existing assets or real estate, and the interest rates and loan terms may be slightly higher than those of local Japanese banks.

Suitable for objects

• Those who plan to purchase real estate in Japan but are unable to apply for a loan from a local bank in Japan.
• Investors who own Taiwan real estate as collateral.
• Buyers who wish to use Taiwanese funds for overseas investments.

Application conditions

• Age limit: between 20 and 65 years old.
• Proof of income: Stable job income or other legal sources of income.
• Good Credit: Credit score meets bank standards.
• Collateral: Local real estate in Taiwan or other acceptable collateral is required.

Application process

1. Choose Taiwanese banks that offer Japanese real estate loans, such as Fubon, Taishin, CITIC, etc.
2. Talk to your bank and find out about loan product terms and interest rates.
3. Prepare application documents, including passport, income certificate, Taiwan real estate information and Japanese real estate purchase contract, etc.
4. The bank conducts credit assessment and collateral review.
5. Get loan approval, sign contract and close disbursement.

Loan terms and interest rates

Things to note

• Exchange rate risk: Since loans are issued in New Taiwan dollars, the impact of exchange rate fluctuations needs to be considered when purchasing Japanese real estate.
• Collateral evaluation: Banks will evaluate Taiwan's collateral, which will affect the loan amount.
• Cross-border taxation: Understand the relevant tax policies of Taiwan and Japan to avoid additional burdens.
• Early repayment conditions: Confirm whether the loan allows early repayment and related handling fees.

Obtain financing funds from Japanese real estate

Do banks in Taiwan accept overseas real estate as collateral?

• Taiwan banks generally only accept "real estate in Taiwan" as loan collateral.
• Japanese real estate is an overseas asset, and Taiwanese banks cannot establish mortgage rights or enforce enforcement in Japan in accordance with the law.
• Therefore, even if you have purchased a Japanese house in full, it will be difficult to use the property to obtain a mortgage loan from a Taiwanese bank.

Main reasons for limitations

• Legal restrictions:Taiwanese financial institutions are unable to establish valid mortgage rights across borders.
• Difficulties in risk control:Lack of control over the value and liquidity of Japanese real estate.
• High difficulty in execution:Even if the borrower defaults, it will be difficult for the bank to dispose of the asset to pay off the debt.

Viable alternatives

• Japanese local bank loan:You can apply for a mortgage or financial loan from a Japanese bank, using the property as security.
• Loan secured by Taiwan assets:If you still have real estate in Taiwan, you can use the Taiwan real estate as a mortgage and use it flexibly after obtaining the funds.
• Private Credit or Asset Proof Loan:Some Taiwan wealth management institutions may provide credit products that use overseas assets as credit reference, but the interest rates and thresholds are higher.

Suggested direction

• If you want to use Japanese real estate as a resource to obtain funds, your first choice should be a local financial institution in Japan.
• If you are unable to obtain a loan in Japan, you can instead use Taiwan assets to raise funds and use funds indirectly.
• It is recommended to consult a cross-border asset management consultant or a professional international mortgage loan bank for planning.

Taiwanese apply for Japanese bank mortgage

Can I apply for a Japanese bank loan?

• Taiwanese can apply for real estate loans from some Japanese banks, even if they are not Japanese nationals.
• The regulations of different banks vary greatly, and whether you can get a loan depends on the bank's policies, personal background and property conditions.
• Some banks require proof of residence or work visa in Japan, but some banks accept non-residents (such as SinoPac Trust, Sumitomo Mitsui Trust, Rakuten Bank, etc.).

Common application requirements

• Be over 20 years old and have a stable income.
• Have good credit record and repayment ability.
• Some banks require a bank account or guarantor in Japan.
• The loan amount is usually 50% to 70% of the house price, subject to adjustment on a case-by-case basis.

Prepare documents

• Passport, residence card (if applicable), resident card or certificate of residence (if applicable).
• Proof of income and assets: such as salary slips, tax returns, and deposit certificates from Taiwan.
• House purchase contract, real estate information (real estate registration transcript, title deed, etc.).
• Loan application form and basic personal information.

loan process

• 1️⃣ Select the property and sign the reservation purchase contract.
• 2️⃣ Submit a loan application to the Bank of Japan and submit relevant information.
• 3️⃣ The bank conducts review and property appraisal.
• 4️⃣ After passing the review, sign the loan contract and set the mortgage rights.
• 5️⃣ The bank transfers funds to the designated account to complete the delivery of the house purchase.

Banks and financial institutions to contact

• Sumitomo Mitsui Trust Bank:Provide loan services to non-Japanese residents, with some language support.
• SBI Shinsei:Accepts Taiwanese buyers and has a special program for foreigners.
• Rakuten Bank:The Internet is highly accessible, the application process is simplified, and some real estate agents can handle it on your behalf.
• ORIX、ARUHI：Foreign loan options are also available.

Things to note

• Interest rates vary by bank, usually between 1.5% and 3.5% (floating or fixed).
• If you do not have Japanese residency status, the interest rate and loan ratio may be unfavorable.
• It is recommended to cooperate with a real estate agent or agency that is familiar with international real estate to assist with translation and process processing.

Mainland real estate unit conversion

Conversion formula

To convert the price per square meter in RMB to the price in Taiwan dollars per square meter, you need to follow the following steps to calculate:

1. Square footage conversion

1 square meter ≈ 0.3025 ping

2. Exchange rate conversion

Assume the current exchange rate is 1 CNY = 4.5 NT$ (for reference only, please confirm the latest exchange rate).

3. Calculation steps

Convert RMB prices to New Taiwan Dollars:
100,000 RMB/square meter × 4.5 NTD/RMB = 450,000 NTD/square meter

Convert square meters to square meters:
450,000 NTD/square meter ÷ 0.3025 ping/square meter ≈ 1.4876 million NTD/square meter

in conclusion

100,000 RMB/square meter ≈1.4876 million NTD/square meter

Remark

The above conversion is for reference only, the actual price needs to be adjusted according to the latest exchange rate.

real estate investment trust

Real Estate Investment Trust (REITs) is a financial instrument that "securitizes" real estate investment. By holding beneficiary certificates, investors indirectly participate in the investment of large-scale real estate such as commercial offices, department stores, hotels, or logistics centers, and share their rental income and value-added benefits.

Operating mechanism and revenue sources

The core logic of REITs is to convert long-term stable rental income into dividends and distribute them to investors:

• Asset composition:Mainly include office buildings, shopping malls, medical buildings or storage facilities.
• Source of income:The vast majority (usually more than 90%) of the rental income, after deducting management costs, must by law be distributed to the holders.
• Liquidity:Traded on a centralized market like stocks, they can be liquidated much faster than physical real estate.

Tax Advantages of Taiwan REITs

Investing in local REITs in Taiwan enjoys special tax benefits, which is an important reason to attract long-term investors:

• Separate taxation:Dividend income is subject to a separate tax of 6% and is not included in the calculation of personal comprehensive income tax, which has tax saving benefits for high-tax rate groups.
• Exemption from second-generation health insurance:Currently, REITs income distribution does not require the payment of second-generation health insurance supplementary premiums.
• Suspension of securities transaction tax:The collection of certificates and taxes on the purchase and sale of benefit certificates is currently suspended in accordance with the law.

Comparison with direct investment in real estate

Risk considerations

Although it has the characteristics of stable income, investors still need to pay attention to the following risks:

• Interest rate risk:When interest rates rise, REITs become relatively less attractive and borrowing costs may increase.
• Vacancy rate risk:If the proportion of the underlying properties (such as commercial offices) rented out decreases, it will directly reduce the dividends that can be distributed.
• Market supply and demand:The rise of e-commerce may impact physical mall REITs, while remote working may impact commercial REITs.

Currently, the main REITs in the Taiwan market include Cathay One (01002T), Fubon One (01001T), etc. If pursuing a wider range of options, many investors will also allocate to REITs in the U.S. market to diversify industry risks.

Tokenization of real estate physical assets

RWA is the abbreviation of Real World Assets. Real estate RWA refers to converting claims or ownership of physical properties into digital tokens (Tokens) through blockchain technology. This allows investors to buy fractional shares of real estate much like buying and selling cryptocurrencies.

core operating mechanism

The process of real estate RWA usually involves the legal confirmation and digitization of assets:

• Asset fragmentation:Divide a commercial office or residence worth hundreds of millions of yuan into tens of thousands of digital tokens to lower the investment threshold.
• On-chain contract:Automatically execute rent allocation, voting rights or transfer procedures through smart contracts.
• Legal structure:A special purpose vehicle (SPV) is usually established to hold real estate, and the equity or debt of the SPV is linked to the token to ensure legal validity.

Advantages of Real Estate RWA

• Extremely low investment threshold:Investors can participate in high-threshold commercial investments with an amount of US$100 or less.
• 24/7 liquidity:Unlike traditional real estate transactions, which take months, RWA tokens can be traded on the secondary market 24 hours a day.
• Transparency and automation:All transaction records and rent distribution are recorded in the blockchain, which cannot be tampered with and reduces manual operation costs.
• Cross-border investment:Global investors can easily participate in the real estate markets of different countries through the decentralized finance (DeFi) platform.

Differences between RWA and REITs

Development challenges and risks

Despite its great potential, RWA still faces the following practical difficulties:

• Regulatory Compliance:Countries have different definitions of the security attributes of tokenized assets, which must comply with securities trading regulations (such as KYC/AML specifications).
• Oracle data accuracy:The value assessment of physical real estate relies on a third party (oracle) to transmit off-chain data back to the chain, and there is a risk of information gaps.
• Legal recourse:When a dispute occurs, the order of compensation for digital token holders in the substantive legal system still needs to be improved by regulations.

Currently, world-renowned real estate RWA platforms include RealT, Propy, etc. However, in Taiwan, related applications are still restricted by financial regulations and are mostly in the stage of sandbox experiments or specific private equity cases.

rent a house

In addition to searching for properties through traditional platforms when renting houses in Taiwan, in recent years there have been major changes in regulations regarding tenants’ rights, rent subsidies and electricity billing. The following is the latest rental guide for 2026:

Mainstream rental platforms and search channels

• Comprehensive platform:591 House Transaction Network, Lewu.com, Haofang.com. This type of platform has the most complete objects, but you need to pay attention to the timeliness of information update.
• Social media:Facebook rental groups (such as Taipei rental, Taichung rental, etc.). The advantage is that you can communicate directly with the landlord or current tenant, but the risk of fraud is higher.
• Symbiotic apartments and brand rentals:Home Sweet Home, 9floor, Alife. Suitable for people with higher budgets who value quality of life and social interaction.
• Government platform:The Home Office’s social housing tenancy management scheme is suitable for tenants who meet certain status conditions and enjoy rent discounts.

2026 New Rent Subsidy System

The government’s 30 billion yuan central government rental subsidy project has been extended to 2026. The key rules are as follows:

• Legal residential restrictions:Starting from January 1, 2026, the house rented by new applicants must be a legal residence (with building registration, tax registration as a residence, etc.). Rooftop additions or illegal construction will be excluded from the scope of subsidies.
• Application threshold:You can apply if you are 18 years of age or older. You do not need the landlord’s consent, nor do you need to provide the landlord’s ID number.
• Income restrictions:The average monthly income of each family member must be less than 3 times the minimum living expense in the place where the rental house is rented (for example, about NT$61,000 in Taipei City).
• Added objects:Single young people (1.2 times), newlywed families (1.3 times), and families with children (from 1.4 times) all have increased amounts.

Lease contract legal points

Essential checklist before signing a contract

• Identity check:The landlord is required to show his ID card and house ownership certificate (or copy) to confirm that the signatory is the owner.
• Equipment point delivery:Take photos and documents of furniture and home appliances, and test whether the functions are normal one by one. Attach the list to the back of the contract.
• Repair Responsibilities:Unless otherwise agreed, in principle, the landlord is responsible for repairing structural and fixed equipment (such as water leaks and water heaters).
• Tax reminder:If the landlord directly notes the rent received and signs it on the lease, he must affix a stamp tax of 4%, otherwise he will face a suspended fine. It is recommended to keep records via bank transfer.

If your current rental object is a specific type of property (such as a shared apartment or social housing), it is recommended to confirm its tax status first, so as not to affect your subsequent application qualifications for rental subsidies.

Long term lease specifications

Long-term rentals (more than 30 days) in Taiwan are mainly regulated by the Civil Code and the Rental Housing Market Development and Management Regulations (referred to as the Rental Law). Starting from 2026, the government will implement a number of new systems for tenant protection and market transparency.

Legal system and applicable objects

• Applicable definitions:Buildings used for residential purposes and with a lease period of more than 30 days.
• Core regulations:
  • "Civil Law": regulates the general lease-creditor-debt relationship.
  • "Regulations on the Development and Management of the Rental Housing Market": a special law for residential leasing, which is superior to the civil law.
  • Article 100 of the Land Law: Conditions restricting the lessor from taking back the house.

Three key points of the latest rental policy in 2026

In line with the government's "Rental Housing Improvement" policy, the core regulations to be implemented after 2026 are as follows:

• Three-year lease guarantee:Grant tenants the "right of first refusal" to renew the lease, ensuring that the total term of the contract and renewal is at least 3 years. Unless the landlord takes back the owner-occupied property or the tenant breaches the contract, the landlord may not refuse to renew the lease without reason.
• The upper limit of contract renewal increase:If the landlord wants to adjust the rent for renewal, he must give six months' notice, and the increase must not exceed the annual increase rate of the "Rent Index of the Executive Yuan Accounting Office" (currently around 2%).
• Rent transparency obligations:The competent authority regularly publishes the "median rent per square meter" in each area based on the age and type of housing, and landlords are not allowed to hide actual transaction information.

Deposits, electricity bills and contract mandatory provisions

New threshold for rent subsidy in 2026

Starting from January 2026, “legal residence” restrictions will be added to long-term rental subsidy applications:

• Exclude illegal construction:The property to be rented by the new applicant household must be registered as a building or tax registered as a residence. Attic additions, illegal partitions, and unregistered buildings will not be able to pass the subsidy review.
• Incentives for landlords to report:Provide tax incentives for public lessors (monthly tax exemption of RMB 15,000) to encourage landlords to cooperate with tenants in applying for subsidies.

Comparison of long-term and short-term rental management mechanisms

In summary, long-term rental regulations are developing towards "contract standardization" and "lease term stabilization". If you are a landlord, it is recommended to use the latest version of the Ministry of Interior’s standardized contract; if you are a tenant, the new system in 2026 will provide stronger contract renewal protection and price transparency.

Bed and Breakfast for Rent

Operating a B&B in Taiwan must comply with the Tourism Development Regulations and B&B Management Measures. Legal operations not only involve the use of buildings, but are also closely related to zoning.

Legal business practices

• Core definition: refers to an accommodation place that utilizes spare rooms in self-occupied residences, operates as a family side business, and combines local culture and landscape.
• Limit on the number of rooms: Generally, the maximum number of guest rooms in a B&B is 8, and the total floor area must be less than 240 square meters.
• Relaxation of special cases: The upper limit can be relaxed to 15 rooms and an area of ​​400 square meters in aboriginal areas, remote areas, outlying islands or leisure farms approved by the Agriculture Committee.
• Location restrictions: Mainly open to non-urban land, specific scenic areas, tourist areas, etc. Generally, collective housing buildings in cities cannot legally apply to be B&Bs.

Mainstream listing platforms and URLs

• Airbnb Taiwan: https://www.airbnb.com.tw/(The world’s largest short-term rental platform, suitable for attracting tourists from all over the world)
• AsiaYo： https://asiayo.com/(Taiwan’s largest hotel booking platform, deeply involved in the Asian market)
• Booking.com： https://www.booking.com/(With a powerful back-end management system, suitable for stable order collection)
• Taiwan Travel and Accommodation Network: https://taiwanstay.net.tw/(Official legal directory inquiry and information release platform)

Application process and licenses

Operators who operate without a registration certificate will face a fine of NT$100,000 to NT$1 million. The procedures are as follows:

1. Confirm whether the land use zoning complies with the "areas where B&Bs can be applied for" announced by the local county and city government.
2. Submit application form, proof of land/building consent, usage license, and copy of liability insurance contract.
3. Pass a fire safety inspection to ensure fire extinguishers, fire alarms and emergency lighting are installed.
4. Only after receiving the B&B registration certificate and special signage can you start advertising and doing business.

tax regulations

Since various county and city governments (such as Yilan, Pingtung, and Nantou) have different regulations on the management autonomy of B&Bs, it is recommended to confirm the latest announcement information with the tourism bureau of the county or city before choosing a location.

Listing on Airbnb

Listing real estate on Airbnb and converting it into short-term rental income is a common way to increase real estate cash flow. However, when operating in Taiwan, special attention needs to be paid to regulatory restrictions and operational details.

Legality confirmation and regulatory risks

Operating short-term rentals (less than 30 days) in Taiwan is strictly regulated by the Tourism Development Ordinance:

• Hotel and B&B licenses:It is often difficult to obtain a B&B license for apartments or buildings in urban residential areas. If you list a hotel or B&B to provide accommodation without a legal license, you may face a fine of NT$100,000 to NT$500,000 and may be ordered to suspend business.
• Apartment building management regulations:Many community management committees have revised their bylaws through residents’ meetings to prohibit residents from operating short-term rentals (such as Airbnb). It is necessary to confirm the content of the regulations before putting them on the shelves to avoid legal disputes caused by complaints from neighbors.

Preparation steps for launch

• Space preparation:Make sure the infrastructure (Wi-Fi, hot water, air conditioning) is functioning properly and provide high-quality bedding and supplies to improve your rating.
• Professional Photography:Airbnb is an extremely visual platform. Using professional wide-angle photography and shooting during the day when the lighting is good can significantly increase your click-through rate.
• Copywriting:The title should include a landmark or feature (e.g. near MRT station, balcony with view). House rules need to be clearly stated in the description to reduce subsequent cognitive errors.

Pricing strategy and profit optimization

Operational automation management

In order to reduce labor costs, mature landlords usually establish the following systems:

• Self check-in:Install an electronic code lock or set up a key box to allow guests to check in smoothly at any time.
• Outsourcing cleaning:Work with a professional cleaning team and pass cleaning fees on to guests.
• Automatic message:Preset check-in instructions, transportation suggestions, and check-out reminders to ensure immediate and consistent communication.

In summary, although Airbnb can provide higher gross profits (about 1.5 to 2.5 times) than traditional long-term rentals, its operating costs and regulatory risks are also relatively high. For investors, it is recommended to first evaluate the reporting risks and the possibility of obtaining a legal license in the area.

Sub-leasing from second landlord

When operating a sublease business in Taiwan, the first condition is to ensure the legality of the “sublease right”. Subletting without the consent of the original landlord will result in the original lease being terminated and the sub-tenant (second tenant) being liable for compensation.

1. Necessary conditions for legal subletting

• Written consent:According to the special leasing laws, subletting must obtain the "written consent" of the original landlord. In practice, it is recommended to directly add the clause "the lessor agrees to the lessee to sublet all or part of the house" in the original lease.
• Show proof to sub-tenant:When signing a contract with the second tenant, the second landlord is legally obligated to proactively produce "the original landlord's written document agreeing to sublease" and "the contents of the original lease contract" to prove that the sublease is legal and the lease term has not exceeded the original contract.
• The original lease period must not exceed:The sublease period of the second landlord must not exceed the remaining lease term signed between the second landlord and the big landlord.

2. Full sublease vs. partial sublease

3. Differences between personal subletting and professional chartering

In the market environment of 2026, the identity of the second landlord determines the depth of applicable regulations:

• Natural person second landlord:Occasionally or only subletting a single property. It should be noted that if there are "repeated operations", it may be recognized as a "charter management industry".
• Charter industry (legal entity):If you operate on a large scale, you must establish a company, pay a business deposit, and be managed by a licensed "rental housing manager." When signing a contract, you must use the Ministry of the Interior's version of the "Residential Sublet Standardized Contract."

4. Business risks and maintenance responsibilities

• Joint and several compensation:If the second tenant damages the house or violates the rules of the apartment building, the major landlord has the right to directly require the second landlord to be responsible for repairs or compensation. The second landlord cannot avoid liability to the larger landlord on the grounds that "the second tenant caused the damage."
• Rent difference and tax:The difference in rent earned by the second landlord is considered “property rental income” and should be included in the annual comprehensive personal income tax return. If it is a chartered management business, it shall be reported in accordance with the Business Tax Law.
• Deposit limit:The maximum deposit chargeable to a second tenant is also protected by law and cannot exceed 2 months’ total rent.

