China's main stock market index, the SHANGHAI, fell to 3898 points on December 2, 2025, losing 0.42% from the previous session. Over the past month, the index has declined 1.98%, though it remains 15.36% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from China. China Shanghai Composite Stock Market Index - values, historical data, forecasts and news - updated on December of 2025.

Prices for China Stock Market Index (CH50) including live quotes, historical charts and news. China Stock Market Index (CH50) was last updated by Trading Economics this December 2 of 2025.

Dataset

This dataset was created by junislee

Contents

Hong Kong's main stock market index, the HK50, rose to 26095 points on December 2, 2025, gaining 0.24% from the previous session. Over the past month, the index has declined 0.24%, though it remains 32.15% higher than a year ago, 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 December of 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.

A50: China's Stock Market Enigma

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

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 2037 companies listed on the Shanghai Stock Exchange (XSHG) in China. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

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Top 5 used data fields in the End-of-Day Pricing Dataset for China:

1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

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Top 5 financial instruments with End-of-Day Pricing Data in China:

Shanghai Stock Exchange (SSE) Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Shanghai Stock Exchange. This index provides an overview of the overall market performance in China.

Shenzhen Stock Exchange (SZSE) Domestic Company Index: The index that tracks the performance of domestic companies listed on the Shenzhen Stock Exchange. This index reflects the performance of companies listed on the technology-focused exchange.

Company A: A prominent Chinese company with diversified operations across various sectors, such as technology, finance, or manufacturing. This company's stock is widely traded on either the Shanghai Stock Exchange or the Shenzhen Stock Exchange.

Company B: A leading financial institution in China, offering banking, insurance, or investment services. This company's stock is actively traded on one of the major stock exchanges in China.

Company C: A major player in the Chinese agriculture sector or other industries, involved in the production and distribution of goods or services. This company's stock is listed and actively traded on either the Shanghai Stock Exchange or the Shenzhen Stock Exchange.

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If you're interested in accessing Techsalerator's End-of-Day Pricing Data for China, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

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Data fields included:

Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

Q&A:

1. How much does the End-of-Day Pricing Data cost in China ?

The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

1. How complete is the End-of-Day Pricing Data coverage in China?

Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on China exchanges.

1. How does Techsalerator collect this data?

Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. While the dataset focuses on Botswana, Techsalerator also provides data for other countries and international markets.

1. How do I pay for this dataset?

T...

Key vaccine stocks like Moderna, Pfizer, and Novavax are rising as new coronavirus concerns emerge in China, highlighting a mixed day in the stock market with travel and tech sectors facing declines.

Prices for Shanghai Stock Exchange Composite Index including live quotes, historical charts and news. Shanghai Stock Exchange Composite Index was last updated by Trading Economics this December 2 of 2025.

The stock market is an important part of the capital market, and the research on the price fluctuation of the stock market has always been a hot topic for scholars. As a dynamic and complex system, the stock market is affected by various factors. However, with the development of information technology, information presents multisource and heterogeneous characteristics, and the transmission speed and mode of information have changed greatly. The explanation and influence of multi-source and heterogeneous information on stock market price fluctuations need further study. In this paper, a graph fusion and embedding method for multi-source heterogeneous information of Chinese stock market is established. Relational dimension information is introduced to realize the effective fusion of multi-source heterogeneous data information. A multi-attention graph neural network based on nodes and semantics is constructed to mine the implied semantics of fusion graph data and capture the influence of multi-source heterogeneous information on stock market price fluctuations. Experiments show that the proposed multi-source heterogeneous information fusion methods is superior to tensor or vector fusion method, and the constructed multi-attention diagram neural network has a better ability to explain stock market price fluctuations.

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 2597 companies listed on the Hong Kong Stock Exchange (XHKG) in Hong Kong. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

Top 5 used data fields in the End-of-Day Pricing Dataset for Hong Kong:

1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

‍

Top 5 financial instruments with End-of-Day Pricing Data in Hong Kong:

Hang Seng Index: The main index that tracks the performance of major companies listed on the Hong Kong Stock Exchange. This index provides an overview of the overall market performance in Hong Kong.

Hang Seng China Enterprises Index (HSCEI): The index that tracks the performance of mainland Chinese companies listed on the Hong Kong Stock Exchange. This index reflects the performance of Chinese companies with significant operations in Hong Kong.

Company A: A prominent Hong Kong-based company with diversified operations across various sectors, such as finance, real estate, or retail. This company's stock is widely traded on the Hong Kong Stock Exchange.

