Hong Kong's main stock market index, the HK50, fell to 24508 points on August 1, 2025, losing 1.07% from the previous session. Over the past month, the index has climbed 1.18% and is up 44.63% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Hong Kong. Hong Kong Stock Market Index (HK50) - values, historical data, forecasts and news - updated on August of 2025.

As of April 2025, the Hang Seng Index at the Hong Kong Exchange amounted to ********* points. After the outbreak of COVID-19, the index dropped as part of a broader Pan-Asian trend. However, by the end of 2020, when the pandemic situation stabilized in many countries and news about a vaccine rollout came out, the Hang Seng Index recovered and recorded significant increases every month. Index composition The Hang Seng Index is the most prominent indicator of stock performance on the Hong Kong Exchange. By including the 50 largest companies, the index represents the market movements of more than half of the bourse’s market capitalization. In addition to that, the Hang Seng Index has numerous smaller indices which mirror smaller industries or market sections. The Hang Seng Composite Index One example of a sub-index is the Hang Seng Composite Index. It reflects the performance of the top 95 percentile of the total market capitalization. The financial industry accounted for the largest share of companies included in the index, followed by the information technology sector. Prominent companies represented in the index are Tencent, AIA, and Meituan.

Interactive daily chart of the Hong Kong Hang Seng Composite stock market index back to 1986. Each data point represents the closing value for that trading day and is denominated in hong kong dollars (HKD). The current price is updated on an hourly basis with today's latest value.

Key information about Hong Kong SAR (China) Hang Seng

• Hong Kong SAR (China) Hang Seng closed at 22,941.3 points in Feb 2025, compared with 20,225.1 points at the previous month end
• Hong Kong SAR (China) Equity Market Index: Month End: Hang Seng data is updated monthly, available from Jul 1964 to Feb 2025, with an average number of 8,846.5 points
• The data reached an all-time high of 32,887.3 points in Jan 2018 and a record low of 58.6 points in Aug 1967

• In the latest reports, Hang Seng recorded a daily P/E ratio of 13.1 in Mar 2025

The statistic shows the annual development of the Hang Seng index from 1986 to 2024. The Hang Seng index reflects the performance of the largest stocks traded on the Hong Kong Stock Exchange. The year value of the Hang Seng index amounted to 20,059.95 by the end of 2023.

Hong Kong Total Return Index: Hang Seng Index data was reported at 74,068.820 02Jan1990=2838.07 in Nov 2018. This records an increase from the previous number of 69,722.850 02Jan1990=2838.07 for Oct 2018. Hong Kong Total Return Index: Hang Seng Index data is updated monthly, averaging 23,979.930 02Jan1990=2838.07 from Jan 1990 (Median) to Nov 2018, with 347 observations. The data reached an all-time high of 88,755.560 02Jan1990=2838.07 in Jan 2018 and a record low of 2,753.510 02Jan1990=2838.07 in Jan 1990. Hong Kong Total Return Index: Hang Seng Index data remains active status in CEIC and is reported by Hong Kong Exchanges and Clearing Limited. The data is categorized under Global Database’s Hong Kong SAR – Table HK.Z001: Main Board: Stock Market Index.

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.

Hang Seng Index: The Future of Hong Kong?

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

Prices for Hong Kong Stock Market Index (HK50) including live quotes, historical charts and news. Hong Kong Stock Market Index (HK50) was last updated by Trading Economics this August 2 of 2025.

Hong Kong Index: Hang Seng Properties data was reported at 36,792.180 13Jan1984=975.47 in Nov 2018. This records an increase from the previous number of 33,818.020 13Jan1984=975.47 for Oct 2018. Hong Kong Index: Hang Seng Properties data is updated monthly, averaging 16,965.450 13Jan1984=975.47 from Jul 1984 (Median) to Nov 2018, with 413 observations. The data reached an all-time high of 43,637.620 13Jan1984=975.47 in Jan 2018 and a record low of 807.120 13Jan1984=975.47 in Jul 1984. Hong Kong Index: Hang Seng Properties data remains active status in CEIC and is reported by Hong Kong Exchanges and Clearing Limited. The data is categorized under Global Database’s Hong Kong SAR – Table HK.Z001: Main Board: Stock Market Index.