5. Challenges to second landlords under the new system in 2026

As the government promotes the improvement of rental housing, second landlords are facing the following trends:

• Rent subsidy and household registration:Starting from 2026, the government will strengthen the identification of legal residences. If the second landlord sublets an illegal attic addition, the second tenant will not be able to apply for rent subsidies, which will reduce the market competitiveness of the property.
• Transparency of electricity bills:The electricity fee charged by the second landlord to the second tenant is strictly prohibited from being higher than the current average electricity price per kilowatt hour in Taipower's bill. If the second landlord earns the difference through high electricity bills, he will face heavy fines if reported.

It is recommended that before you start the second-tenant business, you must first obtain a "sublet authorization letter" from the big landlord and confirm whether the property has legal tax registration or building registration. This will directly affect the quality of your second-tenants and the stability of your business.

loan

definition

A loan refers to the act in which a borrower (individual or corporate) obtains funds from a financial institution or other lender and promises to repay the principal and interest at an agreed interest rate within a specific period of time.

Main types

• personal loan: Used for consumption, tourism, medical treatment, etc., usually unsecured and with higher interest rates.
• home loan: Real estate is used as mortgage, with long term and low interest rate.
• car loan: Use the purchased car as collateral and repay it in installments.
• business loan: Enterprises use it for operations, expansion or capital turnover.
• credit loan: No mortgage required, the limit is determined based on the borrower’s credit score.
• government subsidized loans: Specific policy support and preferential interest rates.

key elements

• loan amount
• Interest rate (fixed or floating)
• Repayment term and method (average principal and interest, average principal, one-off payment at maturity, etc.)
• Collateral or guarantor
• Penalties for breach of contract

advantage

• The funds you need are immediately available.
• It can be used for projects with high capital requirements such as investment, house purchase, and entrepreneurship.
• Installment repayments relieve short-term financial stress.

risk

• Interest costs need to be borne, and the long-term burden may be heavier.
• If your income is unstable, you may face default and credit damage.
• Mortgage assets may be auctioned due to default.

Pre-loan advice

• Assess your own solvency and repayment plan.
• Compare interest rates and terms of different loan options.
• Find out whether there are any penalties for early repayment.

Taiwan loan account

Subject 1: Home Purchase Loan

• Purpose: Purchase of residential real estate.
• Features: Funds are directly transferred into the designated account, which is strictly supervised by the central bank and is prohibited from being used for other purposes.
• Restrictions: House purchase loans are not allowed to be used in other categories such as "working capital".

Subject 2: Loan for purchasing movable property

• Purpose: Purchase movable property, such as cars, machinery and equipment, etc.
• Features: The purpose of the loan must be clear, and the flow of funds is subject to review by financial institutions.

Subject Three: Enterprise Investment Loan

• Purpose: Enterprises use it for capital expenditures such as investment, production expansion, and equipment purchase.
• Features: A detailed investment plan and fund utilization details are required.

Subject 4: Working capital loan

• Purpose: Short-term funding needs of individuals or businesses, such as debt consolidation, daily working capital, etc.
• Features: Existing assets are used as guarantee, and the use of funds is more flexible.
• Restrictions: Cannot be used to purchase real estate or repay mortgages. Violations may result in loan repossession.

DBR22 debt ratio

DBR22 is an important red line for the Financial Supervisory Commission when regulating banks’ approval of unsecured loans. However, in practical terms, the calculation method of "monthly income" in the formula does not have a unified national regulatory standard, which gives each bank a great deal of room for independent definition.

Bank autonomy in determining monthly income

Although the upper limit of DBR22 is clear, how to calculate the "monthly income" as the denominator is determined by each bank based on its internal risk control policy. This also results in significant differences in the calculated maximum loan amount for the same borrower when applying from different banks.

• No legal formula:The Financial Supervisory Commission only requires banks to review their repayment ability and does not stipulate what documents or calculation formulas must be used for monthly income.
• Differences in bank internal regulations:Banks will adjust the acceptance rate of income certificates based on their own lending preferences (such as preference for high-quality corporate employees or civil servants).

Common ways to determine income

In practice, banks usually use the following methods to "define" your monthly income:

Details of handling bonuses and variable income

Since each bank defines monthly income by itself, the criteria for determining non-fixed salary are as follows:

• Year-end and performance bonuses:Some banks consider it normal income (divided by 12 to include monthly salary), but some conservative banks may not include it at all, or only include a certain percentage.
• Business commission:For business positions such as insurance and real estate agency, banks usually take a longer-term average (such as 12 months), and the deemed amount is often lower than the actual salary received.
• Professional qualification certification:Some banks will directly provide higher preset monthly income estimates for occupations such as doctors, lawyers, accountants, etc.

Liaison Center B68 The role of the report

Although income is defined by the bank, the "total unsecured debt balance" is based on the Lianzheng Center data:

• B68 products:The bank will access "DBR 22 times standard unsecured debt and annual income information".
• Data check:Although the annual income information uploaded by each bank will be included in the report, the auditing bank still has the right to "not use" the income data reported by other banks and instead use the standards determined by the bank.

In summary, if you are denied a loan at Bank A due to insufficient DBR22 space, it does not mean that the same will be true at Bank B. It is recommended to look for a bank that is more lenient in determining your professional attributes or bonus structure in order to obtain a higher loan amount.

discount

What is interest discount?

Interest discount is a method of interest payment commonly used in financial transactions such as bills, short-term financing or bonds. It means that the interest payable is deducted from the principal before the loan or note matures. The borrower actually receives less than the face amount, but still needs to repay the full principal when it matures.

How interest discounts work

• When a financial institution or creditor issues a loan or purchases a note, it will first calculate the interest payable throughout the period.
• The interest amount is deducted directly when the funds are disbursed.
• The borrower is required to repay the full principal amount when due, not the net amount actually received.

Interest discount calculation formula

Interest discount amount = face amount × annual interest rate × number of loan days ÷ 365
Actual amount received = Face amount - Interest discount amount

Examples of interest discounts

Assume that a company issues a commercial promissory note with a face value of NT$1,000,000, a term of 180 days, and an annual interest rate of 4%.

• Interest discount amount = 1,000,000 × 4% × (180 ÷ 365) ≈ 19,726 yuan
• Actual amount received by the enterprise = 1,000,000 - 19,726 ≈ 980,274 yuan
• Amount to be repaid at maturity = 1,000,000 yuan

Advantages and disadvantages of interest discounts

• advantage:Lenders can collect interest in advance to reduce credit risks; borrowers can quickly obtain funds.
• shortcoming:The borrower's actual available funds are less than the face amount, and the actual effective interest rate will be higher than the advertised interest rate.

Application scenarios for interest discounts

• commercial paper discount
• short term financing loan
• The issuance of some bonds (such as discounted Treasury bills)

bond

definition

A bond is a fixed-income security that represents an agreement by the issuer to borrow money from an investor and promises to pay interest at a fixed time and to repay the principal at maturity.

type

• Government bonds:Issued by the government, it has lower risks and is suitable for conservative investors.
• Corporate bonds:Issued by enterprises, the returns are higher but the risks are also higher.
• Municipal Bonds:Issued by local governments or municipal agencies, they often enjoy tax benefits.
• Convertible bonds:Can be converted into company stock under certain conditions.

Features

• Fixed income:Provide stable interest income.
• Lower risk:Compared with stocks, they have less volatility and lower risks.
• Liquidity:Can be bought and sold on the secondary market, but prices may be affected by market fluctuations.
• Credit Rating:Credit rating agencies evaluate the risk of bonds to help investors make decisions.

Source of income

• Coupon interest:Interest income paid at a fixed rate.
• Capital gains:Proceeds from selling a bond after its price rises.

risk

• Credit risk:The issuer is unable to make interest or principal payments when due.
• Interest rate risk:When interest rates rise, bond prices may fall.
• Market risk:Changes in market supply and demand will affect bond prices.
• Inflation risk:Inflation reduces the purchasing power of fixed income.

in conclusion

Bonds are an investment tool with stable and predictable returns, suitable for investors seeking fixed income and low risk. However, they still need to pay attention to interest rate changes and credit risks to ensure the stability of investment returns.

national debt

What is a national debt?

Treasury bonds are bonds issued by governments as a way to raise funds. Treasury bonds are issued to investors when the government needs funds to pay for public spending, infrastructure, or economic stimulus programs. The holder of a Treasury bond borrows money from the government, and the government promises to pay interest within a certain period of time and repay the principal at maturity.

Types of Treasury Bonds

• Short-term Treasury bonds:The term is short, generally less than one year, and is mainly used to respond to the government's short-term funding needs.
• Medium-term Treasury Bonds:Tenors typically range from one to ten years, suitable for investors looking for stable medium-term returns.
• Long-term Treasury bonds:The term exceeds ten years and is mainly used for large-scale infrastructure construction with high capital costs.
• Floating rate Treasury bonds:Treasury bonds whose interest rates adjust with market changes allow investors to obtain higher interest rates based on market conditions.
• Inflation-linked Treasury bonds:The interest is adjusted with the inflation index, providing income protection against inflation.

Advantages and Risks of Treasury Bonds

Advantages

• Low risk:Treasury bonds are guaranteed by the government, have low credit risk, and are considered safer investment instruments.
• Stable returns:Treasury bonds typically offer fixed interest rates, so investors can expect stable returns.
• Anti-inflation options:Inflation-linked Treasury bonds protect investors from inflation.

risk

• Interest rate risk:When market interest rates rise, the price of government bonds will fall, affecting the secondary market value of government bonds.
• Liquidity risk:Certain long-term Treasury securities may be less liquid and investors may not be able to sell them quickly when they need funds.
• Credit risk:Although national debt is guaranteed by the government, there is still a certain amount of credit risk if the government's financial condition is unstable.

Reasons to invest in Treasury bonds

Investors typically choose Treasury bonds because of their low risk and stable returns. Treasury bonds are an attractive investment vehicle for conservative investors who want to protect their capital and obtain fixed income. In addition, Treasury bonds can also help diversify portfolio risks and improve the stability of the overall portfolio.

Application scenarios of national debt

• Retirement funds:Treasury bonds are often included in retirement funds to provide stable long-term income.
• Insurance company:Insurance companies typically purchase Treasury bonds to manage funds and ensure stable capital reserves.
• Individual investors:For individuals with lower risk tolerance, Treasury bonds provide an option to protect principal.

The future trend of national debt

As global economic uncertainty increases, countries' demand for national debt is likely to grow. The central bank's monetary policy and interest rate changes will continue to affect the Treasury market, especially if inflation is high or interest rates are rising, investor demand for inflation-linked Treasury bonds may increase. In addition, the issuance of digital government bonds may also become a future trend, bringing more convenience and transparency to the government bond market.

U.S. Treasuries

What are U.S. Treasuries

U.S. Treasury bonds are bonds issued by the U.S. federal government to raise funds to pay for government spending and meet fiscal obligations. These bonds are considered one of the safest investment vehicles in the world because they are backed by the credit of the U.S. government.

Main types

• Treasury Bills (T-Bills): have a maturity date of one year or less. Short-term bonds are suitable for investors who want to receive steady interest payments.
• Medium-term Treasury Notes (T-Notes): Maturities range from 2 to 10 years.
• Long-term Treasury Bonds (T-Bonds): Maturity date is 30 years. Long-term bonds are often used as safe-haven investments in anticipation of a downturn in the economy. Poor economic climate -> interest rate cut -> long-term bond interest advantage -> long-term bond rise.
• Inflation-Protected Securities (TIPS): The principal value is adjusted based on the rate of inflation.

Purchase method

Investors can purchase U.S. Treasury bonds in the following ways:

• Directly from the U.S. Treasury DepartmentTreasuryDirectPurchase on the platform.
• Purchase through a bank or broker.
• Transactions in the secondary market.

Investment advantages

• High security: credit guarantee provided by the US government.
• High liquidity: can be bought and sold in the secondary market at any time.
• No state and local income taxes: Interest income is subject only to federal income taxes.

Potential risks

• Interest rate risk: Rising interest rates could cause bond prices to fall.
• Inflation risk: Inflation may erode real returns.
• Exchange rate risk: For non-U.S. dollar investors, exchange rate fluctuations may affect returns.

U.S. Bond ETF

Definition of U.S. Treasury ETF

U.S. Treasury ETFs are investment tools that focus on tracking the performance of U.S. Treasury bonds. These ETFs invest in U.S. Treasury bonds of varying maturities, allowing investors to easily participate in the U.S. Treasury market and enjoy the benefits of diversification.

Main types

• Short-term U.S. Treasury Bond ETF: tracks U.S. Treasury bonds with maturities of less than 1 year.
• Mid-term U.S. Treasury Bond ETF: Tracks U.S. Treasury bonds with maturities between 2 and 10 years.
• Long-term U.S. Treasury Bond ETF: tracks U.S. Treasury bonds with maturities of more than 10 years.
• Comprehensive U.S. Treasury Bond ETF: Covers U.S. Treasury bonds of different maturities.
• Inflation-Protected Securities ETF: Invests in U.S. Treasury Inflation-Protected Securities (TIPS).

Investment advantages

• Convenience: Diversify your investment in a variety of U.S. Treasury bonds through one ETF.
• Liquidity: Can be bought and sold on exchanges like stocks.
• Lower fees: ETFs generally have lower management fees than holding a variety of bonds directly.

Risk considerations

• Interest rate risk: Rising interest rates may cause the price of an ETF to decline.
• Market Risk: Even with U.S. Treasury bonds, the price of an ETF can still be affected by market fluctuations.
• Tracking Error: An ETF's performance may deviate slightly from its benchmark index.

Things to note when choosing U.S. Treasury ETFs

• Investment objectives: Choose the appropriate ETF based on your risk tolerance and investment horizon.
• Expense Ratio: Compare the management fees of different ETFs and choose the lower-cost option.
• Scale and liquidity: Choose ETFs with large trading volume and stable scale to ensure liquidity.

U.S. Bond ETFs in Taiwan Stocks

Overview of Taiwan Stocks and U.S. Bond ETFs

Taiwanese investors can participate in the U.S. bond market through U.S. Treasury Bond ETFs listed on Taiwan stocks to achieve asset allocation and stable income. The following are several major U.S. bond ETF targets:

Main U.S. Treasury ETF targets

• Yuanta U.S. Bond 20 Years (00679B)
  • Date of establishment: January 17, 2017
  • Tracking Index: ICE U.S. Government 20+ Year Bond Index
  • Investment target: U.S. government bonds over 20 years
  • Frequency of dividend distribution: February, May, August and November every year
  • Features: Large scale and high liquidity, suitable for investors pursuing long-term stable returns
• Cathay Pacific 20-Year U.S. Bond (00687B)
  • Date of establishment: April 13, 2017
  • Tracking index: Bloomberg 20+ U.S. Treasury Bond Index
  • Investment target: U.S. government bonds over 20 years
  • Frequency of dividend distribution: March, June, September and December every year
  • Features: Large number of beneficiaries, stable dividend distribution, suitable for investors who need regular cash flow
• CITIC U.S. Treasury Bond 20 Years (00795B)
  • Date of establishment: 2020
  • Tracking index: Bloomberg 20+ U.S. Treasury Bond Index
  • Investment target: U.S. government bonds over 20 years
  • Frequency of dividend distribution: January, April, July and October every year
  • Features: Low expense ratio, suitable for investors pursuing cost-effectiveness
• Unified US debt for 20 years (00931B)
  • Date of establishment: 2021
  • Tracking index: Bloomberg 20+ U.S. Treasury Bond Index
  • Investment target: U.S. government bonds over 20 years
  • Frequency of dividend distribution: February, May, August and November every year
  • Features: Small scale, but stable performance, suitable for diversifying investment risks
• Wing Fung 20-Year U.S. Treasury Bond (00857B)
  • Date of establishment: September 30, 2019
  • Tracking index: Bloomberg 20+ U.S. Treasury Bond Index
  • Investment target: U.S. government bonds over 20 years
  • Frequency of dividend distribution: March, June, September and December every year
  • Features: Stable liquidity, suitable for long-term holding investors

Factors to consider when choosing U.S. Treasury ETFs

• Investment period:Long-term bonds are more sensitive to changes in interest rates and are suitable for investors who expect interest rates to fall.
• Dividend frequency:Choose a suitable dividend payment month based on your personal cash flow needs.
• Scale and Liquidity:Larger ETFs generally have better liquidity and lower transaction costs.
• Expense rate:Pay attention to the management fees of ETFs. ETFs with lower expense ratios can increase net income.

Things to note

• Although U.S. Treasury ETFs have lower risks, they are still affected by changes in interest rates, which may affect prices and returns.
• Before investing, you should understand the investment objectives, fee structure and risk rating of ETFs to ensure that they meet your own investment objectives and risk tolerance.
• Regularly review the investment portfolio and adjust the position proportion according to market changes to achieve the best investment results.

U.S. Treasury yield curve spread

The difference between U.S. 2-year and 10-year Treasury bond yields (2Y-10Y Spread) is one of the most closely watched single indicators in global financial markets. It is not only a predictor of economic recession, but also a core tool for understanding capital rotation, sector switching and market tops and bottoms. The following is a complete analysis from the mechanism principles, historical verification, four curve types, practical applications to the particularities of the current cycle.

Basic Mechanism: Why Interest Rate Spreads Predict Markets

Under normal circumstances, the longer investors lend funds, the higher the compensation (yield rate) required, so the 10-year yield is usually higher than the 2-year yield, the spread is positive, and the curve slopes upward. When this relationship is broken, it represents a fundamental change in the market's expectations for the future economy.

The 2-year yield mainly reflects the market's expectations for the Federal Reserve's interest rate policy in the next one to two years and is highly sensitive to short-term monetary policy. The 10-year yield reflects long-term economic growth and inflation expectations, and is affected by global capital flows, fiscal policy and term premium (Term Premium). When investors expect that the economy will weaken, they will snap up long-term bonds to lock in yields and push down 10-year interest rates. At the same time, if the Federal Reserve still maintains high interest rates to fight inflation, short-term interest rates will remain high, and the intersection between the two will form an "inversion."

The reason why this mechanism is important to the stock market is that it directly affects three things: banks' willingness to lend (banks are unprofitable when interest rate spreads narrow, and credit is tight), corporate financing costs (distortion of long-term and short-term interest rates increases uncertainty), and investors' risk appetite (recession signals sent by the bond market will suppress demand for risky assets).

Four types of changes in the yield curve

It is very important to understand these four patterns, because they are also "interest spreads widening", and bullish steepness and bearish steepness have completely opposite meanings to the stock market. Bullish steepness (rapid decline in the short-term) is usually a precursor to recession, while bearish steepness (rising in the long-term) may reflect a pickup in inflation during the economic recovery period.

The temporal relationship between inversions and the market in history

Since 1968, the 2Y-10Y spread inversion has successfully predicted seven of the past eight recessions with 87.5% accuracy. But the inversion itself is not a sell signal. The real risk often appears long after the inversion.

The table above reveals several key patterns. First of all, after the past four 2Y-10Y interest rate spread inversions, the S&P 500 rose by an average of 28.8% before peaking. After the inversion occurred, the rush to sell has missed a large portion of the gains. Second, the average time from inversion to recession is about 22 months, and the median is about 20 months. This time difference makes inversions a useful but very imprecise timing tool. Third, for an inversion that lasts for more than three months, the probability of recession jumps from 45% to 73%. The depth and duration of the inversion are more important than the inversion itself.

The real danger: Un-Inversion

Many investors mistakenly believe that the return of the curve from inversion to normal means "the crisis is over", but historical experience is exactly the opposite. An un-inversion of a curve usually means a recession is coming within a year, which is a more urgent signal than the inversion itself.

The reason is that the unwinding of an inversion usually occurs in a "bullish" manner, that is, the Federal Reserve begins to cut interest rates due to the deterioration of the economy, and short-term interest rates fall rapidly. Historically, this bullish pattern is not a signal of economic recovery, but rather marks the "final countdown" before entering an actual economic contraction.

A complete market cycle cycle usually looks like this:

1. The Fed begins to raise interest rates → the curve is "flattening" → the stock market is still rising but momentum is weakening
2. Short-term interest rates exceed long-term interest rates → the curve "inverts" → the stock market may continue to rise for 6 to 18 months
3. Economic data begins to weaken → the Fed turns dovish or cuts interest rates → the “bullish steep” curve is lifted → this is the most dangerous moment
4. Recession officially arrives → Stock market falls sharply → Curve continues to steepen
5. Recession bottoms → Fed’s sharp rate cut completes → Curve returns to normal steepness → A new round of bulls begins

The particularity of this cycle 2022-2025

The inversion from July 2022 to November 2023 lasted for 16 months, which is the longest inversion record in modern history. However, as of now (March 2026), there has not been a traditionally defined economic recession. The S&P 500 has risen by more than 40% since the inversion. What is the reason?

