The rolling stock market was estimated to be worth just under **** billion U.S. dollars in 2023, with Asia-Oceania accounting for the largest share. Rolling stock market in Asia-Pacific Among the largest and fastest-growing countries within the Asia-Pacific region for rolling stock are India and China, with Indian Railways and CRRC ranked as key market players for this region. Reasons contributing to expansion in countries such as India include a growing population and a considerable number of migrant workers who rely on rail as a means of commuting. Back in 2020, there were approximately *** million migrant workers in China. Driving innovation in the sector One of the world’s leading rolling stock manufacturers, CRRC, reported investments of over ** billion Chinese yuan in its research and development activity in the 2022 financial year. As the company continues to develop and manufacture innovative technologies, such as electric and hybrid rail systems, CRRC has started to address concerns about sustainability and emissions while ensuring that it maintains a technological advantage over its competitors in the global market.
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Stock market return (%, year-on-year) in United States was reported at 32.65 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.
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The main stock market index of United States, the US500, fell to 6238 points on July 4, 2025, losing 0.65% from the previous session. Over the past month, the index has climbed 5.04% and is up 12.06% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.
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View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.
As of the end of 2023, the total market cap of the Spanish Stock Exchange amounted to just over 1.2 trillion euros, an increase compared to the previous year. The market capitalization, or market cap, is one measure of calculating the value of a stock or group of stocks. It is found by computing the number of shares times the price per share.
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The main stock market index of United States, the US500, fell to 6226 points on July 14, 2025, losing 0.54% from the previous session. Over the past month, the index has climbed 3.20% and is up 10.56% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.
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Stock Market Tweets Data
Overview
This dataset is the same as the Stock Market Tweets Data on IEEE by Bruno Taborda.
Data Description
This dataset contains 943,672 tweets collected between April 9 and July 16, 2020, using the S&P 500 tag (#SPX500), the references to the top 25 companies in the S&P 500 index, and the Bloomberg tag (#stocks).
Dataset Structure
created_at: The exact time this tweet was posted. text: The text of the tweet, providing… See the full description on the dataset page: https://huggingface.co/datasets/StephanAkkerman/stock-market-tweets-data.
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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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
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This dataset provides detailed historical data on the US stock market, covering the period from 21st November 2023 to 2nd February 2024. It includes daily performance metrics for major stocks and indices, enabling investors, analysts, and researchers to study short-term market trends, fluctuations, and patterns.
The dataset contains the following key attributes for each trading day:
Date: The trading date.
Ticker: Stock ticker symbol (e.g., AAPL for Apple, MSFT for Microsoft).
Open Price: The price at which the stock opened for trading.
Close Price: The price at which the stock closed for trading . High Price: The highest price reached during the trading session.
Low Price: The lowest price reached during the trading session.
Adjusted Close Price: The closing price adjusted for splits and dividend payouts.
Trading Volume: The total number of shares traded on that day.
Time Period: Covers daily data for over two months of trading activity.
Market Scope: Includes data from a diverse set of stocks, industries, and sectors, reflecting the broader US market trends.
Indices and Major Stocks: Tracks key indices (e.g., S&P 500, NASDAQ) and major stocks across various sectors .
Analyzing short-term market performance trends. Developing trading strategies or backtesting investment models. Exploring the impact of macroeconomic events on stock performance. Studying sector-wise performance in the US stock market.
The data has been sourced from publicly available market records, ensuring reliability and accuracy. Each data point represents an official trading record from the respective exchange.
The dataset is intended for educational, analytical, and research purposes only. Users should be mindful of potential market anomalies or external factors influencing data during this time frame.
Special thanks to the organizations and platforms that make financial market data accessible for analysis and research.
This statistic shows the total trading value of stocks on Taiwan Stock Exchange market from 2013 to 2023. In 2023, the total stock trading value on Taiwan Stock Exchange market reached around ** trillion New Taiwan dollars.
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Interactive chart illustrating the performance of the Dow Jones Industrial Average (DJIA) market index over the last ten years. Each point of the stock market graph is represented by the daily closing price for the DJIA. Historical data can be downloaded via the red button on the upper left corner of the chart.
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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.
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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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
In 2024, ** percent of adults in the United States invested in the stock market. This figure has remained steady over the last few years, and is still below the levels before the Great Recession, when it peaked in 2007 at ** percent. What is the stock market? The stock market can be defined as a group of stock exchanges, where investors can buy shares in a publicly traded company. In more recent years, it is estimated an increasing number of Americans are using neobrokers, making stock trading more accessible to investors. Other investments A significant number of people think stocks and bonds are the safest investments, while others point to real estate, gold, bonds, or a savings account. Since witnessing the significant one-day losses in the stock market during the Financial Crisis, many investors were turning towards these alternatives in hopes for more stability, particularly for investments with longer maturities. This could explain the decrease in this statistic since 2007. Nevertheless, some speculators enjoy chasing the short-run fluctuations, and others see value in choosing particular stocks.
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Stock market return (%, year-on-year) in Mexico was reported at 26.44 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Mexico - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.
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The Global Rolling Stock Market is expected to demonstrate a CAGR of approximately 4.13% during the period 2023-2028, as stated by MarkNtel Advisors.
The value of the DJIA index amounted to ********* at the end of March 2025, up from ********* at the end of March 2020. Global panic about the coronavirus epidemic caused the drop in March 2020, which was the worst drop since the collapse of Lehman Brothers in 2008. Dow Jones Industrial Average index – additional information The Dow Jones Industrial Average index is a price-weighted average of 30 of the largest American publicly traded companies on New York Stock Exchange and NASDAQ, and includes companies like Goldman Sachs, IBM and Walt Disney. This index is considered to be a barometer of the state of the American economy. DJIA index was created in 1986 by Charles Dow. Along with the NASDAQ 100 and S&P 500 indices, it is amongst the most well-known and used stock indexes in the world. The year that the 2018 financial crisis unfolded was one of the worst years of the Dow. It was also in 2008 that some of the largest ever recorded losses of the Dow Jones Index based on single-day points were registered. On September 29, 2008, for instance, the Dow had a loss of ****** points, one of the largest single-day losses of all times. The best years in the history of the index still are 1915, when the index value increased by ***** percent in one year, and 1933, year when the index registered a growth of ***** percent.
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Stock market return (%, year-on-year) in United Kingdom was reported at 14.38 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. United Kingdom - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.
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Stock market return (%, year-on-year) in Estonia was reported at 43.16 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Estonia - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.
In 2023, the number of shares issued at China's stock markets amounted to over **************. As the country's financial system developed, the number of issued shares increased as well. The number of shares had more than doubled since 2013.
The rolling stock market was estimated to be worth just under **** billion U.S. dollars in 2023, with Asia-Oceania accounting for the largest share. Rolling stock market in Asia-Pacific Among the largest and fastest-growing countries within the Asia-Pacific region for rolling stock are India and China, with Indian Railways and CRRC ranked as key market players for this region. Reasons contributing to expansion in countries such as India include a growing population and a considerable number of migrant workers who rely on rail as a means of commuting. Back in 2020, there were approximately *** million migrant workers in China. Driving innovation in the sector One of the world’s leading rolling stock manufacturers, CRRC, reported investments of over ** billion Chinese yuan in its research and development activity in the 2022 financial year. As the company continues to develop and manufacture innovative technologies, such as electric and hybrid rail systems, CRRC has started to address concerns about sustainability and emissions while ensuring that it maintains a technological advantage over its competitors in the global market.