Company B: A leading financial institution in Hong Kong, offering banking, insurance, or investment services. This company's stock is actively traded on the Hong Kong Stock Exchange.

Company C: A major player in the Hong Kong property development or other industries, involved in the construction and management of real estate projects. This company's stock is listed and actively traded on the Hong Kong Stock Exchange.

‍

If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Hong Kong, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

‍

Data fields included:

Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

Q&A:

1. How much does the End-of-Day Pricing Data cost in Hong Kong ?

The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

1. How complete is the End-of-Day Pricing Data coverage in Hong Kong?

Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Hong Kong exchanges.

1. How does Techsalerator collect this data?

Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. While the dataset focuses on Botswana, Techsalerator also provides data for other countries and international markets.

1. How do I pay for this dataset?

Techsalerator accepts various payment methods, including credit cards, direct tr...

Post-Christmas, Asian markets rise as retail and tourism stocks thrive, with gains in Japan's Nikkei 225 and increased oil prices boosting the momentum.

Media information plays an essential role in the stock market. Recent financial research has verified that media information could shock stock price by influencing investors’ expectation. Now, a new type of interactive media, called Digital Interactive Media (DIM), is popular in Chinese stock market and becomes the main channel for investors to understand listed companies. Unlike general news media or investor forums, DIM enables direct interaction between listed companies and investors. In the modern society where digital economy is booming, media information would largely affect investors’ decisions. Therefore, it is urgent to use natural language processing (NLP) technology to deconstruct the massive questions and answers (Q&A) interactive information in DIM and extract valuable factors that affect stock prices and stock performances to explore the influence mechanism of digital interactive information on stock performances. This paper firstly uses web crawling technology to obtain approximately 110000 Q&A text information from the digital interactive platform (‘Panoramic Network’) from 2015 to 2021. Then we use big data text analysis technology and emotional quantification technology to extract valuable influencing factors from the massive text. A Multiple Linear Regression (MLR) model was created to explore specific influence mechanism of digital interactive information on stock price performance. The empirical results show that the emotions implicit in investors’ questions do not significantly impact stock performance. However, the emotions and attitudes of the answers by listed companies can significantly affect corresponding stock prices, which indirectly confirms the Proximate Cause Effect of behavioral finance. This effect is particularly evident in the stock prices on the current trading day and the next trading day. In the Robustness Test, this paper replaces dependent variable and adds relevant control variables, and the conclusion remains valid. In the Endogeneity Test, this paper selects sample data before the launch of Panorama Network in 2014 as a comparison, and uses a Difference-in-Difference (DID) model to prove the significant impact of the launch of Panorama Network on Chinese stock market. In the Heterogeneity Test, the paper classifies the market value, region, and industry of listed companies and regressed the sub samples, once again confirming the reliability of the empirical conclusions. The results of Robustness Test, Endogeneity Test, and Heterogeneity Test conducted in this paper all support empirical conclusions.

Discover the latest trends in the Chinese market for toilet paper, napkins, towels, and tissue stock. Learn about projected growth rates and market volume and value forecasts for the period from 2024 to 2035.

Stock Analysis Software Market Outlook

The global stock analysis software market size was valued at approximately USD 1.2 billion in 2023 and is projected to reach around USD 3.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 12.5% during the forecast period. The growth of this market is driven by the increasing adoption of advanced analytics tools by individual investors and financial institutions to make informed investment decisions. The rising demand for automated trading systems and the integration of artificial intelligence (AI) and machine learning (ML) in stock analysis software are significant growth factors contributing to the market expansion.

One of the primary growth factors for the stock analysis software market is the increasing complexity and volume of financial data. With the exponential growth of data from various sources such as social media, news articles, and financial statements, investors and financial analysts require sophisticated tools to process and interpret this information accurately. Stock analysis software equipped with AI and ML algorithms can analyze vast datasets in real-time, providing valuable insights and predictive analytics that enhance investment strategies. Moreover, the growing trend of algorithmic trading, which relies heavily on high-speed data processing and automated decision-making, is further propelling the market growth.

Another crucial growth driver is the rising awareness and adoption of stock analysis software among individual investors. As more individuals seek to actively manage their investment portfolios, there is a growing demand for user-friendly and cost-effective stock analysis tools that offer comprehensive market analysis, technical indicators, and personalized investment recommendations. The proliferation of mobile applications and the increasing accessibility of cloud-based stock analysis solutions have made it easier for retail investors to access advanced analytical tools, thereby contributing to market expansion.