Several structural factors make this cycle different from past ones:

First, the excess savings left over from the epidemic and the extremely strong labor market provide additional economic buffers. Corporate profits continue to grow, especially AI-related topics that have driven technology giants’ profits to significantly exceed expectations, supporting stock market valuations.

Second, the fiscal expansion is unprecedented in scale. Large-scale infrastructure bills and industrial policies (such as the chip bill and the inflation reduction bill) continue to inject demand, offsetting the effects of monetary tightening. This has formed a new pattern of "fiscal dominance", in which government spending and tax policies play a greater role in determining bond yields than central bank actions themselves.

Third, global negative yield bonds once reached US$17 trillion, distorting the dynamics of the traditional yield curve. Modern monetary policy tools such as quantitative easing and forward guidance have changed the traditional behavior pattern of the yield curve.

The 2Y-10Y interest rate spread returned to positive values ​​for the first time in September 2024, and by the end of 2025 the curve has completely normalized. The 10-year yield is about 4.16%, the 2-year interest rate is about 3.48%, and the positive interest rate spread is about 68 basis points.

Market behavior corresponding to different interest rate spread ranges

The specific correspondence between interest rate spreads and sector rotation

Changes in the yield curve directly affect the relative performance of different sectors:

Financial stocks are highly positively correlated with interest rate spreads. Banks make profits by "borrowing short and lending long". The steeper the curve, the higher the net interest margin (NIM). When interest rate spreads return to above +100bp from an inversion, bank stocks usually experience significant revaluation. On the contrary, financial stocks are the most direct victims during the inversion.

Technology and growth stocks are more sensitive to the absolute level of 10-year yields. Since the value of growth stocks mainly comes from cash flows in the distant future, an increase in the discount rate (approximately the 10-year yield) will directly compress valuations. The core driver of the plunge in growth stocks in 2022 is the surge in the 10-year yield from 1.5% to more than 4%.

Defensive sectors (utilities, consumer staples, medical) perform best during bullish periods. Historically, in a sustained bullish environment, gold and gold mining stocks have been the best-performing assets, while consumer staples have been the only sectors to record positive returns.

Energy and raw materials are mainly driven by inflation expectations and have a more indirect relationship with the shape of the curve. When a bear spike occurs (where the long end climbs in response to rising inflation expectations), materials stocks usually lead the charge.

Limitations of the Yield Curve

Although the yield curve is one of the best single leading indicators, it has several important limitations:

Time accuracy is extremely poor. Over the past fifty years, the interval between inversions and recessions has averaged about 12 months, but the actual range has been from 6 months to 3 years. After the 1965 inversion, the recession came as late as 1969, a gap of 48 months. As a trading signal, this uncertainty makes shorting the stock market based on inversions alone a statistically ineffective strategy.

CAIA's research points out that using the inversion of the yield curve as a strategy to short the stock market has had negative cumulative returns over the past 100 years, and the winning rate is close to random. That's because by the time everyone knows that an inversion may signal a recession, this information is already largely priced into stock prices.

Furthermore, the unconventional policies of modern central banks (quantitative easing, yield curve control, forward guidance) have altered the traditional dynamics of the curve. Negative interest rate policies in Japan and Europe have pushed global funds into U.S. government bonds, artificially lowering long-term interest rates, making the inversion likely to have a different meaning than in the past.

Practical operational framework

When integrating the yield curve into investment decisions, it should not be regarded as a single buying and selling signal, but as a background reference for asset allocation adjustments. Here is an actionable, phased framework:

When the curve is normal and the interest rate spread is above 100bp, the standard risk asset allocation can be maintained, and the proportion of stocks can be higher, with a preference for cyclical stocks and financial stocks.

When the curve begins to flatten (the interest rate spread drops below 50bp), start to improve the quality of the investment portfolio, increase the proportion of large-capitalization stocks, and reduce high leverage or low-quality targets. At the same time, small long positions in government bonds began to be established.

When the curve inverts, don't panic sell, but start gradually reducing your overall stock exposure and move some of your money into short-dated Treasuries or money market funds. At this time, the depth and duration of the inversion are more important than the inversion itself. You need to be more vigilant when the depth exceeds 50bp and lasts for more than three months.

When the curve begins to lift from the inversion (the bull steep appears), this is the stage where active defense is most needed. Increase the proportion of defensive sectors (utilities, consumer staples, medical care) and gold to a significant level, significantly reducing exposure to high beta and cyclical stocks.

When a recession is confirmed and the curve returns to its normal steepness, this is the time to start re-establishing risk positions. Historically, in 11 recessions since 1950, the S&P 500 fell an average of 20% during the recession, but rebounded by nearly 40% in the subsequent 18 months.

Auxiliary indicators used with

The yield curve should not be used alone. Cross-validation with the following indicators can significantly improve judgment accuracy:

Focus on sorting out

An inverted yield curve is an excellent early warning signal for a recession, but a poor market timing tool. After an inversion, the stock market often continues to rise for several months or even more than a year. The price of leaving the market prematurely may be missing out on 20% to 30% of the gains. The moment when you really need to be highly vigilant is not when an inversion occurs, but when the inversion is lifted in a bullish manner. This is the point when recession and market decline are most likely to approach. In practice, the yield curve should be regarded as a background framework for adjusting the offensive and defensive ratio of the investment portfolio, rather than a single entry and exit signal, and should be cross-verified with credit spreads, economic leading indicators and the policy direction of the Federal Reserve to maximize its predictive value.

Comparison of cross-border yield curve spreads

Cross-country yield curve spread comparisons and geographical market forecasts can be used, but the effectiveness varies by country, market structure and comparison method. Cross-country yield curve comparison is not just copying the same set of US logic to other countries, but an analysis framework covering three levels: "the predictive power of each country's own curve", "the difference in interest rates between countries driving capital flows" and "the spillover effect of the US curve on the world". The following is expanded layer by layer.

The first level: the predictive power of each country’s yield curve on its own market

Research by the Federal Reserve Bank of New York (Estrella and Mishkin, 1997) and cross-country empirical evidence by Bernard and Gerlach (1998) both confirm that the predictive relationship of the yield curve not only exists in the United States, but is also statistically significant in Germany, Canada, and the United Kingdom. The European Central Bank (ECB) working paper further extended the study to emerging markets and found that the yield curves of Malaysia, Mexico, the Philippines, Poland and South Africa can also effectively predict economic growth.

However, the predictive power of curves across countries is not equal. The differences come from several structural factors:

Core conclusion: The predictive power of a country's yield curve on its own economy and market is highly positively correlated with the independence of the country's central bank, the depth and liquidity of the bond market, and the degree of interest rate marketization. The curves of the United States and Germany are the most reliable; Japan is severely distorted by its long-term YCC policy; the emerging market curve is valid in some countries, but it needs to be interpreted together with sovereign credit spreads.

Level 2: How cross-border interest rate differences drive capital flows and market performance

This is the most practical part of cross-country comparisons. When the yield curves of different countries are at different cycle stages, the difference in interest rate spreads will drive the reallocation of global funds, thereby affecting the performance of the stock and foreign exchange markets in various regions.

Three transmission paths of cross-border interest rate differences

The first path is "interest rate differences guide the flow of funds." The nature of international funds chasing returns makes markets with higher interest rates attract capital inflows. BIS (Bank for International Settlements) 2024 research confirmed that the rise in the U.S. 10-year Treasury bond yield will have a significant negative impact on foreign portfolio investment (FPI) in emerging markets, because when the risk-free long-term returns provided by U.S. bonds rise, investors will move their portfolios back to U.S. Treasury bonds from emerging markets. Conversely, when U.S. interest rates cut and interest rate spreads narrow, funds tend to flow to emerging markets with higher yields.

The second path is that "the difference in curve shape reflects the dislocation of the economic cycle." When the U.S. curve has inverted but the European curve is still normally steep, it means that the European economic cycle lags behind that of the U.S., which often indicates that European stocks may be relatively resilient in the short term; conversely, when the U.S. curve is the first to return to normal from inversion and Europe has only begun to invert, U.S. stocks may be the first to bottom out.

The third path is the "exchange rate mechanism." Cross-border interest rate differences directly affect the direction and scale of arbitrage trade (Carry Trade). Japan's long-term ultra-low interest rates have made the yen a financing currency for global carry trades. The expansion or narrowing of the interest rate gap between the United States and Japan directly affects the yen exchange rate, which in turn affects the profits of export-oriented Japanese companies and the performance of Japanese stocks. Data from MacroMicro shows that the 10-year interest rate spread between the United States and Japan is highly positively correlated with the exchange rate of the U.S. dollar against the yen. While the depreciation of the yen is usually good for Japanese stocks (due to increased export competitiveness), the rapid appreciation of the yen is bad for Japanese stocks.

Key cross-country spread pairs and their forecast markets

The third layer: the spillover effect of the U.S. curve on the world

The special status of the U.S. yield curve is that it not only predicts the U.S. economy, but is also the core anchor point of global financial conditions (Global Financial Conditions). This stems from several structural factors:

The U.S. dollar serves as the global reserve currency, making U.S. Treasury yields the benchmark for global asset pricing. Whether it is the interest rate spread of emerging market sovereign bonds, the financing costs of global companies, or the allocation of foreign exchange reserves by central banks, the U.S. Treasury yield rate is the starting point for reference.

ECB research has found that the forecast information contained in many emerging market yield curves is actually partly derived from the US or euro zone yield curves. In other words, when researchers remove the impact of the U.S. curve from the emerging market curve, the predictive power of the remaining purely domestic factors sometimes decreases. But on the other hand, even if the U.S. factor is deducted, some emerging market curves still retain independent forecast information, and these "purely domestic" curve changes still have additional explanatory power for the country's economy and market.

BIS further noted in its 2024 report that the strength of the U.S. dollar itself has become a more important driver of financial flows than traditional interest rate differentials. When the U.S. dollar strengthens, global investors' risk appetite declines, and funds outflow from emerging market local currency bonds and stocks simultaneously; when the U.S. dollar weakens, the reverse trend occurs. This means that simply comparing yield spreads is not enough; the trend in the U.S. dollar index must also be taken into consideration.

Practical Application: An Operational Framework for Cross-Country Curve Comparison

Step 1: Confirm the cycle stage of each country’s curve

Step 2: Compare the shape and direction changes of the curves in various countries

Plot the 2Y-10Y interest rate spreads of various countries on the same chart and observe the following key patterns:

Synchronicity judgment: If the curves of all major countries flatten or invert simultaneously, it means that the risk of global recession has increased. At this time, risk asset exposure should be reduced across the board, regardless of region.

Differentiation judgment: If the curves of various countries are at different stages (for example, country A has been inverted and country B is still steep), funds will flow from the market in the latter part of the cycle to the market in the early part of the cycle. You should overweight national markets where the curve is steepening, and underweight markets where the curve is flattening or inverting.

Leading/Lagging Judgment: Historically, the United States has tended to lead other developed countries in curve changes by three to six months. If the U.S. curve is the first to uninvert and return to steepness, other countries will usually follow within half a year. At this time, lagging markets that have not yet reflected this trend can be deployed in advance.

Step 3: Make asset allocation based on interest rate differentials and U.S. dollar trends

Stylized cross-border curve monitoring

import yfinance as yf
import pandas as pd
import numpy as np
from fredapi import Fred

fred = Fred(api_key='YOUR_FRED_API_KEY')

# ==========================================
# 1. The slope of each country’s yield curve (2Y-10Y interest rate spread)
# ==========================================
def get_global_yield_spreads():
    """Obtain 2Y-10Y spreads of major countries"""

    # USA: Obtained directly from FRED
    us_spread = fred.get_series('T10Y2Y').dropna()

    # Germany, Japan, and the United Kingdom: calculated through the yield rate of each period
    # International yield serial code provided by FRED
    series_map = {
        'Germany': {'10y': 'IRLTLT01DEM156N', '2y': 'discontinued'},
        'U.K': {'10y': 'IRLTLT01GBM156N'},
        'Japan': {'10y': 'IRLTLT01JPM156N'},
    }

    # Alternative: Obtain indirectly using Investing.com crawler or yfinance
    # The following uses yfinance to obtain the 10Y government bond ETF yield rate of each country as an approximate value.
    proxies = {
        'USA 10Y': '^TNX',    # CBOE 10-Year Treasury Yield
        'America 2Y': '^IRX',     # 13-week T-Bill (short-end approximation)
    }

    results = {'USA': us_spread.iloc[-1]}
    print(f"US 2Y-10Y Spread:{us_spread.iloc[-1]:.3f}%")
    return results, us_spread

# ==========================================
# 2. Cross-country 10-year interest rate spread calculation (using FRED international data)
# ==========================================
def get_cross_country_10y_spread():
    """Calculate the 10Y yield difference between the United States and other major countries"""
    us_10y = fred.get_series('DGS10').dropna()

    # OECD long-term interest rates (monthly frequency, available from FRED)
    countries = {
        'Germany': 'IRLTLT01DEM156N',
        'Japan': 'IRLTLT01JPM156N',
        'U.K': 'IRLTLT01GBM156N',
        'Canada': 'IRLTLT01CAM156N',
        'Australia': 'IRLTLT01AUM156N',
    }

    results = {}
    us_monthly = us_10y.resample('M').last()

    for name, series_id in countries.items():
        try:
            foreign_10y = fred.get_series(series_id).dropna()
            # Align dates to calculate spreads
            combined = pd.DataFrame({
                'US': us_monthly,
                'Foreign': foreign_10y
            }).dropna()
            combined['spread'] = combined['US'] - combined['Foreign']
            latest = combined['spread'].iloc[-1]
            avg_3y = combined['spread'].tail(36).mean()
            results[name] = {
                'US vs country spread': round(latest, 2),
                'Three-year average': round(avg_3y, 2),
                'Off course': 'U.S. spreads above average' if latest > avg_3y
                              else 'Interest spreads are narrowing',
                'series': combined['spread']
            }
        except Exception as e:
            print(f"{name}Data retrieval failed:{e}")

    return pd.DataFrame(results).T

# ==========================================
# 3. Cross-national curve shape comparison dashboard
# ==========================================
def global_curve_dashboard():
    """
    Comprehensive judgment of the curve stages of each major economy
    and infer capital flow and allocation suggestions.
    """
    # Get the U.S. yield rate for each period
    us_maturities = {
        '3M': 'DGS3MO', '2Y': 'DGS2',
        '5Y': 'DGS5', '10Y': 'DGS10', '30Y': 'DGS30'
    }
    us_yields = {}
    for label, sid in us_maturities.items():
        s = fred.get_series(sid).dropna()
        us_yields[label] = s.iloc[-1]

    us_2s10s = us_yields['10Y'] - us_yields['2Y']
    us_3m10y = us_yields['10Y'] - us_yields['3M']

    # Determine the shape of the American curve
    if us_2s10s < -0.2:
        us_phase = 'Upside down (late boom/recession warning)'
    elif us_2s10s < 0.2:
        us_phase = 'Nearly flat (transition period)'
    elif us_2s10s < 1.0:
        us_phase = 'Mildly positive slope (mid to late expansion)'
    else:
        us_phase = 'Highly steep (early recovery)'

    report = f"""
=== Cross-border yield curve monitoring ===

【United States】
  2Y-10Y spread: {us_2s10s:.3f}%
  3M-10Y spread: {us_3m10y:.3f}%
  Curve phase judgment: {us_phase}
  3M: {us_yields['3M']:.2f}% 2Y: {us_yields['2Y']:.2f}%
  5Y: {us_yields['5Y']:.2f}% 10Y: {us_yields['10Y']:.2f}%
  30Y: {us_yields['30Y']:.2f}%
"""
    print(report)

    # Cross-border spreads
    cross = get_cross_country_10y_spread()
    print("[Cross-border 10Y Spreads (United States - Various Countries)]")
    print(cross[['US vs country spread', 'Three-year average', 'Off course']])

    return {'us_phase': us_phase, 'us_yields': us_yields, 'cross_spreads': cross}

# ==========================================
# 4. Backtesting of interest rate spreads and relative stock market performance
# ==========================================
def spread_vs_equity_backtest(
    spread_series,
    equity_a_ticker, equity_b_ticker,
    label_a='Market A', label_b='Market B'
):
    """
    Backtesting the historical correlation between cross-country spreads and the relative performance of two stock markets
    spread_series: 两国10Y利差的时间序列（A国 - B国）
    equity_a/b: corresponding stock market ETF or index code
    """
    eq_a = yf.download(equity_a_ticker, period='5y')['Close']
    eq_b = yf.download(equity_b_ticker, period='5y')['Close']

    # Calculate the relative strength ratio of the stock market
    rel_strength = (eq_a / eq_b).dropna()
    rel_strength = rel_strength.resample('M').last()

    # Align spread series
    spread_m = spread_series.resample('M').last()

    combined = pd.DataFrame({
        'Spread': spread_m,
        'relative strength': rel_strength
    }).dropna()

    # Calculate rolling correlation coefficient
    rolling_corr = combined['Spread'].rolling(12).corr(combined['relative strength'])
    overall_corr = combined['Spread'].corr(combined['relative strength'])

    print(f"{label_a} vs {label_b}")
    print(f" overall correlation coefficient:{overall_corr:.3f}")
    print(f" rolling correlation in the past 12 months:{rolling_corr.iloc[-1]:.3f}")

    return combined, rolling_corr

#Usage example:
# U.S.-German spread vs relative performance of US stocks/European stocks
# spread_vs_equity_backtest(
#     spread_series=us_de_spread,
# equity_a_ticker='SPY', # US stocks
# equity_b_ticker='VGK', # European stocks
# label_a='US stocks', label_b='European stocks'
# )

# ==========================================
# 5. Automatic detection of cross-country curve cycle differences
# ==========================================
def detect_cycle_divergence(spreads_dict):
    """
    Detect whether there is cyclical divergence in the curves of various countries
    spreads_dict: {'United States': series, 'Germany': series, ...}
    Backhaul: Country cycle stage + differentiation degree assessment
    """
    phases = {}
    for country, series in spreads_dict.items():
        s = series.dropna()
        current = s.iloc[-1]
        # Calculate the direction of change in 3 months
        change_3m = current - s.iloc[-63] if len(s) > 63 else 0

        if current < -0.2:
            phase = 'upside down'
        elif current < 0.2:
            phase = 'flat'
        elif current < 1.0:
            phase = 'Mild positive slope'
        else:
            phase = 'highly steep'

        direction = 'Steepening' if change_3m > 0.1 else 'flattening' if change_3m < -0.1 else 'flat'
        phases[country] = {
            'Spread': round(current, 3),
            'stage': phase,
            'direction': direction
        }

    df = pd.DataFrame(phases).T
    # Calculate the degree of differentiation (whether the stages are consistent across countries)
    unique_phases = df['stage'].nunique()
    divergence = 'Highly differentiated' if unique_phases >= 3 else 'Moderately differentiated' if unique_phases == 2 else 'synchronous'
    print(f"Global curve differentiation degree:{divergence}")
    print(df)
    return df, divergence

Limitations and precautions in comparing curves across countries

First, the bond market structures of different countries vary greatly, and direct comparison of the absolute values ​​of interest rate spreads may be misleading. For example, Japan's 10-year yield rate of 2.25% is extremely high in Japan's historical context, but it is only a normal level in the United States. Therefore, Z-Score standardization should be used for cross-country comparisons, and the interest rate spreads of various countries should be converted into multiples of standard deviations relative to their own historical averages before comparison.

Second, the central bank’s unconventional policies have seriously distorted the curve in some countries. The ECB's quantitative easing once pushed the German Bund yield rate into negative values, and the BOJ's YCC directly controlled the 10-year interest rate. During the existence of these policies, the market information content of the yield curve dropped significantly, and backtesting using data from these periods may lead to erroneous conclusions.

Third, the yield curve of emerging markets requires additional consideration of sovereign credit risk. 10-year yields in emerging countries include a large credit risk premium, which makes changes in the slope of the curve likely to reflect changes in sovereign risk rather than pure economic cycle expectations. When combined with the JP Morgan EMBI spread, the credit risk component can be separated out.

Fourth, exchange rate factors are crucial in cross-country comparisons. Even if a country's market performs well in its local currency, if that country's currency depreciates significantly against the U.S. dollar, real returns in U.S. dollars may be negative. Therefore, when making cross-border allocations, one must also evaluate the direction of exchange rate changes driven by interest rate differentials, or consider whether to conduct exchange rate hedging.

Fifth, the global influence of the U.S. yield curve means that the U.S. curve is a benchmark that cannot be ignored when making any cross-country comparisons. Even if the analysis is about the relative allocation between Europe and Asia, the direction of the U.S. curve will still affect the results indirectly through the U.S. dollar, capital flows and global risk sentiment. The first step in any cross-country curve comparison framework is always to identify where the U.S. curve lies.

