Key information about Taiwan P/E ratio

• Taiwan All Listed Stocks recorded a monthly P/E ratio of 20.460 on Mar 2025, compared with 21.750 from the previous month.
• Taiwan All Listed Stocks P/E ratio is updated monthly, with historical data available from May 1989 to Feb 2025.
• The P/E ratio reached an all-time high of 124.720 in Jan 2010 and a record low of 9.050 in Jan 2009.
• Taiwan Stock Exchange Corporation provides monthly P/E Ratio.

In the latest reports, Month End closed at 23,053.180 points in Feb 2025.

Taiwan TWSE: PE Ratio: Electronics data was reported at 15.040 NA in Nov 2018. This records a decrease from the previous number of 15.070 NA for Oct 2018. Taiwan TWSE: PE Ratio: Electronics data is updated monthly, averaging 18.060 NA from Aug 1995 (Median) to Nov 2018, with 247 observations. The data reached an all-time high of 87.090 NA in Jun 1999 and a record low of 8.940 NA in Jul 1996. Taiwan TWSE: PE Ratio: Electronics data remains active status in CEIC and is reported by Taiwan Stock Exchange Corporation. The data is categorized under Global Database’s Taiwan – Table TW.Z003: Taiwan Stock Exchange (TWSE): Price Earnings Ratio.

Key information about Taiwan Market Capitalization: % of GDP

• Taiwan Market Capitalization accounted for 289.2 % of its Nominal GDP in Dec 2024, compared with a percentage of 240.9 % in the previous year
• Taiwan Market Capitalization: % Nominal GDP is updated yearly, available from Dec 1962 to Dec 2024
• The data reached an all-time high of 289.2 % in Dec 2024 and a record low of 6.1 % in Dec 1968

CEIC calculates Market Capitalization as % of Nominal GDP from annual Market Capitalization and annual Nominal GDP. Market Capitalization is calculated as the sum of the Market Capitalizations of Common and Preferred Stocks. Taiwan Stock Exchange Corporation provides Market Capitalization in local currency. The Directorate-General of Budget, Accounting and Statistics, Executive Yuan provides Nominal GDP in local currency. Market Capitalization as % of Nominal GDP prior to 1981 is calculated from Nominal GDP with reference year 2016.


Further information about Taiwan Market Capitalization: % of GDP

• In the latest reports, All Listed Stocks recorded a monthly P/E ratio of 21.8 in Jan 2025
• Month End closed at 23,525.4 points in Jan 2025

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Taiwan Weighted Index: A Reliable Indicator of Economic Health?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

How do you predict if a stock will go up or down? (Taiwan Weighted Index Stock Prediction)

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Taiwan Consumer Price Index (CPI): Kaohsiung City: Frequency of Purchase: >=1 per Quarter data was reported at 104.630 2016=100 in Jun 2018. This records an increase from the previous number of 103.170 2016=100 for May 2018. Taiwan Consumer Price Index (CPI): Kaohsiung City: Frequency of Purchase: >=1 per Quarter data is updated monthly, averaging 101.540 2016=100 from Jan 2017 (Median) to Jun 2018, with 18 observations. The data reached an all-time high of 104.630 2016=100 in Jun 2018 and a record low of 98.130 2016=100 in Apr 2017. Taiwan Consumer Price Index (CPI): Kaohsiung City: Frequency of Purchase: >=1 per Quarter data remains active status in CEIC and is reported by Department of Budget, Accounting and Statistics, Kaohsiung City Government. The data is categorized under Global Database’s Taiwan – Table TW.I008: Consumer Price Index: 2016=100: Kaohsiung City.