Hong Kong Index: Hang Seng China 50 Index data was reported at 7,587.620 NA in Nov 2018. This records an increase from the previous number of 7,357.360 NA for Oct 2018. Hong Kong Index: Hang Seng China 50 Index data is updated monthly, averaging 5,569.140 NA from Jan 2000 (Median) to Nov 2018, with 227 observations. The data reached an all-time high of 10,962.480 NA in Oct 2007 and a record low of 1,537.860 NA in Dec 2002. Hong Kong Index: Hang Seng China 50 Index data remains active status in CEIC and is reported by Hong Kong Exchanges and Clearing Limited. The data is categorized under Global Database’s Hong Kong SAR – Table HK.Z001: Main Board: Stock Market Index.

Predictions for Hang Seng index indicate a possible continuation of the recent bullish trend. However, there is also the risk of a pullback or consolidation phase before the uptrend resumes. The risk of a pullback increases if the index fails to hold above a key support level.

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.

Will Hang Seng Soar Higher?

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.

Hang Seng Index: Uptrend or U-Turn?

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

Hong Kong SAR (China) Hong Kong Stock Exchange: Index: Total Return: Hang Seng China (Hong Kong Listed) 25 Index data was reported at 19,406.950 NA in Apr 2025. This records a decrease from the previous number of 20,408.380 NA for Mar 2025. Hong Kong SAR (China) Hong Kong Stock Exchange: Index: Total Return: Hang Seng China (Hong Kong Listed) 25 Index data is updated monthly, averaging 14,802.300 NA from Jun 2013 (Median) to Apr 2025, with 143 observations. The data reached an all-time high of 20,571.990 NA in Jan 2018 and a record low of 10,167.910 NA in Oct 2022. Hong Kong SAR (China) Hong Kong Stock Exchange: Index: Total Return: Hang Seng China (Hong Kong Listed) 25 Index data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s Hong Kong SAR (China) – Table HK.EDI.SE: Hong Kong Stock Exchange: Monthly.

In April 2025, the value of the Hang Seng China Enterprise Index amounted to ***** points. The index aims to reflect the performance of mainland Chinese securities that are listed on the Hong Kong Exchange. It includes companies such as Tencent, Alibaba, and Ping An.

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.

Hang Seng Index: Where is the Market Headed?

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

Hong Kong Index: Hang Seng Composite: HK LargeCap data was reported at 2,196.100 03Jan2000=2000 in Nov 2018. This records an increase from the previous number of 2,058.410 03Jan2000=2000 for Oct 2018. Hong Kong Index: Hang Seng Composite: HK LargeCap data is updated monthly, averaging 1,813.350 03Jan2000=2000 from Jan 2000 (Median) to Nov 2018, with 227 observations. The data reached an all-time high of 2,760.710 03Jan2000=2000 in Jan 2018 and a record low of 1,026.610 03Jan2000=2000 in Mar 2009. Hong Kong Index: Hang Seng Composite: HK LargeCap data remains active status in CEIC and is reported by Hong Kong Exchanges and Clearing Limited. The data is categorized under Global Database’s Hong Kong SAR – Table HK.Z001: Main Board: Stock Market Index.

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.

Hang Seng Index Forecast: Mixed Outlook

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.

When to Sell and When to Hold Hang Seng Index Stock

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

Hong Kong Index: Hang Seng Composite: HK SmallCap data was reported at 1,972.670 03Jan2000=2000 in Nov 2018. This records an increase from the previous number of 1,871.150 03Jan2000=2000 for Oct 2018. Hong Kong Index: Hang Seng Composite: HK SmallCap data is updated monthly, averaging 2,036.670 03Jan2000=2000 from Jan 2000 (Median) to Nov 2018, with 227 observations. The data reached an all-time high of 3,454.250 03Jan2000=2000 in Oct 2007 and a record low of 878.110 03Jan2000=2000 in Sep 2002. Hong Kong Index: Hang Seng Composite: HK SmallCap data remains active status in CEIC and is reported by Hong Kong Exchanges and Clearing Limited. The data is categorized under Global Database’s Hong Kong SAR – Table HK.Z001: Main Board: Stock Market Index.