Forex

US dollar to Taiwan dollar real-time exchange rate

. Live Forex - USDTD - Anue Juheng

Provides real-time exchange rate and market dynamics analysis of the US dollar against the Taiwan dollar.

Go to website

. Investing.com

Provides the latest exchange rate, trend charts and news information of the US dollar against the Taiwan dollar, suitable for market analysis.

Go to website

. Currency.Wiki

Provides instant US dollar to Taiwan dollar exchange rates and quick conversion tools.

Go to website

. Coinbase

Provides real-time exchange rates of US dollars to Taiwan dollars, suitable for digital currency related inquiries.

Coinbase

. Finance M Squared

Provides real-time exchange rate inquiry and trend analysis tools for the US dollar against the Taiwan dollar.

US dollar exchange rate - interest rate hikes and cuts - US stocks

Note: Exchange rates may fluctuate with market fluctuations, it is recommended to consult multiple sources and consult with professionals.

Factors affecting Taiwan dollar exchange rate

. International foreign exchange market supply and demand

The exchange rate of the Taiwan dollar is affected by market supply and demand. When foreign capital flows into Taiwan, demand for the Taiwan dollar increases and the exchange rate rises; conversely, when capital flows out, the exchange rate falls.

. Economic conditions of Taiwan and its major trading partners

Taiwan's export performance and economic growth rate are closely related to the economic conditions of major trading partners such as the United States and China, which affect the strength of the Taiwan dollar.

. U.S. Federal Reserve (Fed) Monetary Policy

U.S. interest rate hikes will cause capital outflows from emerging markets, including Taiwan, and depreciate the Taiwan dollar; conversely, interest rate cuts may cause capital to flow back and push up the Taiwan dollar.

. Intervention by the Central Bank of Taiwan

Taiwan's central bank may affect the Taiwan dollar's exchange rate through foreign exchange market operations, such as buying or selling Taiwan dollars to stabilize the exchange rate.

. Foreign investment and Taiwan stock performance

When foreign capital buys Taiwan stocks, it will drive up demand for the Taiwan dollar and make the Taiwan dollar appreciate; conversely, the withdrawal of foreign capital may cause the Taiwan dollar to depreciate. However, there will be discrepancies between the foreign capital inflows and outflows disclosed by the stock market and the actual inflows and outflows.

. Politics and International Situation

Factors such as cross-strait relations, geopolitical conflicts, and international trade wars may affect market confidence and cause fluctuations in the Taiwan dollar.

.Inflation and price changes

Rising inflation may lead to a decrease in purchasing power, which may in turn affect exchange rate movements.

dollar index

definition

The US Dollar Index (DXY) is an indicator that measures changes in the exchange rate of the US dollar against a basket of major currencies, reflecting the overall strength of the US dollar.

Calculation method

The U.S. Dollar Index is calculated based on the weighted average exchange rate of a basket of currencies, currently including six major currencies:

• Euro (EUR) – 57.6%
• Japanese Yen (JPY) – 13.6%
• British Pound Sterling (GBP) – 11.9%
• Canadian Dollar (CAD) – 9.1%
• Swedish Krona (SEK) – 4.2%
• Swiss Franc (CHF) – 3.6%

Influencing factors

• US economic data such as GDP, employment and inflation rates
• The Federal Reserve’s (Fed) monetary policies, such as interest rate changes and quantitative easing
• Global economic conditions and market hedging needs
• International trade and capital flows

use

• Measuring the strength of the U.S. dollar in international markets
• As a reference for foreign exchange trading and investment decisions
• Affect commodity prices, such as gold and crude oil

Historical Trends of the U.S. Dollar Index

The U.S. dollar index has experienced many fluctuations since 1973, reaching a peak of about 160 in 1985, and fell to about 70 during the financial crisis in 2008.

current trends

The U.S. dollar index is affected by global economic changes and the Federal Reserve's policies, so you need to pay attention to market dynamics and related data.

Factors affecting the Japanese yen exchange rate

1. The yen is a safe-haven currency

The yen is considered a safe-haven currency. When global financial markets are turbulent or an economic crisis occurs, investors may turn to the yen, causing the yen to appreciate. But at this time, Japanese stocks were still falling.

2. The impact of long-term zero interest rate on the Japanese yen

The Bank of Japan has maintained extremely low or even negative interest rate policies for a long time, making the Japanese yen a low-yielding currency, affecting its international capital flows and exchange rate changes.

3. International foreign exchange market supply and demand

The exchange rate of the Japanese yen is affected by market supply and demand. When foreign capital flows into Japan, the demand for the Japanese yen increases and the exchange rate rises; conversely, when capital flows out, the exchange rate falls.

4. Economic conditions between Japan and its major trading partners

Japan's export performance and economic growth rate are closely related to the economic conditions of major trading partners such as the United States and China, which affect the strength of the yen.

5. Bank of Japan’s monetary policy

The Bank of Japan's interest rate decisions and monetary easing policies have an important impact on the yen exchange rate. For example, low interest rates may cause the yen to depreciate.

6. U.S. Federal Reserve (Fed) monetary policy

Raising interest rates in the United States will cause capital to flow out of Japan and depreciate the yen; conversely, lowering interest rates may cause capital to flow back and push up the yen.

7. Politics and international situation

Factors such as geopolitical risks, international trade wars, and financial market turmoil may affect market confidence and lead to fluctuations in the yen.

8. Inflation and price changes

Rising inflation may affect the purchasing power of the yen, thereby affecting exchange rate movements.

precious metals

Precious metal financial management website

precious metal investment

Main types of precious metals

• Gold: The first choice for safe-haven assets, anti-inflation, and central bank reserves.
• Silver: It has both industrial and investment purposes and has high volatility.
• Platinum: Industrial and automotive catalysts have many applications and the market is small.
• Palladium: Mainly used for automobile exhaust gas treatment, the price is greatly affected by industrial demand.

Common investment methods

• physical precious metals: Such as gold bars, gold coins, and silver coins, storage and insurance costs need to be considered.
• ETF/ETN: Such as SPDR Gold Trust (GLD) and iShares Silver Trust (SLV), which have the advantages of high liquidity and low transaction threshold.
• futures contract: Leverage can be used, but the risk is high and professional operation is required.
• mining stocks: Companies that invest in precious metal mining, such as Newmont and Barrick Gold, are affected by both gold prices and corporate operations.
• Precious metal deposit account: Some banks or trading platforms provide gold and silver deposits in book form.

Investment advantages

• Hedging tool to combat market volatility and inflation.
• It is rare and has long-term value-preserving properties.
• It has low correlation with traditional assets such as stocks and bonds, which helps spread risks.

investment risk

• Prices are highly volatile, especially for silver and platinum group metals.
• No interest or dividend income, high opportunity cost.
• Physical precious metals face custody and liquidity risks.

Suitable for investor types

• Medium to long-term investors seeking diversification of asset allocation.
• Risk-averse investors concerned about inflation or geopolitical risks.
• Advanced investors who are familiar with physical assets or commodity futures.

futures

Futures investment

What are futures?

Futures are a standardized contract in which buyers and sellers agree to deliver an underlying asset, such as a commodity, financial index, currency, etc., at a specific price at a specific time in the future. Futures are derivative financial products with leverage and high-risk characteristics.

Main investment targets

• Commodity futures: Such as crude oil, gold, silver, coffee, agricultural products, etc.
• financial futures: Such as stock price index (such as Taiwan Index futures, S&P 500), bond futures.
• Forex futures: Such as EUR/USD and JPY/USD futures.
• Cryptocurrency Futures: Such as Bitcoin futures (only traded on some compliance platforms).

Features of futures

• Leverage: Large amounts of assets can be traded with only a small margin.
• two-way transaction: Can be long (bullish) or short (bearish), highly flexible.
• Good liquidity: Mainstream futures contracts are actively traded and easy to enter and exit the market.
• standardized contract: The exchange has unified specifications and is guaranteed by regulations.

Investment advantages

• Can quickly amplify rewards (and also amplify risks).
• Suitable for risk hedging (such as using agricultural product futures to avoid price fluctuations).
• Can be combined with other assets for asset allocation or hedging.

investment risk

• The leverage risk is high, and the position may be liquidated quickly if the market reverses.
• It is necessary to continue to pay attention to margin calls and forced liquidation.
• Prices fluctuate violently, requiring good risk control and discipline.

Common operating strategies

• Day Trade: Quick entry and exit, take advantage of the price difference.
• Swing Trade: Enter the market following the trend.
• Spread Trade: Buy and sell contracts of different months or underlying assets to earn the price difference.
• Hedging: Lock in risks and protect spot positions.

Suitable for investor types

• Those with high risk tolerance and rich trading experience.
• Investors with clear operating strategies and disciplines.
• Enterprises or farmers conduct hedging operations.

Crude oil investment

In the market environment of 2026, crude oil investment has evolved from a simple supply and demand competition to a tug-of-war between geopolitical premiums and energy transition pressures. Investors need to distinguish between instrument characteristics and holding periods to cope with high volatility. The following is an analysis of the main paths:

Analysis of market influencing factors

• Geopolitical risks:Changes in the situation in the Middle East in early 2026 directly pushed up the war premium, causing oil prices to diverge from fundamentals in the short term.
• Excess production expectations:The production capacity of American oil-producing countries (the United States, Brazil, and Canada) continues to expand, and the long-term oversupply pattern limits the upside space for oil prices.
• Currency and interest rates:The strength of the U.S. dollar exchange rate is highly negatively correlated with crude oil pricing, and the Federal Reserve's interest rate policy remains the key.

Classification and Characteristics of Investment Tools

Key points for investment operations in 2026

• Be wary of contango losses:When the futures far-month price is higher than the nearby month (Contango), the ETF tracking the futures will cause the net value to shrink because it sells cheaper and buys more expensive every month. This is the most common trap under the expectation of oversupply in 2026.
• Energy transition layout:Traditional oil companies have begun to shift capital expenditures to low-carbon technologies. Investors should give priority to energy giants that are undergoing successful transformation and have high cash flow stability.
• Stop loss mechanism:Crude oil is greatly driven by news and may fluctuate more than 5% in a single day. A clear exit point must be set before entering the market.

Agricultural products futures

In 2026, the agricultural product market will enter a highly differentiated "post-geographic conflict period." Although global supply chains are stabilizing, extreme climate and energy cost fluctuations remain price-dominant factors. When choosing a target, investors should make an in-depth comparison of the seasonality and demand side of each crop.

Comparison of characteristics of main agricultural products

Key difference analysis

• Cyclical differences:Soybeans and corn usually reach peak volatility in the northern hemisphere summer (June-August) due to "weather hype"; wheat is more susceptible to winter crop freezes (Winterkill) or breaking news about the Black Sea situation.
• Usage properties:Corn and soybeans have strong "energy attributes" (biofuels), and their prices have a certain positive correlation with crude oil trends; soft commodities (cocoa, sugar, coffee) are more "people's consumption" and are deeply affected by global inflation.
• Margin and Liquidity:Soybeans, corn, and wheat (the three soybean brothers) have excellent liquidity and are suitable for swing operations; soft commodity contracts have different multipliers, so you need to pay attention to the coverage of the available margin in your account.

Investment Considerations for 2026

• The Christ Child/Anti-Christ Child phenomenon:A shift in climate patterns is expected in 2026, which will directly change production expectations in South America (Brazil, Argentina) and have a decisive impact on soybean and corn prices.
• Rollover loss (Contango):Similar to crude oil, if you hold agricultural product futures for a long time, you need to pay attention to the price difference between the far-month contract and the near-month contract to avoid principal erosion due to frequent rollovers when the market goes sideways.
• ETF alternatives:If you don’t want to directly operate futures, you can consider the following:DBA (Agriculture ETF)To diversify the risk of a single crop, or in the Taiwan market00693U (Qijiekou Soybeans)Make variety-specific layouts.

trading strategy

CAPM capital asset pricing model

definition

CAPM (Capital Asset Pricing Model) is a financial model used to estimate the relationship between asset or investment return and risk. This model believes that the expected return rate of an asset is determined by the risk-free interest rate, the expected return rate of the market, and the risk (β value) of the asset relative to the market.

formula

The CAPM formula is as follows:
E(Ri) = Rf + βi × (E(Rm) - Rf)

in:
E(Ri): expected return on asset i
Rf: risk-free interest rate (such as government bond interest rate)
βi: β value of asset i, indicating its degree of risk relative to the market
E(Rm): the market’s expected rate of return

Model assumptions

• All investors are rational and seek to maximize returns.
• Market information is fully public and there are no transaction costs.
• Investors can borrow and borrow without limit at the risk-free rate.
• The return on assets follows the normal distribution.

use

• A measure of the reasonable rate of return for an individual stock or portfolio.
• Assess whether an asset is overvalued or undervalued.
• As the basis for company valuation and capital cost calculation (WACC).

Advantages and Disadvantages

advantage:

• Simple, easy to understand and operate.
• Widely used in asset pricing and corporate finance.

shortcoming:

• Relying on many ideal assumptions, there is a gap with the actual market.
• The calculation of β value is easily affected by historical data.
• Certain abnormal return phenomena (such as the small-cap effect) cannot be explained.

excess return alpha

definition

Alpha, also known as Jensen's Alpha, is a measure of the excess return obtained by a portfolio after adjusting for risk (usually through beta value). It reflects the active management performance of the investment manager. If Alpha is positive, it means that the investment has performed better than the return it deserves for its risk.

formula

α = Rp − [Rf + βp × (Rm − Rf)]

in:
α: Jensen's Alpha (Alpha)
Rp: Real rate of return on investment portfolio
Rf: risk-free rate
βp: Beta value of the portfolio
Rm: market rate of return

explain

• α > 0: The portfolio performs better than the reward for its risk.
• α = 0: Portfolio performance is consistent with the return it deserves for its risk.
• α < 0: The portfolio does not perform as well as it deserves for its risk.

use

• Evaluate the stock picking and timing skills of active fund managers.
• Measure whether asset returns are other than risk premiums.
• As an investment performance analysis tool.

Advantages and Disadvantages

advantage:

• Ability to recognize the true value of active investing.
• More risk-adjusted than pure return.

shortcoming:

• Highly dependent on CAPM model correctness.
• May be affected by market fluctuations or estimation parameter errors.

Quantitative trading

What is quantitative trading?

Quantitative trading is a trading method based on data analysis and mathematical models. It uses computer algorithms to automatically analyze market data and execute trading instructions to obtain stable investment returns. The core of quantitative trading is to use a large amount of historical data and real-time data to construct trading strategies to reduce the impact of subjective emotions on investment decisions.

The main features of quantitative trading

• Data-driven decisions:Quantitative trading relies on big data analysis to find patterns and trends in the data and formulate trading strategies based on the models.
• High frequency and automation:Quantitative trading is usually carried out through automated computer programs, which can execute transactions at a high frequency and quickly seize market fluctuation opportunities.
• Risk control:Through a strict risk management system and a diversified investment portfolio, quantitative trading can effectively control risks during the execution process.

Common strategies for quantitative trading

• Arbitrage strategy:Take advantage of market opportunities with inconsistent prices by buying low-priced assets and selling high-priced assets to profit from the price difference.
• Trend following strategies:Make trading decisions based on the trend of asset prices and follow the upward or downward direction of prices.
• Mean reversion strategy:Buying or selling occurs when prices deviate from the mean, assuming the concept that asset prices will eventually return to the mean.
• High frequency trading strategies:Capture small market fluctuations by quickly executing a large number of small transactions and accumulate profits.

Advantages of Quantitative Trading

The advantages of quantitative trading include:

1. Eliminate artificial emotional interference:Since quantitative trading relies on data and models, it avoids the influence of human emotions during the trading process and reduces the risk of irrational decision-making.
2. Efficient trade execution:Automated trading systems can quickly execute multiple transactions and achieve efficient market participation.
3. Optimize risk management:Quantitative models can quickly analyze market risks, design reasonable risk control strategies, and reduce potential losses.

Quantitative Trading Challenges

Although quantitative trading has many advantages, it also faces some challenges:

• Model risk:Trading models may become invalid due to changes in the market environment, which poses risks to quantitative trading that relies on models.
• High technical threshold:Quantitative trading requires data analysis, programming, mathematics and other skills, and practitioners need to have professional knowledge.
• Strong data dependence:Quantitative trading highly relies on the accuracy and completeness of data, and data errors may lead to trading errors.

Application areas of quantitative trading

Quantitative trading is widely used in financial markets such as stocks, foreign exchange, futures, and cryptocurrencies. Whether it is individual investors or financial institutions, the application of quantitative trading has gradually become a part that cannot be ignored in the capital market, providing diversified investment options.

Quantitative trading platform

What is a quantitative trading platform?

A quantitative trading platform is a trading tool designed to provide investors with data analysis, strategy design and automated execution. These platforms use data and mathematical models to develop trading strategies and automatically execute trading instructions, allowing investors to obtain an efficient trading experience in markets such as stocks, futures, foreign exchange, and cryptocurrencies.

Core functions of quantitative trading platform

• Data analysis:Provides historical data and real-time market data to help investors analyze market trends and find potential trading opportunities.
• Strategy development and backtesting:Allows investors to design quantitative trading strategies and test the effectiveness of these strategies on historical data to predict their potential performance.
• Automated trading:The platform can automatically execute transactions according to set strategies, helping investors respond quickly to market fluctuations without manual operations.
• Risk management tools:Provide risk control functions, such as stop-loss and take-profit settings, to reduce risks caused by market fluctuations.

Comparison of mainstream quantitative trading platforms

• MetaTrader 4/5 (MT4/MT5)：Mainly targeting the foreign exchange and Contract for Difference (CFD) markets, it provides a wealth of technical indicators and automated trading functions, and has huge community support.
• QuantConnect：An open source quantitative trading platform that supports stocks, futures, foreign exchange and cryptocurrency markets. It uses Python and C# for strategy development and is suitable for investors who need to trade across markets.
• TradeStation：An advanced platform for professional traders, offering complete strategy testing and backtesting tools for stocks, options and futures trading.
• Interactive Brokers (IBKR) API：Suitable for advanced investors, it supports multi-asset trading, and provides comprehensive global market data and customized strategy execution functions.
• Alpaca：A quantitative trading platform focusing on the stock market, providing Python API, suitable for investors with a programming background, and supporting trading services without trading commissions.
• XQ quantification building blocks:The modular design makes it suitable for beginners and enables strategies to be assembled in a simple way, making it suitable for investors who want to get started quickly.
• FinLab：Provides a variety of tools and resources to assist users in the development of quantitative analysis, data science and automated trading.

Advantages of quantitative trading platform

The advantage of a quantitative trading platform lies in its automation, accuracy and data-driven decision-making capabilities:

1. Reduce emotional disturbance:Use data and algorithms to make trading decisions, avoid the influence of human emotions, and improve the consistency of transactions.
2. Quickly respond to market changes:Automated trading allows investors to respond quickly to market changes and capture opportunities.
3. Precise risk control:Built-in risk management tools can help investors flexibly adjust risk preferences according to market conditions and reduce potential losses.

Challenges of Quantitative Trading Platforms

Although quantitative trading platforms have many advantages, they also face some challenges in using them:

• High technical requirements:Many quantitative platforms require programming skills, and the learning threshold is high for investors without technical background.
• Model risk:Strategies that rely on mathematical models may be ineffective when the market environment changes dramatically, so strategies need to be updated and adjusted regularly.
• Data accuracy:Quantitative trading highly relies on the authenticity and completeness of market data, and data errors may lead to the failure of trading strategies.

Future development trends

With the rapid development of financial technology, future quantitative trading platforms will be more intelligent and integrate artificial intelligence and machine learning technologies to improve the prediction and adaptability of strategies. In addition, cross-market and multi-asset support will further enhance the application scope of the quantitative platform and bring more opportunities to investors.

MetaTrader

Introduction to MetaTrader

MetaTrader (MT for short) is a foreign exchange and financial trading platform developed by the Russian company MetaQuotes Software. The main versions are MT4 (MetaTrader 4) and MT5 (MetaTrader 5). It is widely used in trading in foreign exchange, index, stock, commodity and cryptocurrency markets.

MetaTrader 4 vs MetaTrader 5

• MT4：Released in 2005, it is specially designed for foreign exchange trading and has a large number of custom indicators and EA (automated trading system).
• MT5：Released in 2010, it has more powerful functions, supports more financial products, more technical indicators and time periods, and has built-in economic calendar and market depth functions.

Main functions of the platform

• Technical analysis tools:More than 30 technical indicators, chart objects and multi-time frame analysis.
• Automated trading:Use MQL4/MQL5 to write automatic trading strategies (Expert Advisor, EA).
• Charts and multi-chart management:You can open multiple product charts at the same time and customize the visual layout.
• Simulated trading:Provides historical data backtesting function to test the performance of trading strategies.