The integration of innovative technologies such as natural language processing (NLP) and sentiment analysis into stock analysis software is also a significant growth factor. These technologies enable the software to interpret and analyze unstructured data from news articles, social media, and other textual sources to gauge market sentiment and predict stock price movements. This capability is particularly valuable in today's fast-paced financial markets, where sentiment and news events can have a substantial impact on stock prices. The continuous advancements in AI and NLP technologies are expected to drive further innovations and improvements in stock analysis software, thereby boosting market growth.

In the evolving landscape of financial technology, Investor Relations Tools have become indispensable for companies seeking to maintain transparent and effective communication with their stakeholders. These tools facilitate seamless interaction between companies and their investors, providing real-time updates, financial reports, and strategic insights. By leveraging these tools, companies can enhance their investor engagement strategies, build trust, and foster long-term relationships with their shareholders. The integration of advanced analytics and AI-driven insights into Investor Relations Tools further empowers companies to tailor their communication strategies, ensuring that they meet the diverse needs of their investor base. As the demand for transparency and accountability in financial markets continues to grow, the adoption of sophisticated Investor Relations Tools is expected to rise, playing a crucial role in the broader ecosystem of stock analysis software.

From a regional perspective, North America is anticipated to hold the largest market share due to the high concentration of financial institutions, brokerage firms, and individual investors in the region. The presence of key market players and the early adoption of advanced technologies also contribute to the dominant position of North America in the global stock analysis software market. Additionally, the Asia Pacific region is expected to witness significant growth during the forecast period, driven by the increasing number of retail investors, rapid economic development, and the growing financial markets in countries such as China and India.

Component Analysis

This study investigates the influence of investor sentiment on the Chinese stock market during the COVID-19 pandemic, using an event study analysis to examine data from December 2019 to December 2022. It aims to explore how investor sentiment, driven by news, social media, and economic uncertainties, has affected stock market performance during the pandemic. Data from 2005 to 2022 have been used to analyze abnormal and cumulative returns across key pandemic-related events, such as government interventions, lockdowns, and vaccine rollouts. The results show significant fluctuations in market returns driven by changes in sentiment. Positive sentiment, linked to government stimulus measures and vaccine announcements, led to positive market reactions, while negative sentiment, stemming from pandemic uncertainty, triggered market downturns. The study contributes to understanding the role of sentiment in market volatility, particularly in an emerging market like China, during periods of crisis. Accordingly, the study suggests multiple policy implications for policy makers.

The daily climate change news indices for China from 2010 to 2024 are provided.Initially, based on nearly 4.9 million news articles published by nine Chinese newspapers (People's Daily, Guangming Daily, Xinhua Daily Telegraph, China News Service, Science and Technology Daily, Science Times, China Energy News, China Environment News, and Global Times) from January 2010 to November 2022, the indices were constructed using the Latent Dirichlet Allocation (LDA) model, encompassing five distinct themes: natural disasters, climate governance, energy transition, climate cooperation, and climate communication.Subsequently, the indices were updated to 2024 utilizing a naive Bayes model.Cite: Ma, D., Zhang, Y., Ji, Q., Zhao, W. L., & Zhai, P. (2024). Heterogeneous impacts of climate change news on China's financial markets. International Review of Financial Analysis, 91, 103007.

Peoples Insurance Company of China reported CNY296.76B in Market Capitalization this December of 2025, considering the latest stock price and the number of outstanding shares.Data for Peoples Insurance Company of China | 601319 - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last December in 2025.

The daily climate change news indices for China from 2010 to 2023 are provided. Initially, based on nearly 4.9 million news articles published by nine Chinese newspapers (People's Daily, Guangming Daily, Xinhua Daily Telegraph, China News Service, Science and Technology Daily, Science Times, China Energy News, China Environment News, and Global Times) from January 2010 to November 2022, the indices were constructed using the Latent Dirichlet Allocation (LDA) model, encompassing five distinct themes: natural disasters, climate governance, energy transition, climate cooperation, and climate communication. Subsequently, the indices were updated to 2023 utilizing a naive Bayes model.Cite: Ma, D., Zhang, Y., Ji, Q., Zhao, W. L., & Zhai, P. (2024). Heterogeneous impacts of climate change news on China's financial markets. International Review of Financial Analysis, 91, 103007.

The statistic shows the financial news share in newspaper retail market in China from 2013 to 2015. As of 2015, financial newspapers accounted for around ***** percent of China's newspaper retail market.

Discover the projections for the toilet paper, facial tissue, towel, and similar paper market in China over the next decade. With an anticipated growth in both volume and value, find out how the market is expected to reach 18M tons and $23.2B by the end of 2035.