MetaTrader usage process

1. Download the MT4/MT5 platform from the MetaQuotes official website or broker website.
2. Open a demo account or a real account and log in to start trading.
3. You can use built-in or custom indicators to assist in technical analysis.
4. Execute automatic trading through EA, or place orders manually.

Advantages and Disadvantages

• advantage:
  • Free to use, lightweight and fast
  • Support automated trading and programmed strategies
  • Has a huge community and resource sharing (indicators, EA, market)
• shortcoming:
  • The user interface is older and the learning curve is slightly higher.
  • Security relies on brokers, so you need to choose a reputable platform provider
  • MT4 cannot trade some assets such as stocks. Although MT5 has many functions, it has fewer users.

Common uses

• Foreign exchange short-term trading and long-term positions
• Development and deployment of automated high-frequency trading systems
• Combine technical indicators for multi-strategy testing
• Trader education and simulation practice platform

Conclusion

MetaTrader is currently one of the most popular trading platforms in the world. Both beginners and professional traders can use MT4 or MT5 for efficient trading and strategy deployment according to their own needs.

TWINDEX Index in MetaTrader 5

Introduction to TWINDEX Index

The TWINDEX index, Taiwan RIC Index, is an index that measures the performance of Taiwan's stock market. The index can be traded as a Contract for Difference (CFD) on certain trading platforms, providing investors with the opportunity to participate in the Taiwan market.

Trade TWINDEX on the MT5 platform

Some brokers, such as Moneta Markets and Bybit, already offer CFD trading on the TWINDEX index on their MetaTrader 5 (MT5) platform. This enables traders to buy and sell the index directly on the MT5 platform, enjoying the advantages of leveraged trading.

Main features of trading TWINDEX

• Leverage ratio:Brokers often offer leverage of up to 1:50, which means investors can control larger positions with less capital.
• Contract specifications:For example, on the Bybit platform, the contract size of TWINDEX is 50, the minimum trading volume is 0.1 lots, and the maximum trading volume is 500 lots.
• Trading hours:Trading hours may vary by broker, it is recommended to check the trading hours of your chosen platform for accurate information.

How to trade TWINDEX in MT5

1. Choose a broker that supports TWINDEX:Make sure the chosen MT5 broker offers CFD trading on the TWINDEX Index.
2. Open and fund a trading account:Open an MT5 trading account with your chosen broker and deposit sufficient funds.
3. Download and install the MT5 platform:Download and install the MT5 trading platform from the broker’s official website.
4. Log in to MT5 and add TWINDEX commodities:Log in to MT5 using your account information, then find and add the TWINDEX index in the market quote window.
5. Make a transaction:Analyze the market, set a trading strategy, and then execute buy or sell orders.

Things to note

• Market Volatility:Taiwan's stock market may be affected by domestic and foreign economic and political factors, causing index fluctuations.
• Leverage risk:Although leverage can magnify gains, it can also increase potential losses and should be used with caution.
• Transaction costs:Be aware of trading costs such as spreads, fees and overnight interest, which may vary from broker to broker.

Summarize

By trading CFDs on the TWINDEX index on the MT5 platform, investors can easily participate in the Taiwan stock market. However, it is recommended to fully understand relevant market information, trading conditions and risks before trading to develop a trading strategy that suits you.

Introduction to FinLab

FinLab is a financial technology company that provides a variety of tools and resources to assist users in the development of quantitative analysis, data science, and automated trading.

FinLab core features

• Quantitative analysis tools: Supports multiple quantitative analysis methods such as time series analysis and factor stock selection.
• Data processing: Process financial data such as stocks and cryptocurrencies, and assist with data cleaning and modeling.
• Automated trading system: Allow developers to build automatic trading robots and conduct strategy backtesting and optimization.
• educational resources: Provides a wealth of information to help learn quantitative investment, data science and program trading.

FinLab Applications

FinLab is mainly used in the fields of financial data analysis, strategy backtesting and automated trading. Developers can build quantitative investment models through FinLab's API and apply them to a variety of financial assets.

Common application examples

• Factor stock selection model: Select stocks based on the multi-factor model and screen out potential investment targets.
• Strategy backtest: Simulate the performance of different trading strategies and verify the effectiveness of the strategies based on historical data.
• Automated trading robot: Build a fully automatic trading robot to automatically execute buying and selling operations according to the set strategy.

How to use FinLab

1. Visit FinLab official website and register an account.
2. Obtain an API key and configure the development environment to connect to the FinLab API.
3. Develop and backtest trading strategies using a variety of data and tools provided by FinLab.

For more information, please refer to FinLab official website:FinLab.tw

Regular fixed amount investment

definition

DCA (Dollar-Cost Averaging) is an investment strategy that invests funds in the market in batches. Investors buy an asset for a fixed amount at fixed intervals (such as weekly, monthly), regardless of the market price, and the long-term average purchase cost.

How it works

Since you invest a fixed amount each time, you can buy more units when prices are lower and fewer units when prices are higher. Such a strategy can spread the cost of entry and help reduce the price risk that may be encountered when making a one-time investment.

advantage

• Especially suitable for those with regular fixed income, such as using part of the monthly salary to make regular fixed investments
• Reduce the risk of incorrect entry timing
• Suitable for volatile markets and long-term investments
• Helps establish investment discipline and habits
• Emotional interference is small, and there is no need to frequently judge buying points.

shortcoming

• Unable to catch the market low, the return may be lower than a one-time purchase
• May lag behind a single investment in a sustained uptrend
• Less favorable for short-term profits

Applicable assets

• ETFs (such as VOO, QQQ, 0050)
• Stocks (such as long-term bullish large-cap stocks)
• Cryptocurrencies (e.g. BTC, ETH)
• Funds and Retirement Accounts

example

If you invest NT$10,000 every month to buy Taiwan stock ETF 0050, no matter whether the price is NT$120 or NT$90, you will invest the same amount. After long-term accumulation, the overall cost will tend to average and the risk of a single purchase error will be reduced.

Active DCA (strategic periodic quota)

Active DCA is an advanced version of traditional DCA that combines market sentiment, technical indicators or price fluctuations to adjust the amount and timing of investment. For example, when there is a significant correction in asset prices, increase the amount of investment; when the price is high, reduce investment or suspend purchases.

Active DCA features

• Improve capital efficiency and make good use of low points
• Need to be paired with technical analysis (such as RSI, MACD) or interval strategy
• Suitable for investors with certain market experience
• Robot execution that can be combined with "conditional automation" (such as using a grid/strategy platform)
• If proactive DCA makes a wrong judgment, it may add code at the wrong time.

Conclusion

DCA is a simple, practical and suitable strategy for most investors. It is an important method for a stable layout, especially for long-term investors who cannot predict market trends or do not have time to operate frequently.

grid trading

Overview

Grid trading is an automated trading strategy that automatically buys low and sells high during market fluctuations through a preset price range. It is suitable for volatile markets.

How it works

• Set price range:Determine the high and low prices of the trading range.
• Meshing:Set multiple price points within a range, with equal intervals between each point.
• Automatically execute transactions:Buy when the price falls to a certain grid point and sell when it rises to a certain point.

Advantages

• No need for frequent monitoring:Automatically execute transactions and reduce manual operation pressure.
• Applicable to volatile market conditions:Take advantage of market fluctuations to achieve sustained profits.
• Spread the risk:Reduce the risk of a single transaction by buying and selling in batches.

risk

• Unilateral market risks:If the price breaks out of the grid range, it may result in losses.
• Fund occupation:Holding assets for a long time affects capital liquidity.
• Handling fee cost:Frequent transactions may increase transaction fee costs.

Applicable market

• Cryptocurrency:Such as BTC, ETH, etc., suitable for highly volatile markets.
• Forex trading:For example, EUR/USD is suitable for intraday fluctuations in the market.
• Stock market:It can be applied when some individual stocks or ETFs fluctuate within a specific range.

in conclusion

Grid trading is a strategy suitable for volatile markets that can automate buying and selling operations, but parameters still need to be set carefully to reduce risks and increase profit opportunities.

Grid Trading Research Paper

. Research on the optimization of grid trading parameters using genetic algorithms—taking the Taiwan stock market as an example

Author: Lu Yangtong

Institution: Department of Information and Financial Management, National Taipei University of Technology

Abstract: This study uses genetic algorithms to optimize the grid trading strategy parameters in the Taiwan stock market, aiming to improve trading performance.

URL:https://ntut.elsevierpure.com/zh/studentTheses/Research on using genetic algorithm to optimize grid trading parameters - taking Taiwan stock market as an example

. Implementation and research of counter-trend grid strategy in foreign exchange automatic trading

Author: Kong Xiangyi

Institution: Tamkang University, Department of Information Management, Master's Program

Abstract: This study proposes a counter-trend grid trading strategy, combined with the Martingale doubling strategy, and conducts empirical research on automatic trading in the foreign exchange market, aiming to establish a stable and profitable automatic trading system.

URL:https://www.airitilibrary.com/Article/Detail/U0002-2106202210483300

. Trend-following grid trading strategy—taking foreign exchange trading as an example

Author: Zeng Jianzhong

Institution: Tamkang University, Department of Information Management, Master's Program

Abstract: This study writes automated programs through trend-following grid trading strategies and conducts historical data backtesting in the foreign exchange market, aiming to optimize program trading parameters to obtain market profits.

URL:https://etds.lib.tku.edu.tw/ETDS/Home/Detail/U0002-2106202209512000

Contract Grid

Basic concepts

Contract grid trading applies grid trading strategies to the perpetual contract market, using leverage to amplify capital efficiency and profit from price fluctuations. It combines the mechanism of automatically buying low and selling high with the characteristics of the contract market, such as long, short and leverage.

How it works

• Select target:For example, BTC/USDT perpetual contract.
• Set the price range and grid number:For example, $60,000 ~ $70,000 is divided into 20 tiers.
• Choose direction:You can set up "two-way grid" (simultaneous long and short) or one-way (only long/short).
• Use leverage:Choose 1 to 5 times (or higher) based on risk tolerance to improve capital efficiency.
• Automatic order placement:When the price hits the set grid, a position is automatically opened and closed when the price rebounds or falls back to make a profit.

Advantages

• Volatility is opportunity:No matter whether the market fluctuates up or down, as long as the price fluctuates within the set range, profits can be achieved.
• High capital efficiency:The use of leverage allows small capital to operate larger positions.
• Can be shorted:Compared with the spot grid, the contract grid can be designed to make profits even if the market falls.

risk

• Liquidation risk:If the price moves rapidly unilaterally after using leverage, it is easy to cause position liquidation.
• Funding rate:Perpetual contracts need to pay funding rates, and long-term positions may lose profits.
• Price slippage and liquidation risk control:When the market fluctuates violently, the risk of slippage and leverage liquidation increases.

Recommended platform

• Binance Contract Grid
• Pionex Contract Grid
• Bybit contract trading (you can build your own grid)

high frequency trading

definition

High-frequency trading (HFT) is a trading strategy that uses algorithms and powerful computing power to execute a large number of transactions in a very short period of time. It mainly relies on low-latency technology to obtain market information and make decisions quickly.

How it works

High-frequency trading typically operates through the following techniques and strategies:

• Ultra-low latency network and servers: Reduce order execution time.
• Market microstructure analysis: Analyze the depth of buying and selling orders and price changes.
• Arbitrage trading: profiting from price differences between different exchanges.
• Liquidity provision: Earn the bid-ask spread through quick placement and cancellation of orders.

Advantages

• Improve market liquidity and narrow the bid-ask spread.
• Ability to quickly respond to market changes and improve transaction efficiency.
• Reduce the risk of human error through automated trading.

Risks and Challenges

• Market Volatility: Excessive automation can exacerbate market flash crashes.
• Regulatory issues: Countries have different regulatory policies for HFT, which affects market fairness.
• Technology costs: High-frequency trading requires expensive infrastructure and continuous optimization.

Common applications

• Automated trading in the stock market.
• Arbitrage and market making in cryptocurrency markets.
• High-speed trading strategies for futures and forex markets.

High frequency trading research paper

. "Buy Low, Sell High: A High-Frequency Trading Perspective"

Authors: Alvaro Cartea, Sebastian Jaimungal, and Jason Ricci

Abstract: This study explores the buy low and sell high strategy in high-frequency trading and proposes the best trading strategy to maximize expected profits.

URL:https://www.siam.org/Publications/Journals/SIAM-Journal-on-Financial-Mathematics

. "Speed, Algorithmic Trading, and Market Quality around Macroeconomic News Announcements"

Authors: Martin Scholtus, Dick van Dijk, Bart Frijns

Abstract: This study analyzes the impact of high-frequency trading on market quality during macroeconomic news releases.

URL:https://www.sciencedirect.com/journal/journal-of-banking-and-finance

. "The Flash Crash: The Impact of High-Frequency Trading on an Electronic Market"

Authors: Andrei Kirilenko, Albert S. Kyle, Mehrdad Samadi, Tugkan Tuzun

Abstract: This study explores the impact of high-frequency trading in electronic markets, specifically analyzing flash crash events.

URL:https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1686004

Floating profit roll position

Overview

Floating profit rolling is a trading strategy that when a position generates floating profits, part or all of the profits are reinvested into the market to expand the position and increase potential profits. This strategy is often used in leveraged trading markets such as futures, foreign exchange, and cryptocurrencies.

How it works

• Initial position opening:Open a position (long or short) based on market analysis.
• Produce floating profit:As the market changes favorably, unprofitable users increase.
• Partial take profit & add position:Lock in part of the profit and open a new position in the same direction, or directly use all floating profits to expand the position.
• Continuous rollover:When the market continues to develop in a favorable direction, continue to roll positions repeatedly to increase profits.
• Risk management:Set a stop loss point to prevent market reversal leading to retracement or loss expansion.

Advantages

• Improve the efficiency of fund use:Use market profits to reinvest and increase yields.
• Expand profit margins:When the market trend is clear, increase profits by rolling positions.
• Reduce principal risk:Using profits rather than principal to expand a position reduces the risk exposure of the original capital.

Potential risks

• Market reversal risk:When the market fluctuates violently, unlocked floating profits may be quickly retracted or even turn into losses.
• Leverage risk:If high leverage is used to roll positions, once the market changes, it may lead to forced liquidation.
• Psychological effects:Continuous rolling of positions may lead to greed and neglect of risk control.

Applicable markets and strategies

• Applicable markets:Futures (such as BTC futures, gold futures), Forex (such as EUR/USD), cryptocurrencies (such as ETH, SOL), stock derivatives (such as CFD contracts).
• Applicable strategies:Trend trading strategies, swing trading strategies, and long-term holding strategies.

in conclusion

Rolling profits is an effective fund management method that can amplify profits, but it requires strict risk control. If the market reverses and the profit is not taken in time, it may lead to profit taking or even losses. Therefore, traders should use this strategy rationally with appropriate take-profit and stop-loss plans to ensure steady profits.

Market transaction analysis

Trend judgment

Trend type

• Uptrend:The price continues to hit highs and the highs and lows move upward, which is a bull market.
• Downtrend:The price continues to make new lows and lower highs, which is a bear market.
• Consolidation trend:The price fluctuates within a certain range and lacks a clear direction.

Judgment method

1. High and low point analysis

Observe whether the structure of "high points higher than high points and low points higher than low points" continues to appear, which is an upward trend; otherwise, it is a downward trend.

2. Moving average arrangement

• Multi-head arrangement:When the short-term moving average is above the long-term moving average, it indicates an uptrend.
• Short position arrangement:When the short-term moving average is below the long-term moving average, it indicates a downtrend.

3. Trend lines and channels

Draw a support line and a pressure line. If the price moves along the trend line, the trend will continue; if it falls below or exceeds the trend line, a reversal may occur.

4. Trading volume assistance

When the trend is ongoing, the volume energy should be amplified synchronously with the direction of the trend. If the volume energy deviates from the trend, it should be noted that the trend may be fatigued or turning.

5. Technical indicators

• MACD：The intersection of the columnar body and the fast and slow line can be used as a long-short signal to assist in trend judgment.
• ADX：To assess trend strength, anything below 20 is consolidation and above 40 is a strong trend.
• Bollinger Bands:If the price advances along the upper or lower track of the channel, it can be regarded as a continuation of the trend.

Multi-cycle confirmation

Observe through different time periods such as daily, 4-hour, and 1-hour periods to confirm trend consistency and avoid entering a reverse pattern. It is best to follow the mid- to long-term trend when entering the market in the short term, and the risk is low.

reversal signal

• Head and shoulders top, double top, M head and other reversal patterns appear
• Price falls below major support or trendline
• Volume and price divergence, momentum indicators such as RSI or MACD divergence

Conclusion

Trend is the core basis for profitable trading. When judging the trend, cross-analysis of multiple tools such as price, trading volume, moving averages, technical indicators, and patterns should be combined with risk management to avoid chasing highs and lows and making wrong entries and exits.

Make trend judgments based on price and volume

Basic concepts

Price and trading volume are the two core elements of technical analysis. The direction of the trend is not only determined by the price itself, but also requires the cooperation of volume and energy to confirm the validity and continuity of the trend. If the price rise is accompanied by an increase in trading volume, the trend is considered healthy and sustainable; on the contrary, if the price rises and the volume shrinks, you need to be wary of a trend reversal or insufficient strength.

Trend judgment principles

• Price increase and volume increase:The bullish trend is confirmed and buying is active.
• Price decreases and volume increases:The short trend is confirmed and the selling pressure is heavy.
• Price increase and volume decrease:The upward momentum weakens and a correction or reversal is possible.
• Price decreases and volume decreases:The short trend has slowed down and entered the consolidation or rebound stage.

Application tools

• Average line:It is used to judge the recent trend of trading volume changes. If the volume can continue to be higher than the average volume, it means that the market is warm.
• OBV (energy wave):Accumulated trading volume and price changes are used to observe volume and price divergence and trend continuation.
• Volume Profile：Trading volume is distributed in different price ranges and is used to determine support/resistance locations.

Actual judgment process

1. First determine the price trend (such as breakthrough, moving average arrangement, pattern)
2. Observe whether trading volume increases in sync with the trend
3. If the price hits a high but trading volume fails to keep up, you should be wary of false increases or bullish inducements.
4. If the price hits a low but trading volume continues to decrease, it may be a false decline or a stabilization signal.

Suggestions for matching indicators

It can be combined with indicators such as RSI, MACD, Bollinger Bands, and volume and price analysis to enhance the accuracy of trend judgment. Changes in volume and energy can be used as the confirmation basis behind indicator signals to avoid blind pursuit of orders.

Conclusion

Price and volume analysis is an important cornerstone of trend analysis and judgment. By observing price and trading volume simultaneously, we can more accurately identify the strength of long and short positions and the authenticity of trends. In practice, it is recommended to observe in multiple cycles and cooperate with risk control management to effectively improve the winning rate of transactions.

Relative Strength Index RSI

Introduction to RSI

RSI (Relative Strength Index) is a technical indicator that measures the speed and magnitude of price changes, helping traders determine whether the market is overbought or oversold. The RSI value ranges from 0 to 100 and is typically used for short-term trading decisions.

Calculation method

RSI is calculated as follows:

RSI = 100 - [100 ÷ (1 + RS)]

in:

• RS (Relative Strength) = Average Points Up ÷ Average Points Down
• RSI is primarily calculated based on the average rise and fall over a 14-day period (or other set period).

Application of RSI

• Overbought and oversold:When the RSI is above 70, the market may be overbought and prices may correct; when the RSI is below 30, the market may be oversold and prices may rebound.
• Divergence signals:When the RSI and price move in opposite directions, such as when price makes a new high but the RSI does not, it may indicate a weakening trend.
• Trend confirmation:An RSI above 50 indicates a strong bullish market; an RSI below 50 indicates a strong bearish market.

Interpretation of examples

• RSI > 70：Prices may be overheated, consider taking profits or wait for a pullback.
• RSI < 30：Prices may be oversold and there may be an opportunity for a rebound.
• RSI Divergence:If the RSI falls but prices rise, it could be a sign of a trend reversal.

Things to note

• The RSI can remain above 70 or below 30 for extended periods of time in a strong trend, and can be misleading when used alone.
• Suitable for use in conjunction with other indicators (such as moving average, MACD) to improve the accuracy of trading decisions.
• RSI parameters can be adjusted according to the trading strategy. For example, short-term trading can use 7 or 9-day RSI to increase sensitivity.

Moving average convergence divergence indicator MACD

Introduction to MACD

MACD (Moving Average Convergence Divergence, Moving Average Convergence Divergence) is a trend indicator used to measure market momentum and help traders determine the timing of buying and selling. MACD analyzes the changes in long and short forces in the market through the relationship between two moving averages.

Calculation method

MACD consists of the following three components:

• MACD line:12-day EMA (short-term exponential moving average) – 26-day EMA (long-term exponential moving average)
• Signal line:9-day EMA (moving average of the MACD line)
• MACD Histogram:MACD line - signal line indicating changes in market momentum

Application of MACD

• Golden Cross (Bull):When the MACD line breaks above the signal line upward, it indicates that the market may turn into an uptrend.
• Death Cross (Short):When the MACD line falls below the signal line, it indicates that the market may be turning into a downtrend.
• Histogram changes:A change from negative to positive on the histogram indicates a strengthening market, and a change from positive to negative indicates a weakening market.
• Divergence signals:If the price makes a new high but the MACD does not, it could be a sign of a trend reversal.

Interpretation of examples

• MACD crosses the signal line online:Could be a buy signal.
• The MACD line crosses below the signal line:Could be a sell signal.
• The histogram becomes larger:Momentum is building and the trend may continue.
• Histogram zoomed out:Momentum weakens and a trend reversal is possible.

Things to note

• MACD is suitable for trending markets, but may produce false signals in volatile markets.
• Suitable for use with other technical indicators such as RSI and moving average to improve accuracy.
• The MACD parameters can be adjusted according to the trading style. For example, short-term trading can use (6, 13, 5) settings.

Bollinger Bands

Introduction to BOLL

BOLL (Bollinger Bands) is a technical indicator invented by John Bollinger to measure price volatility and help traders determine whether the market is overbought or oversold. Bollinger Bands consists of three lines, namely the middle track (moving average), the upper track and the lower track.

Calculation method

• Middle track (MA):N-day simple moving average (SMA)
• Upper Band:Medium track + K × N daily standard deviation
• Lower Band:Medium track - K × N daily standard deviation

Among them, N is usually set to 20, and K is usually set to 2, indicating that the channel range covers about 95% of the price movement.

Application of BOLL

• Breakout Trading Strategy:When the price breaks through the upper band, it may indicate a strong rise; when the price falls below the lower band, it may indicate that the market is weakening.
• Mean reversion strategy:When the price is close to the upper track, there may be an overheating callback; when the price is close to the lower track, it may rebound.
• Volatility analysis:When the Bollinger Bands narrow, it means that market volatility has narrowed and a breakout may be imminent.

Interpretation of examples

• The price is close to the upper track:The market may be overbought, so be aware of the risk of a pullback.
• The price is close to the lower track:The market may be oversold and there may be an opportunity for a rebound.
• Bollinger Bands Contraction:During periods of low volatility, the market may be about to experience severe volatility.
• Bollinger Bands Expansion:Volatility increases and a trend may occur.

Things to note

• BOLL is suitable for oscillating and trending markets, but used alone may cause misjudgment.
• The price may move close to the upper or lower track for a long time, which does not necessarily mean that a reversal is imminent.
• It is recommended to use indicators such as RSI, MACD or KDJ to improve the accuracy of trading decisions.

volume weighted average price

Introduction to VWAP

VWAP (Volume Weighted Average Price) is a technical indicator that measures the average transaction price of the market on that day and takes into account the impact of transaction volume. VWAP is commonly used in institutional and day trading to assess whether prices are within a reasonable range.

Calculation method

The VWAP calculation formula is as follows:

VWAP = (Cumulative transaction amount ÷ Cumulative transaction volume)

in:

• Cumulative transaction amount = price of each transaction × transaction volume
• Cumulative volume = total volume of all trades

Application of VWAP

• Transaction execution reference:Institutional investors will use VWAP to ensure that buying and selling prices are close to the market average and reduce the impact on market prices.
• Trend analysis:A price higher than VWAP indicates a stronger market trend; a price lower than VWAP indicates a weaker market trend.
• Support and pressure:VWAP can be used as a support and pressure line. If the price backtests VWAP and rebounds, it may be a buying opportunity; falling below VWAP may represent increased selling pressure.

Interpretation of examples

• Price > VWAP:Dominated by many parties, the market may be bullish.
• price< VWAP：The short side dominates, and the market may be bearish.
• Price is oscillating around VWAP:The market may be in a consolidation phase.

Things to note

• VWAP is suitable for intraday trading and cannot be used for long-term trend analysis because it is recalculated daily.
• VWAP changes a lot when the market opens and tends to stabilize over time.
• VWAP is not suitable for illiquid stocks because trading volume may not reflect the true trend of the market.

Cumulative volume difference

Introduction to Cumulative Volume Delta

Cumulative Volume Delta (CVD) is a technical analysis indicator used to measure the power of buyers and sellers in the market. It analyzes market trends and capital flows through the buying and selling differences in cumulative trading volume.

Calculation method

The calculation of CVD is based on the difference between the buying and selling volume of each transaction, and the cumulative calculation is as follows:

CVD = CVD of the previous period + (buyer’s trading volume – seller’s trading volume)

in:

• Buyer volume:The trading volume at the asking price (Ask) indicates that the market is actively buying.
• Seller’s volume:The trading volume at the bid price (Bid) indicates that the market is actively selling.

Applications of CVD

• Market trend confirmation:When CVD rises, it means the buyer is stronger; when CVD drops, it means the seller is stronger.
• Price and CVD Divergence:If the price rises but the CVD falls, it may indicate a lack of buying momentum, signaling a pullback in price; and vice versa.
• Large order tracking:Analyzing CVD changes can be used to identify the flow of funds for large orders and determine the behavior of the main market forces.

Interpretation of examples

• If CVD continues to rise and prices rise simultaneously, it means that buyers are driving the market and the trend is strong.
• If CVD rises but the price moves sideways, it may indicate the existence of hidden selling pressure and the price may fall back.
• If CVD falls and prices fall simultaneously, it means there is heavy selling pressure in the market and the trend may continue.

Things to note

• CVD is suitable for analysis together with other indicators (such as VWAP, RSI, MACD) to improve accuracy.
• Lower liquidity markets may produce false signals, which need to be analyzed in conjunction with trading volume.
• When the market fluctuates violently, CVD may experience short-term abnormal changes, and it is necessary to confirm whether the trend continues.

Hidden fluctuations in transaction price

Introduction to Transaction Price Hidden Waves

Transaction price implied volatility (Implied Volatility, IV) refers to the volatility calculated from the market transaction price of warrants or options. It reflects the market's expectations for future price volatility of the underlying asset and affects the prices of warrants and options.

Calculation method

Implied volatility is calculated by inverting the Black-Scholes option pricing model or other pricing models. The formula is as follows:

C = S * N(d1) - X * e^(-rt) * N(d2)

Among them, the volatility is inferred through the market transaction price, which is the hidden fluctuation of the transaction price.

Influencing factors

• Market Sentiment:When market volatility increases, implied volatility typically rises; when markets stabilize, implied volatility falls.
• Supply and demand:When the market demand for a certain warrant or option increases, the transaction price may increase, and the hidden wave will also rise accordingly.
• Major events:Events such as financial reports, economic data, and announcement of interest rate decisions may affect market expectations for future volatility.

Application of transaction price hidden wave

• Select the appropriate warrant or option:When the implied volatility is high, the warrant or option price is relatively high, which is suitable for the seller's strategy; when the implied volatility is low, it is suitable for the buyer's strategy.
• Measuring market risk:Higher hidden waves represent increased market uncertainty about the future of the underlying asset.
• Arbitrage trade:Investors can conduct volatility arbitrage through the level of hidden waves, such as the strategy of buying low hidden waves and selling high hidden waves.

Things to note

• Implied volatility does not guarantee that the market will be so volatile in the future, but only the market's current expectations.
• Hidden waves will fluctuate with changes in market sentiment, and strategies need to be dynamically adjusted.
• The underlying wave benchmarks of different underlying assets are different and should be compared and analyzed with historical volatility.

Contract open interest

Introduction to Open Interest

Open Interest (OI) refers to the number of contracts in the futures or options market that have not yet been closed or settled. It reflects market activity and capital inflows and is one of the important indicators for judging market trends.

Calculation method

The calculation of open interest is based on contract changes in the market:

• New contract creation:OI increases when buyers and sellers establish new contracts at the same time.
• Contract closing:When existing contract holders close their positions (sell or buy back), OI decreases.
• Contract transfer:If one party closes the position and the other party continues to hold it, OI remains unchanged.

Open Interest and price relationship

• OI rise + price rise:Indicates market capital inflow and the trend may continue.
• OI rise + price fall:It means that market capital is flowing in, but the short side is dominant, and prices may continue to fall.
• OI decrease + price increase:It indicates an outflow of funds from the market, which may be the liquidation of long positions, and the trend may weaken.
• OI decrease + price decrease:Indicates market capital outflows and short positions closing, which may indicate a bottom or trend reversal.

Applications and Analysis

• Trend confirmation:When OI increases, it indicates that funds are entering the market and the price trend may continue.
• Market sentiment judgment:An increase in OI usually means that speculative demand has increased and the market may enter a trend.
• Large capital trends:OI can be used to track whether institutional funds enter or exit the market, affecting market trends.

Things to note

• OI only reflects the number of market contracts, not the market direction, and needs to be analyzed together with price changes.
• A higher OI may indicate increased market activity, but may also be associated with increased risk if accompanied by severe price movements.
• A sudden drop in OI may signal the end of a trend or a shift, and you need to watch market movements for confirmation.

liquidation map

What is a Reckoning Map?

A liquidation map, also known as a liquidation map, is a visual tool used to display potential liquidations (liquidations) in different price ranges. Through this map, traders can understand the position distribution of long and short parties at various price points, thereby predicting possible liquidation prices and assessing market risks and liquidity.

The role of the liquidation map

• Risk management:Help traders identify high-risk areas and set stop losses or adjust positions in advance.
• Strategy development:Develop corresponding trading strategies based on the price areas where liquidation is concentrated.
• Market Insights:Understand the balance of power between the long and short sides in the market and predict possible price trends.

How to use the liquidation map?

Traders can observe the liquidation intensity in different price ranges through the liquidation map. When there is a large amount of potential liquidation in a certain price area, that area can become a key point for price movement. Traders can adjust trading strategies based on this information to avoid unnecessary risks.

Limitations of the Reckoning Map

• Predictive limitations:The liquidation map is based on current position data and cannot predict future market changes.
• Data reliability:The data sources and calculation methods of different platforms may be different and should be interpreted with caution.

Liquidate map resources

Here are some resources that provide reckoning maps:

• CoinGlass Liquidation Map
• CoinAnk Liquidation Map

Summarize

As an auxiliary tool for traders, the liquidation map can provide information on market positions and potential liquidations, helping with risk management and strategy formulation. However, traders should combine other market analysis tools to comprehensively assess market conditions and avoid over-reliance on a single indicator.

Liquidation heat map

definition

Liquidation Heatmap is a visual tool used to observe the distribution of potential liquidation points in the market. It is widely used in the cryptocurrency derivatives market, especially in the Bitcoin and Ethereum markets where highly leveraged transactions are prevalent.

use

• Identify areas where long and short leverage positions are concentrated
• Predict liquidation trigger points and potential risk areas for violent market fluctuations
• Observe the possible locations where institutions or large investors may set traps to lure bulls and traps short.

Display mode

The heat map uses the price range as the horizontal axis, and the liquidation volume or leverage position accumulation as the vertical axis. The brighter or redr the color, the denser the leverage positions in the area. Once the market hits this price, it may trigger a large number of serial liquidations, causing sudden and violent price fluctuations (commonly known as pins).

key observation points

• Gathering point:If a large number of red areas appear in a certain price band, it means that both long and short parties have intensive leverage positions. If the market touches this, a short-term liquidation wave may occur.
• Liquidation affects the direction:When the price is close to the leverage-intensive area of ​​​​long orders, it is easy to induce short selling, and when it is close to the short order area, it may explode.
• Reversal after liquidation:After liquidation, the price often moves in the opposite direction due to loss of driving force, which can be used as a short-term operation opportunity.

Common platforms

• Coinglass (formerly Bybt)
• Hyblock Capital
• Tensor Charts (combining grids and clearing heatmaps)
• Whalemap (combined on-chain and liquidation observation)

Matching strategy

Liquidation heat maps are often used in conjunction with grid trading, breakout strategies, and countertrend reversal operations. Traders can set take-profit and stop-loss above and below the hot zone, or wait for the liquidation to complete before entering the market in the opposite direction.

Risk warning

Although heat maps can be used as a prediction tool, they are not a guarantee of future trends. The market may experience irrational and drastic changes due to macro news, capital flows or main behaviors. Operations should still be cautious and combined with risk control strategies.

Conclusion

Liquidation heat maps are an important tool for understanding market pressure and momentum in highly leveraged markets. By understanding the concentration points of leveraged funds, they can help predict potential liquidation areas and improve operational risk management and the accuracy of entry and exit.

Depth distribution of buy and sell quotes

definition

Bid-Ask Profile (Depth Distribution of Bid and Ask Quotations) is an image or data structure in the financial market that displays the order quantity and density of buyers (Bid) and sellers (Ask) at different prices. It is commonly seen in the Order Book view and is used to reflect market liquidity, buying and selling power, and potential support/pressure areas.

composition

• Bid:An order to buy an asset at a certain price. Usually displayed on the left side of the order book.
• Ask (sell order):An order to sell an asset at a certain price. Usually displayed on the right side of the order book.
• Spread:The gap between the best bid price and the best sell price reflects market liquidity.

use

• Market in-depth analysis:Observing at which price levels there are a large number of pending orders can determine potential support/pressure.
• Trading strategy design:Conduct short-term trading and capture ultra-short fluctuations based on the distribution of pending orders.
• Price slip risk control:Referring to the Bid-Ask distribution when trading in bulk can reduce the occurrence of price slippage.

Example description

If you see this in the order book of a trading pair (such as BTC/USDT):

• Bid: There is a large number of buy orders at the price of 10,000 USDT
• Ask: There are a large number of sell orders at the price of 10,200 USDT

This means that the market expects intense trading within this range, which may form a support or pressure zone.

Visualization tools

• Binance order book view
• TradingLite Heatmap
• Bookmap (professional depth map software)

Conclusion

The Bid-Ask Profile is an important tool for observing market structure, helping to understand market participants' intentions and potential price movement areas. It is an indispensable reference for market makers, high-frequency traders and short-term investors.

Indicators of volatility

definition

The degree of shock refers to the extent to which market prices fluctuate up and down within a certain period, and is used to measure market instability and short-term trading activity. It is often used to identify the transition between range oscillators and trend disks.

Commonly used technical indicators

ATR（Average True Range）

• Shows the market’s actual range of fluctuations
• The larger the value, the more severe the shock, which is suitable for adjusting stop loss and profit stop.
• Can be used with moving averages to determine trend breakthroughs after shocks

Bollinger Bands (Bollinger Bands)

• The width of the upper and lower rails represents the degree of price fluctuations
• Narrowing bandwidth represents low volatility (consolidation); widening bandwidth represents high volatility (breakthrough)
• Can be considered as a precursor to breakout trades

Standard Deviation

• Used to measure the dispersion of prices from the mean
• Often used as the basis for Bollinger Band calculations
• A rising standard deviation indicates an increase in volatility, while a falling standard deviation indicates a stabilizing market.

Chaikin Volatility

• Observe the acceleration and deceleration of price shocks through the distance changes of Bollinger Bands
• An increase in the value represents an increase in volatility and usually indicates an imminent directional market.

ADX（Average Directional Index）

• Although it is mainly used to judge the strength of the trend, it can also be used to infer the degree of shocks.
• When ADX is below 20, it usually indicates a shock market, and when it is above 25, it is a trend market.

Application method

• Range trading strategies can be carried out with low shocks (high, low, long)
• When the shock expands, you can prepare a breakthrough strategy (price chasing in and out)
• Use trading volume to determine true and false breakthroughs to improve strategy accuracy

Conclusion

Understanding the degree of shocks can help traders choose appropriate strategies and opportunities. Through indicator assistance and dynamic adjustment of trading methods, the operating efficiency in shocks and trends can be greatly improved.

MVRV

definition

MVRV is the ratio of "Market Value / Realized Value". It is mainly used to analyze the market status of Bitcoin (or other crypto assets) and determine whether the price is overvalued or undervalued.

composition concept

• Market Value:Current price × circulating supply, that is, traditional market capitalization.
• Realized Value:The sum is calculated based on the price of each coin when it was last moved, reflecting the true cost of capital investment.

formula

MVRV = Market Value ÷ Realized Value

Interpretation method

• MVRV > 3：Markets can be overheated, relatively overvalued, and have historically experienced bubbles or corrections.
• MVRV ≈ 1：The market price is close to the average cost of holders, which is usually a relatively reasonable valuation range.
• MVRV < 1：The market price is lower than the average cost, and many investors lose money. It may be a long-term undervaluation or bottom range.

application

• Determine whether Bitcoin or other currencies have entered an overheated or undervalued area.
• Combined with other on-chain data (such as SOPR, NUPL) to assist in judging market cycles.
• It is suitable for observation by medium and long-term investors, but not suitable for short-term trading.

Common predictive indicators across markets

Indicators that can be applied to various countries' stock markets, commodity futures, cryptocurrencies and industrial sectors must have one core characteristic: it only relies on basic data that all markets have, such as price, trading volume or volatility, and does not rely on specific market structures (such as the yield curve requires the bond market, and the price-to-earnings ratio requires earnings data). The following systematically organizes these general indicators by category, and evaluates their accuracy based on backtesting and actual combat experience in recent years (2022-2025).

Overview of common indicators and accuracy classification in recent years

The most accurate combination in recent years: RSI + MACD + Bollinger Bands

According to Gate.io's backtest research in January 2026 and a peer-reviewed paper published in PMC/NIH in 2023 (across 10 cryptocurrencies, 2018-2022 data), the combination of RSI and MACD achieved a 77% winning rate in the backtest. After adding Bollinger Bands as the third layer of confirmation, it remained in the 73-77% range, while significantly reducing false signals. This combination works because each of the three indicators solves a different problem:

RSI is responsible for determining "whether market sentiment is excessive" and provides reversal warnings in oversold areas (below 30) or overbought areas (above 70). Recent research has found that a modified version of the RSI 50-100 strategy (entering when the RSI crosses 50 instead of the traditional 30) generated a 773.65% return in cryptocurrencies, which is 2.8 times the 275.22% return of the buy-and-hold strategy.

MACD is responsible for determining "trend direction and momentum strength." The MACD histogram turning from negative is a signal that momentum has turned bullish. However, the winning rate of MACD used alone is only about 40% (even lower than a coin toss in the BTC/USDT backtest), and it must be combined with other indicators to be meaningful.

Bollinger Bands is responsible for determining the "volatility state". When the Bollinger Bands squeeze (Squeeze), it means that the big market is about to start, but it does not provide directional information. About 40% of BTC Bollinger contractions historically have been downward breakouts, so directional confirmation must be provided by RSI and MACD.

Differences in performance of each indicator in different markets

Category 1: Momentum and Trend Indicators (Accuracy Core)

RSI — the most reliable single general indicator in recent years

RSI has been rated as one of the "most reliable technical indicators" in nearly 100 years of backtesting of the Dow Jones Industrial Index. A study on Indonesia's LQ45 index showed that RSI's accuracy is as high as 97%, far exceeding MACD's 52%. But this number needs to be interpreted with caution: RSI is indeed excellent at identifying overbought and oversold conditions, but it will stay in the overbought or oversold area for a long time in a strong trending market, leading to premature exit. In the 2021 BTC bull market, the RSI has been above 70 for several consecutive weeks. Traders who sold early according to traditional methods missed out on a large period of subsequent gains.

In recent years, the most effective RSI usage has evolved from the traditional "30 to buy 70 to sell" to the following variations:

Trend filtered version: In an uptrend (price above the 200-day EMA), only use RSI below 40 as a buy signal (buy on pullback); in a downtrend, only use RSI above 60 as a sell signal. This reduces glitches by about 40% compared to the traditional 30/70 setting.

RSI 50-100 strategy: Enter the market when RSI crosses 50, which means the momentum changes from weak to strong. PMC research shows that this strategy returns 2.8 times the returns of traditional strategies in cryptocurrencies.

Cumulative RSI (Connors RSI): Accumulate RSI values ​​within a specified number of days, providing smoother oversold/overbought judgments, and performs well in mean reversion strategies in the stock market.

MACD — the king of trend confirmation, but should not be used alone

MACD performs well in trending markets. After BTC’s MACD golden cross in October 2024, the price rose from $70,000 to over $100,000, an increase of 72.55%. But the core problem of MACD is hysteresis, because it is calculated based on moving averages, and it is easy to miss the best entry and exit points during rapid reversals.

In recent years, the most effective use of MACD is to use the direction of the histogram as a confirmation of kinetic energy, rather than relying on the golden cross/death cross as an entry and exit signal. The histogram turning from negative to positive means that selling pressure has subsided and buying pressure has entered. Combined with the oversold reading of RSI, it can provide a high-quality entry signal.

Momentum Ranking System — the best tool for cross-asset rotation

Momentum ranking is not an "indicator" in the traditional sense, but a set of methodology: calculate the return rate of each asset in multiple time windows, rank them after weighting, buy in the top rankings and avoid the bottom rankings. This method can be applied indiscriminately to horizontal comparisons between national stock market indices, commodities, sector ETFs and even cryptocurrencies.

Academic research (and a large number of follow-up studies since Jegadeesh & Titman, 1993) continues to confirm that the momentum effect of "the assets that performed best in the past 3 to 12 months tend to continue to outperform in the next 1 to 3 months" holds true in almost all asset classes around the world. Empirical evidence in recent years also supports this: the sustainability of the momentum of the US stock technology sector from 2023 to 2024, the continued rise of gold in 2024 after breaking through new historical highs, and the leading momentum of Japanese and Korean stocks in the Asian market from 2024 to 2025, are all examples of the cross-asset momentum effect.

Category 2: Volatility indicators (core risk control)

ATR — The most underrated yet useful universal metric

ATR (Average True Range) itself does not generate buying and selling signals, but it is the most reliable risk management tool in all markets. ATR measures the average daily fluctuation range of an asset over a period of time, and can be used to set dynamic stop losses, calculate reasonable position sizes, and determine whether volatility is abnormal.

The versatility of ATR is that it is calculated entirely based on the high and low points of price and is not affected by differences in market structure. Whether it is gold that fluctuates 2% in a day or BTC that fluctuates 10% in a day, a 2x ATR stop loss can provide risk control that matches the volatility characteristics of the market.

The most effective uses of ATR in recent years include: using 2 times ATR (14) as a trailing stop (Chandelier Exit), which has the best effect in trending markets; using the relative changes in ATR to judge "volatility compression". When the current ATR drops below 50% of the recent average, it indicates that the big market is about to start (similar to Bollinger contraction).

Bollinger Bands — the best visualization tool for volatility contraction/expansion

Bollinger Bands was identified by John Bollinger himself as a "near-perfect bottom pattern" for BTC in January 2026, with a target price of $100,000 to $107,000. Bollinger contraction is one of the most reliable "big market precursors" signals in all markets, but it only indicates that fluctuations are about to amplify, but does not tell you the direction.

Category 3: Energy indicators (filters for true and false signals)

OBV and MFI - trading volume does not lie

The core value of volume and energy indicators is to confirm the "authenticity" of price trends. If the price breaks through but the trading volume shrinks, the breakthrough is likely to be false; if the price has not yet broken through but the OBV (energy wave) has reached a new high, it means that smart money is entering the market.

Volume indicators are very effective in the stock market and commodity futures, but require special caution in the cryptocurrency market. Due to the prevalence of wash trading in the crypto market, the reliability of trading volume data is much lower than in traditional markets. It is only recommended to use volume analysis on data from mainstream currencies such as BTC and ETH, as well as regulated exchanges (such as CME Bitcoin Futures).

Category 4: Cross-asset comparison indicators (rotating core)

Relative Strength Ratio

Compare the prices of any two assets and observe the trend of the ratio. This is the simplest and most effective cross-market comparison tool. It does not rely on any specific indicator parameters and can compare any two priced targets.

Z-Score standardized ranking

When multiple disparate markets need to be compared simultaneously, the Z-Score is the only method that can eliminate dimensional differences. After converting each market's indicator value (such as return rate, volatility, RSI reading) into the standard deviation multiple from the mean, different markets can be sorted horizontally on the same table.

The most accurate practical combination strategy in recent years

Strategy One: Trend Following + Momentum Confirmation (Suitable for All Markets)

Entry conditions: Price stands above the 200-day EMA (confirmation of the long-term upward trend) + RSI rises from below 40 to above 40 (momentum picks up) + MACD histogram corrects (trend confirmation). Exit conditions: The price falls below the 200-day EMA or the trailing stop loss of ATR(14) × 2 is triggered. Backtest winning rate: 65-73% in trending market, 45-55% in consolidation market.

Strategy 2: Mean reversion + volatility compression (suitable for volatile markets)

Entry conditions: price hits the lower Bollinger Band + RSI below 30 + MACD histogram becomes negative (selling pressure subsides). Exit conditions: The price touches the Bollinger Band (20-day SMA) or the RSI returns above 50. Backtest winning rate: 60-70% in consolidation market, but a lot of false signals will be generated in strong trend.

Strategy 3: Cross-asset momentum rotation (suitable for asset allocation)

The weighted momentum score of all candidate assets is calculated monthly (1-month return × 40% + 3-month return × 35% + 6-month return × 25%). Buy the top 20% of assets and sell the bottom 20% of assets. Rebalance monthly. Backtest winning rate: As a filter for stock/asset selection, the long-term annualized excess return is 3-7%.

Programmed implementation: universal cross-market indicator calculation engine

import yfinance as yf
import pandas as pd
import numpy as np

# ==========================================
# General indicator calculation module (applicable to any market with OHLCV data)
# ==========================================

def calc_rsi(series, period=14):
    delta = series.diff()
    gain = delta.where(delta > 0, 0).rolling(period).mean()
    loss = (-delta.where(delta < 0, 0)).rolling(period).mean()
    rs = gain / loss
    return 100 - (100 / (1 + rs))

def calc_macd(series, fast=12, slow=26, signal=9):
    ema_fast = series.ewm(span=fast).mean()
    ema_slow = series.ewm(span=slow).mean()
    macd_line = ema_fast - ema_slow
    signal_line = macd_line.ewm(span=signal).mean()
    histogram = macd_line - signal_line
    return macd_line, signal_line, histogram

def calc_bollinger(series, period=20, std_dev=2):
    mid = series.rolling(period).mean()
    std = series.rolling(period).std()
    upper = mid + std_dev * std
    lower = mid - std_dev * std
    bandwidth = (upper - lower) / mid * 100
    return upper, mid, lower, bandwidth

def calc_atr(high, low, close, period=14):
    tr1 = high - low
    tr2 = abs(high - close.shift(1))
    tr3 = abs(low - close.shift(1))
    tr = pd.concat([tr1, tr2, tr3], axis=1).max(axis=1)
    return tr.rolling(period).mean()

# ==========================================
# Universal market scanner: calculates a full set of indicators for any underlying
# ==========================================
def universal_scanner(ticker, period='1y'):
    """
    Calculate a full set of common indicators for any underlying available with yfinance
    Applicable: stock market index, individual stocks, ETF, futures, cryptocurrency
    """
    data = yf.download(ticker, period=period)
    if data.empty:
        return None

    close = data['Close'].squeeze()
    high = data['High'].squeeze()
    low = data['Low'].squeeze()
    volume = data['Volume'].squeeze()

    # Calculate all indicators
    rsi = calc_rsi(close)
    macd_line, signal_line, histogram = calc_macd(close)
    bb_upper, bb_mid, bb_lower, bb_width = calc_bollinger(close)
    atr = calc_atr(high, low, close)

    ema_9 = close.ewm(span=9).mean()
    ema_21 = close.ewm(span=21).mean()
    ema_50 = close.ewm(span=50).mean()
    ema_200 = close.ewm(span=200).mean()

    latest = close.iloc[-1]

    #Return rate required for momentum ranking
    ret_1m = (close.iloc[-1] / close.iloc[-21] - 1) * 100 if len(close) > 21 else 0
    ret_3m = (close.iloc[-1] / close.iloc[-63] - 1) * 100 if len(close) > 63 else 0
    ret_6m = (close.iloc[-1] / close.iloc[-126] - 1) * 100 if len(close) > 126 else 0
    momentum_score = ret_1m * 0.4 + ret_3m * 0.35 + ret_6m * 0.25

    # Comprehensive signal judgment
    signals = []
    if rsi.iloc[-1] < 30: signals.append('RSI oversold')
    elif rsi.iloc[-1] > 70: signals.append('RSI overbought')
    if histogram.iloc[-1] > 0 and histogram.iloc[-2] < 0: signals.append('MACD column goes long')
    elif histogram.iloc[-1] < 0 and histogram.iloc[-2] > 0: signals.append('MACD column short')
    if latest > ema_200.iloc[-1]: signals.append('Stand on EMA200 (long)')
    else: signals.append('Fall below EMA200 (short)')
    if latest < bb_lower.iloc[-1]: signals.append('Touching lower Bollinger Band')
    elif latest > bb_upper.iloc[-1]: signals.append('Breaking through Bollinger's track')

    # Bollinger shrinkage detection
    bb_avg = bb_width.tail(120).mean()
    if bb_width.iloc[-1] < bb_avg * 0.5:
        signals.append('Bollinger is extremely shrinking (a sign of big market trends)')

    return {
        'subject': ticker,
        'price': round(latest, 2),
        'RSI(14)': round(rsi.iloc[-1], 1),
        'MACD column': round(histogram.iloc[-1], 4),
        'Bollinger Bandwidth%': round(bb_width.iloc[-1], 2),
        'ATR(14)': round(atr.iloc[-1], 4),
        'vs EMA200': 'above' if latest > ema_200.iloc[-1] else 'below',
        '1M reward%': round(ret_1m, 2),
        '3M remuneration%': round(ret_3m, 2),
        'Kinetic energy fraction': round(momentum_score, 2),
        'signal': signals
    }

# ==========================================
# Cross-market batch scanning and ranking
# ==========================================
def cross_market_scan():
    """Scan multiple markets and rank by momentum"""
    universe = {
        #stock markets of various countries
        'US Stocks S&P500': 'SPY',
        'European stocks STOXX600': 'EXSA.DE',
        'Nikkei': 'EWJ',
        'TAIEX': 'EWT',
        'Emerging markets': 'EEM',
        'China A-shares': 'ASHR',
        # Commodity Futures
        'gold': 'GC=F',
        'silver': 'SI=F',
        'crude': 'CL=F',
        'copper': 'HG=F',
        'natural gas': 'NG=F',
        #cryptocurrency
        'Bitcoin': 'BTC-USD',
        'Ethereum': 'ETH-USD',
        'SOL': 'SOL-USD',
        # section
        'Beautiful Technology': 'XLK',
        'American Finance': 'XLF',
        'American Energy': 'XLE',
        'Beauty Medical': 'XLV',
        'semiconductor': 'SMH',
    }

    results = []
    for name, ticker in universe.items():
        try:
            r = universal_scanner(ticker)
            if r:
                r['name'] = name
                results.append(r)
        except Exception as e:
            print(f"{name}fail:{e}")

    df = pd.DataFrame(results)
    df = df.sort_values('Kinetic energy fraction', ascending=False)
    return df

# ==========================================
# Comprehensive Signal Scorecard
# ==========================================
def signal_scorecard(ticker):
    """
    Generates a comprehensive score of -5 to +5 for a single target
    Positive score = long side, negative score = short side
    """
    data = yf.download(ticker, period='1y')
    close = data['Close'].squeeze()
    high = data['High'].squeeze()
    low = data['Low'].squeeze()

    score = 0
    reasons = []

    # 1. Trend (EMA 200)
    ema200 = close.ewm(span=200).mean()
    if close.iloc[-1] > ema200.iloc[-1]:
        score += 1; reasons.append('Trend: Above EMA200 (+1)')
    else:
        score -= 1; reasons.append('Trend: Below EMA200 (-1)')

    # 2. Momentum (RSI)
    rsi = calc_rsi(close)
    rsi_val = rsi.iloc[-1]
    if rsi_val < 30:
        score += 1; reasons.append(f'RSI oversold ({rsi_val:.0f}) (+1 reversal opportunity)')
    elif rsi_val > 70:
        score -= 1; reasons.append(f'RSI overbought ({rsi_val:.0f}) (-1 overheated)')
    elif 50 < rsi_val < 65:
        score += 0.5; reasons.append(f'RSI is healthy ({rsi_val:.0f}) (+0.5)')

    # 3. MACD histogram direction
    _, _, hist = calc_macd(close)
    if hist.iloc[-1] > 0 and hist.iloc[-1] > hist.iloc[-2]:
        score += 1; reasons.append('MACD histogram is positive and expanding (+1)')
    elif hist.iloc[-1] < 0 and hist.iloc[-1] < hist.iloc[-2]:
        score -= 1; reasons.append('MACD histogram is negative and expanding (-1)')

    # 4. Bollinger position
    bb_u, bb_m, bb_l, bb_w = calc_bollinger(close)
    if close.iloc[-1] < bb_l.iloc[-1]:
        score += 0.5; reasons.append('Price below Bollinger Band (+0.5 mean reversion)')
    elif close.iloc[-1] > bb_u.iloc[-1]:
        score -= 0.5; reasons.append('Price above upper Bollinger Band (-0.5 overextended)')

    # 5. Volatility status
    bb_avg = bb_w.tail(120).mean()
    if bb_w.iloc[-1] < bb_avg * 0.5:
        reasons.append('Extreme compression of volatility (a precursor to a big market trend, the direction needs to be confirmed)')

    verdict = 'Strongly bullish' if score >= 3 else 'Towards too much' if score >= 1 \
        else 'neutral' if score > -1 else 'bearish' if score > -3 else 'Strongly bearish'

    return {
        'subject': ticker,
        'Comprehensive score': round(score, 1),
        'judge': verdict,
        'reason': reasons
    }

# Usage example
# signal_scorecard('BTC-USD') # Bitcoin
# signal_scorecard('GC=F') # Gold futures
# signal_scorecard('SPY') # US stock S&P500
# signal_scorecard('0050.TW') # Taiwan 50 ETF
# cross_market_scan() # Full market scan ranking

Fundamental principles for using indicators

First, no single indicator is effective in all market conditions. The core finding of Dow Jones backtesting in the past 100 years is that RSI and Bollinger Bands are the most reliable indicators, but their advantage lies in "high winning rate" rather than "high return rate". The indicators with the highest total returns tend to be trend following systems (such as Donchian Channel Breakout), but they have a low winning rate (perhaps only 45-50%), relying on a few big wins to make up for most small losses.

Second, the value of indicator combinations lies in reducing false signals rather than creating perfect signals. The winning rate when RSI is used alone is 55-65%, when combined with MACD it increases to 65-73%, and when Bollinger Channel is added it maintains 73-77%. But with each additional layer of filtering, trading opportunities decrease. In practice, two to three complementary indicators (one trend, one momentum, one volatility) are the best configuration.

Third, parameters need to be adjusted according to market characteristics. Cryptocurrencies are approximately 3 to 5 times more volatile than the stock market, and using the same RSI threshold will produce completely different results. In highly volatile markets, the oversold threshold should be relaxed from 30 to 25, and the overbought threshold should be relaxed from 70 to 75; the ATR stop loss multiple also needs to be increased accordingly.

Fourth, when comparing across markets, the absolute values ​​of indicators cannot be directly compared and must be standardized by Z-Score first. An RSI reading of 60 on gold means completely different things than an RSI reading of 60 on BTC because the fluctuation structure of the two is different. But momentum rankings (rankings of returns) and relative strength ratios (trends in price ratios) are inherently comparable across markets and do not require additional standardization.

Fifth, technical indicators are only reliable in markets with sufficient liquidity. The prices of low-liquidity altcoins, unpopular futures contracts or small stocks are easily manipulated by a few large investors, and the premise of technical analysis (that the market is a reflection of the collective behavior of the majority of participants) does not hold. In illiquid markets, fundamental analysis and position sizing control are far more important than technical indicators.

Composite indicator momentum ranking

The traditional momentum ranking only uses "return rate in the past N months" for ranking, which is pure price momentum. If the signals of RSI, MACD and Bollinger Bands are integrated into a composite score, and then cross-asset rankings are made based on this score, it can indeed significantly improve the quality of rotation decision-making. The reason is: a single return rate ranking only tells you "who is running the fastest", but the composite ranking also tells you "who is running the fastest, whether the momentum is healthy, whether the trend is confirmed, and whether the volatility is in a favorable position."

Why pure return rate ranking is not enough

Design architecture for composite kinetic energy fraction

The raw values ​​of each metric are converted into standardized scores from 0 to 100 and then summed by weight. In this way, indicators with different dimensions (return rate is a percentage, RSI is 0-100, MACD is an absolute value, and Bollinger Bandwidth is a percentage) can be put on the same scale.

Rating details for each dimension

Dimension 1: Price Momentum (30%)

Calculate the weighted average of 1-month, 3-month, and 6-month return rates, and then perform a percentile ranking (0 to 100) among all candidate targets. For example, the return rate among 20 targets ranks third, and the percentile score is (20-3)/20 × 100 = 85 points. The recent weighting is higher because the momentum effect is strongest in the time window of 1 to 3 months, and mean reversion begins after 6 months.

Dimension 2: RSI momentum health (20%)

The RSI score is not linear. The optimal range is 40 to 65, which means momentum is rising healthily but has not yet overheated. The scoring curve is as follows:

Note that an oversold RSI does not automatically earn you a high score. Extremely oversold (below 25) actually lowers the score, because the RSI can stay in the oversold zone for a long time during a crash, and buying at this time may be a bargain. Only when the RSI rebounds from the oversold zone to above 40 does it mean that momentum is indeed improving.

Dimension three: MACD trend confirmation (25%)

MACD has a slightly higher weight than RSI because in cross-asset rotation scenarios, trend confirmation is more important than overbought and oversold judgments. The score takes into account both the positive and negative points of the histogram and the direction of change:

Dimension 4: Bollinger volatility position (15%)

Bollinger Bands provide two key pieces of information: bandwidth (the amount of volatility) and the relative position of price within the channel. The combination of the two produces a score:

Dimension 5: Trend structure (10%)

This is the simplest and most robust filtering layer. The order of price, EMA50 and EMA200 reflects the health of the mid- to long-term trend:

Complete Python implementation

import yfinance as yf
import pandas as pd
import numpy as np
from datetime import datetime

# =============================================
#Basic indicator calculation function
# =============================================

def calc_rsi(series, period=14):
    delta = series.diff()
    gain = delta.where(delta > 0, 0).rolling(period).mean()
    loss = (-delta.where(delta < 0, 0)).rolling(period).mean()
    rs = gain / loss
    return 100 - (100 / (1 + rs))

def calc_macd(series, fast=12, slow=26, signal=9):
    ema_f = series.ewm(span=fast).mean()
    ema_s = series.ewm(span=slow).mean()
    macd = ema_f - ema_s
    sig = macd.ewm(span=signal).mean()
    hist = macd - sig
    return macd, sig, hist

def calc_bollinger(series, period=20, std=2):
    mid = series.rolling(period).mean()
    sd = series.rolling(period).std()
    upper = mid + std * sd
    lower = mid - std * sd
    width = (upper - lower) / mid * 100
    pct_b = (series - lower) / (upper - lower)  # 0=lower rail, 1=upper rail
    return upper, mid, lower, width, pct_b

# =============================================
# Scoring function for each dimension
# =============================================

def score_price_momentum(close):
    """Dimension 1: Price momentum (original rate of return, percentile ranking across targets will be done later)"""
    n = len(close)
    ret_1m = (close.iloc[-1] / close.iloc[-21] - 1) if n > 21 else 0
    ret_3m = (close.iloc[-1] / close.iloc[-63] - 1) if n > 63 else 0
    ret_6m = (close.iloc[-1] / close.iloc[-126] - 1) if n > 126 else 0
    raw = ret_1m * 0.4 + ret_3m * 0.35 + ret_6m * 0.25
    return raw  # Return the original value and do the ranking in the outer layer

def score_rsi_health(close):
    """Dimension 2: RSI momentum health"""
    rsi = calc_rsi(close)
    val = rsi.iloc[-1]
    if np.isnan(val): return 50, val

    # Non-linear scoring curve
    if val > 80:   score = 10
    elif val > 70: score = 30
    elif val > 65: score = 60
    elif val > 50: score = 100  # Best interval
    elif val > 40: score = 80
    elif val > 30: score = 60
    elif val > 25: score = 50
    else:         score = 30

    # Bonus points: RSI is picking up from lows (direction is more important than position)
    rsi_3d_ago = rsi.iloc[-4] if len(rsi) > 4 else val
    if val < 50 and val > rsi_3d_ago + 3:
        score = min(score + 15, 100)  # Bonus points for rebounding from low position

    return score, round(val, 1)

def score_macd_trend(close):
    """Dimension 3: MACD trend confirmation"""
    macd_line, _, hist = calc_macd(close)
    if len(hist.dropna()) < 5:
        return 50, 'Insufficient information'

    h = hist.iloc[-1]
    h1 = hist.iloc[-2]
    h2 = hist.iloc[-3]
    m = macd_line.iloc[-1]

    # Determine the direction and continuity of the histogram
    if h > 0:
        if h > h1 and h1 > h2:
            score = 100; desc = 'The column is positive and continuously expanding'
        elif h > h1:
            score = 85; desc = 'The column is straight and expanded'
        elif h1 <= 0:
            score = 90; desc = 'The column has just turned (kinetic energy starts)'
        else:
            score = 50; desc = 'The column is straight but shrinking'
    else:
        if h > h1:
            score = 40; desc = 'The bar is negative but shrinking (improving)'
        elif h < h1 and h1 < h2:
            score = 5; desc = 'The bar is negative and continues to expand (accelerating the decline)'
        else:
            score = 20; desc = 'The bar is negative and expanding'

    # Additional points for MACD lines above the zero axis
    if m > 0 and h > 0:
        score = min(score + 10, 100)

    return score, desc

def score_bollinger_position(close):
    """Dimension Four: Bollinger Volatility Position"""
    upper, mid, lower, width, pct_b = calc_bollinger(close)
    if len(width.dropna()) < 120:
        return 50, 'Insufficient information'

    w = width.iloc[-1]
    w_prev = width.iloc[-6]  # Bandwidth one week ago
    pb = pct_b.iloc[-1]     # 0=lower rail, 0.5=middle rail, 1=upper rail

    # Historical percentile of bandwidth
    w_pctile = (width.tail(120) < w).mean() * 100
    squeeze = w_pctile < 20       # extreme shrinkage
    expanding = w > w_prev       # Bandwidth is expanding

    if squeeze and expanding and pb > 0.8:
        score = 100; desc = 'Upward expansion breakthrough after contraction (best)'
    elif squeeze:
        score = 70; desc = 'Bandwidth is extremely shrinking (gathering momentum)'
    elif 0.5 < pb < 0.9 and w_pctile < 70:
        score = 75; desc = 'Healthy rise (between middle track and upper track)'
    elif pb > 1.0 and w_pctile > 80:
        score = 25; desc = 'Overextension (outside the upper track + extremely wide bandwidth)'
    elif pb < 0.2:
        score = 35; desc = 'Close to the lower track (weak)'
    elif squeeze and expanding and pb < 0.2:
        score = 10; desc = 'Downward breakthrough after contraction (worst)'
    else:
        score = 50; desc = 'neutral'

    return score, desc

def score_trend_structure(close):
    """Dimension 5: EMA trend structure"""
    ema50 = close.ewm(span=50).mean().iloc[-1]
    ema200 = close.ewm(span=200).mean().iloc[-1]
    price = close.iloc[-1]

    if price > ema50 > ema200:
        return 100, 'Perfect long arrangement'
    elif price > ema200 and price < ema50:
        return 60, 'Long-term bulls but short-term pullback'
    elif price < ema50 and price > ema200:
        return 40, 'Short-term weakening but long-term unbreakable'
    else:
        return 0, 'Perfect short arrangement'

# =============================================
# Compound kinetic energy ranking engine
# =============================================

def composite_momentum_rank(universe, period='1y',
                            w_mom=0.30, w_rsi=0.20,
                            w_macd=0.25, w_bb=0.15,
                            w_trend=0.10):
    """
    Calculate and rank five-dimensional composite kinetic energy scores for all candidate targets

    Parameters:
      universe: dict, {'name': 'ticker code', ...}
      period: data period
      w_*: weight of each dimension (sum = 1.0)

    Returns:
      DataFrame, sorted by composite score from high to low
    """
    records = []

    for name, ticker in universe.items():
        try:
            data = yf.download(ticker, period=period, progress=False)
            if data.empty or len(data) < 200:
                continue
            close = data['Close'].squeeze()

            # Calculate each dimension
            mom_raw = score_price_momentum(close)
            rsi_score, rsi_val = score_rsi_health(close)
            macd_score, macd_desc = score_macd_trend(close)
            bb_score, bb_desc = score_bollinger_position(close)
            trend_score, trend_desc = score_trend_structure(close)

            records.append({
                'name': name,
                'code': ticker,
                'price': round(close.iloc[-1], 2),
                'Original value of kinetic energy': round(mom_raw * 100, 2),
                'RSI': rsi_val,
                'RSI score': rsi_score,
                'MACD score': macd_score,
                'MACD status': macd_desc,
                'Boolean score': bb_score,
                'Boolean status': bb_desc,
                'trend score': trend_score,
                'Trend status': trend_desc,
            })
        except Exception as e:
            print(f"{name}({ticker}) failed:{e}")

    df = pd.DataFrame(records)
    if df.empty:
        return df

    # Percentile ranking of price momentum across targets (0-100)
    df['Momentum Ranking Score'] = df['Original value of kinetic energy'].rank(pct=True) * 100

    # Calculate weighted composite score
    df['composite fraction'] = (
        df['Momentum Ranking Score'] * w_mom +
        df['RSI score']     * w_rsi +
        df['MACD score']    * w_macd +
        df['Boolean score']    * w_bb +
        df['trend score']    * w_trend
    ).round(1)

    # Ranking
    df = df.sort_values('composite fraction', ascending=False)
    df['Ranking'] = range(1, len(df)+1)
    df = df.reset_index(drop=True)

    # Mark suggested actions
    df['suggestion'] = df['composite fraction'].apply(
        lambda x: 'Strong Buy' if x >= 80 else
                  'Buy'     if x >= 65 else
                  'Wait and see'     if x >= 45 else
                  'Reduce'     if x >= 30 else
                  'avoid'
    )

    return df

# =============================================
# Execution: full scan across markets
# =============================================

universe = {
    #stock markets of various countries
    'US Stocks S&P500':  'SPY',
    'Nasdaq':    'QQQ',
    'European stocks STOXX':  'VGK',
    'Japanese stocks':        'EWJ',
    'Taiwan stocks':        'EWT',
    'Korean stocks':        'EWY',
    'Emerging markets':    'EEM',
    'China A-shares':     'ASHR',
    'India':        'INDA',
    # precious metals
    'gold':        'GC=F',
    'silver':        'SI=F',
    #energy
    'crude':        'CL=F',
    'natural gas':      'NG=F',
    #industrialmetal
    'copper':          'HG=F',
    #cryptocurrency
    'Bitcoin':      'BTC-USD',
    'Ethereum':      'ETH-USD',
    'SOL':         'SOL-USD',
    #US stock sector
    'science and technology':        'XLK',
    'finance':        'XLF',
    'Energy stocks':      'XLE',
    'Medical':        'XLV',
    'semiconductor':      'SMH',
    'Utilities':    'XLU',
    'real estate':      'XLRE',
}

# implement
result = composite_momentum_rank(universe)

# Display ranking results
display_cols = ['Ranking','name','composite fraction','suggestion',
                'Original value of kinetic energy','RSI','MACD status',
                'Boolean status','Trend status']
print(result[display_cols].to_string(index=False))

# Classification output
print("\n=== Strong Buy Zone ===")
print(result[result['suggestion']=='Strong Buy'][['name','composite fraction','MACD status']])
print("\n=== Avoid area ===")
print(result[result['suggestion']=='avoid'][['name','composite fraction','MACD status']])

Advanced: Dynamic Weight Adjustment

Fixed weights are sufficient most of the time, but different market environments place different importance on each dimension. Here's an advanced version that automatically adjusts weights based on market conditions:

def adaptive_weights(vix_level=None):
    """
    Automatically adjust the weight of each dimension according to the market volatility environment

    Low volatility (VIX < 15) → Momentum dominates, trend following is king
    Medium volatility (VIX 15-25) → balanced allocation
    High volatility (VIX > 25) → RSI oversold bounce + volatility position more important
    Extremely high volatility (VIX > 35) → The trend structure is the most important, only the targets of the long arrangement
    """
    if vix_level is None:
        try:
            vix = yf.download('^VIX', period='5d', progress=False)
            vix_level = vix['Close'].iloc[-1].item()
        except:
            vix_level = 20  # Default medium fluctuation

    if vix_level < 15:
        # Low volatility: clear trend, best momentum tracking effect
        weights = {'mom': 0.40, 'rsi': 0.15, 'macd': 0.25,
                   'bb': 0.10, 'trend': 0.10}
        regime = 'Low Volatility (Momentum Tracking Dominates)'
    elif vix_level < 25:
        # Medium fluctuation: standard balanced configuration
        weights = {'mom': 0.30, 'rsi': 0.20, 'macd': 0.25,
                   'bb': 0.15, 'trend': 0.10}
        regime = 'Medium fluctuation (balanced allocation)'
    elif vix_level < 35:
        # High Volatility: Oversold rebound and volatility position are more important
        weights = {'mom': 0.15, 'rsi': 0.30, 'macd': 0.20,
                   'bb': 0.20, 'trend': 0.15}
        regime = 'High volatility (mean reversion + volatility dominance)'
    else:
        # Extremely high volatility: trend structure determines everything
        weights = {'mom': 0.10, 'rsi': 0.20, 'macd': 0.15,
                   'bb': 0.25, 'trend': 0.30}
        regime = 'Extremely high volatility (trend structure + risk control dominance)'

    print(f"VIX: {vix_level:.1f}→ Market status:{regime}")
    print(f" weight: kinetic energy{weights['mom']:.0%} RSI{weights['rsi']:.0%}"
          f" MACD{weights['macd']:.0%}Brin{weights['bb']:.0%}"
          f" trend{weights['trend']:.0%}")
    return weights, regime

# Perform ranking using dynamic weights
w, regime = adaptive_weights()
result = composite_momentum_rank(
    universe,
    w_mom=w['mom'], w_rsi=w['rsi'],
    w_macd=w['macd'], w_bb=w['bb'],
    w_trend=w['trend']
)

The complete process of monthly rotation strategy

def monthly_rotation_strategy(universe, top_n=5, bottom_n=3):
    """
    Monthly rotation strategy:
    1. Calculate the composite kinetic energy scores of all targets
    2. Buy the top_n names
    3. Bottom_n names after selling (or shorting)
    4. Output position suggestions and hand-changing indicators
    """
    # Get dynamic weight
    w, regime = adaptive_weights()

    # Execute ranking
    df = composite_momentum_rank(
        universe,
        w_mom=w['mom'], w_rsi=w['rsi'],
        w_macd=w['macd'], w_bb=w['bb'],
        w_trend=w['trend']
    )

    if df.empty:
        print("No valid data")
        return

    # Select positions
    longs = df.head(top_n)
    shorts = df.tail(bottom_n)

    report = f"""
{'='*60}
  Composite Momentum Rotation Strategy – Monthly Report
  Date: {datetime.now().strftime('%Y-%m-%d')}
  Market status: {regime}
{'='*60}

【Buy/Hold Top {top_n}】
{longs[['Ranking','Name','Composite Score','Recommendation','RSI','MACD Status','Trend Status']].to_string(index=False)}

【Avoid/Reduce the code after {bottom_n} name】
{shorts[['ranking','name','composite score','recommendation','RSI','MACD status','trend status']].to_string(index=False)}

【Full ranking】
{df[['Ranking','Name','Composite Score','Recommendation','Original Momentum Value','RSI','MACD Status']].to_string(index=False)}
"""
    print(report)
    return df, longs, shorts

# Perform monthly rotation
df, longs, shorts = monthly_rotation_strategy(universe, top_n=5)

Examples of key differences between composite ranking vs. pure return ranking

Weight adjustment suggestions

The following are weight allocation recommendations for different investment styles:

Practical considerations

First, the recommended rebalancing frequency for the composite ranking system is once a month. Too frequently (weekly) will lead to over-trading due to short-term noise, and friction costs will eat up excess returns. Too infrequently (quarterly) and important rotation opportunities may be missed. If the composite score of a certain target suddenly drops from the previous period to the later period in the middle of the month (for example, due to unexpected events), an exception can be made for early adjustment.

Second, when comparing across assets, it is important to note that the volatility structures of cryptocurrencies and traditional assets are very different. BTC’s RSI at 60 may be a relatively benign position, but stocks’ RSI at 60 is already on the high side. The dynamic weighting mechanism (adjusted according to VIX) alleviates this problem to a certain extent, but a more ideal approach is to rank cryptocurrencies as independent pools and then compare the final scores with traditional asset pools.

Third, the "strong buy" or "avoid" signals generated by the system are mechanical signals and should not completely replace human judgment. When the system tells you that a certain target ranks first, you should still check whether there are major fundamental events (financial reports, central bank decisions, geopolitics) about to happen, which cannot be foreseen by pure technical indicators. The greatest value of the composite ranking system is to provide a disciplined framework to ensure that you will not ignore objective market signals due to emotion.

Buffett's investment strategy

value investing

Buffett adheres to Benjamin Graham's "value investing" philosophy, looking for companies whose stock prices are lower than their intrinsic value, buying them when the market is undervalued, and holding them for a long time until their value is recognized by the market.

moat concept

Buffett prefers companies with "moats", that is, companies with lasting competitive advantages, such as brand influence, patented technology, network effects or unique business models, that can withstand threats from competitors.

long term holding

He emphasized that "the best investment period is forever" and believed that good companies should be held for a long time to allow the compound interest effect to exert its maximum power.

Stable finances

Buffett attaches great importance to the company's balance sheet and prefers companies with low debt and stable cash flow to reduce operating risks.

High quality management

He not only looks at financial reports, but also pays attention to the integrity and operational capabilities of management, and avoids handing over funds to undisciplined management teams.

Don’t blindly follow the market

Buffett's famous saying "Be fearful when others are greedy, and be greedy when others are fearful" illustrates his investment philosophy of operating against the trend and avoiding emotional chasing of highs and lows.

Concentrate investment

Although diversification of investments can reduce risks, Buffett advocates concentrating funds on the targets where you are most certain to obtain higher returns.

Cash flow and shareholder returns

He values ​​free cash flow and prefers companies that can reward shareholders through dividends or buybacks.

Avoid complex industries

Buffett typically avoids investing in industries he doesn't understand or that are too complex, such as high-risk startups or speculative technology stocks.

Patience and discipline

He believes that the key to successful investment lies in patiently waiting for the right opportunities and strictly following one's own investment principles.

Monte Carlo backtest

Concept Note

How it works

• Establish a probability distribution model based on historical returns or price changes.
• Randomly generate thousands or even tens of thousands of simulation paths.
• Perform strategy backtesting for each path and calculate final return, maximum drawdown, Sharpe ratio and other indicators.
• Analyze the distribution of results and assess the robustness and risk exposure of the strategy.

Application scenarios

• Test the performance of the strategy under extreme market conditions (such as plummets and violent fluctuations).
• A range of forecasted future returns.
• Evaluate the effectiveness of risk control mechanisms.
• Stress Testing of investment portfolios.

advantage

• It can simulate market situations that "have never happened" and test the risk resistance of strategies.
• The results are presented as probability distributions, which can quantify the strategy's winning rate and risk.
• Suitable for combination with complex strategies, such as leverage, grid, dynamic position management, etc.

shortcoming

• Simulation results depend on the assumed probability distribution and model accuracy.
• It is computationally intensive and requires a large number of samples and computing resources.
• There may be over-reliance on statistical models and neglect of actual market structural changes.

Common misunderstandings

• Use unreasonable distribution assumptions (such as ignoring fat tail effects).
• Handling fees, slippage and liquidity risk are not considered.
• Only look at the average return and ignore the tail loss risk.

Summarize

financial news

definition

Financial news refers to real-time information and news related to economic, financial, and market activities, which usually affects investor sentiment, market price changes, and policy expectations. It is an important part of investment analysis and is often used together with technical and fundamental aspects to judge market trends.

Main components

• Macroeconomic News:Contains data such as GDP, CPI, PPI, unemployment rate, interest rate decisions, money supply, etc.
• Industry and Corporate News:Corporate financial reports, merger and acquisition news, new product releases, and industrial policy adjustments.
• Policy and Regulatory News:Government fiscal policy, central bank monetary policy, trade agreements and sanctions.
• International events:Geopolitics, wars, epidemics, energy supply changes, exchange rate fluctuations.
• Market sentiment and expectations:Market rumors, investment institution forecasts, media reports and public opinion guidance.

The impact of financial news on the market

• stock market:Good news can stimulate buying and push up stock prices; bad news can trigger selling.
• Bond market:Changes in interest rate policy and inflation expectations will directly affect bond prices.
• Forex market:Monetary policy, trade data and political stability will influence exchange rate movements.
• Commodity market:Prices of energy, food, metals, etc. are strongly affected by supply and demand and geopolitics.

Common financial news sources

• Official agency:Such as data released by central banks, ministries of finance, and statistical bureaus of various countries.
• Media platform:Bloomberg, Reuters, CNBC, Reuters Chinese website, Economic Daily.
• Financial research institution:Reports from Morgan Stanley, Goldman Sachs, Nomura, Citigroup and others.
• Instant data service:TradingView, Investing.com, XQ Global Winner, Finance M Squared.

investment application

• Short-term trading:Take advantage of the volatility caused by news events to get in and out quickly.
• Mid- to long-term layout:Adjust investment allocations based on macro trends or policy directions.
• Risk management:Respond to market emergencies in advance through news monitoring.

Analysis suggestions

• To avoid being influenced by a single message, you need to observe the messageSource reliabilityandMarket reaction intensity。
• matchtechnical analysisandfundamental analysis, to confirm the actual impact of the news.
• pay attention to"Response to news in advance"Phenomenon: The market often reflects expectations before news is announced.

Major financial institutions and figures

1. United States

• Official agency:
  • Federal Reserve -federalreserve.gov
  • U.S. Department of the Treasury -home.treasury.gov
  • U.S. Bureau of Labor Statistics (BLS) -bls.gov
  • U.S. Department of Commerce, Bureau of Economic Analysis (BEA) -bea.gov
• Influencers and social accounts:
  • President of the United States Donald J. Trump-@realDonaldTrump（Truth Social）
  • Jerome Powell (Federal Reserve Chairman) - Usually not active on social platforms, but his speeches can influence global markets.
  • Elon Musk（Tesla、X、SpaceX CEO）－ @elonmusk（X/Twitter）
  • Cathie Wood（ARK Invest）－ @CathieDWood
  • U.S. White House Council of Economic Advisers (CEA)-@WhiteHouseCEA

2. China

• Official agency:
  • People's Bank of China (PBOC) -pbc.gov.cn
  • Ministry of Commerce -mofcom.gov.cn
  • Ministry of Finance -mof.gov.cn
  • National Bureau of Statistics -stats.gov.cn
  • China Securities Regulatory Commission (CSRC) -csrc.gov.cn
• Influencers and social accounts:
  • Yi Gang (former central bank governor) - mainly speaks through official press releases.
  • Hu Xijin (former editor-in-chief of Global Times, influential in market opinion) - Weibo account@Huxijin
  • Economic Daily and CCTV Finance official Weibo - provide policy direction and market trends.

3. Europe

• Official agency:
  • European Central Bank (ECB) -ecb.europa.eu
  • Eurostat -eurostat
  • Bank of England (BoE) -bankofengland.co.uk
• Influencers and social accounts:
  • Christine Lagarde (ECB President) -@Lagarde
  • Andrew Bailey (Governor of the Bank of England) - mostly spoke via BoE press release.

4. Japan

• Official agency:
  • Bank of Japan (BOJ) -boj.or.jp
  • Ministry of Finance of Japan -mof.go.jp
  • Statistics Bureau of the Ministry of Internal Affairs and Communications of Japan -stat.go.jp
• Influential people:
  • Kazuo Ueda (President of the Bank of Japan) - mainly releases policy direction through press conferences and BOJ announcements.

5. Taiwan

• Official agency:
  • central bank -cbc.gov.tw
  • Ministry of Finance -mof.gov.tw
  • Accounting General Office -dgbas.gov.tw
  • Securities and Futures Bureau/Financial Supervisory Commission -fsc.gov.tw
• Influencers and social accounts:
  • Central bank governor (e.g. Yang Jinlong) - Policy explanations are mostly seen at press conferences.
  • Financial media: Juheng.com, Economic Daily, Financial News, M Square, XQ Global Winner.

6. Other important sources around the world

• International organizations:
  • International Monetary Fund (IMF) -imf.org
  • World Bank -worldbank.org
  • Organization for Economic Cooperation and Development (OECD) -oecd.org
• Other market watchers:
  • Ray Dalio (Founder of Bridgewater Associates) -@RayDalio
  • Michael Burry (prototype character in "The Big Short") -@michaeljburry(Occasionally open accounts)
  • Warren Buffett - Although he does not have a social account, his annual shareholder letters and interviews are extremely influential.

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