100+ datasets found
  1. T

    United States Stock Market Index Data

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +11more
    csv, excel, json, xml
    + more versions
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    TRADING ECONOMICS (2025). United States Stock Market Index Data [Dataset]. https://tradingeconomics.com/united-states/stock-market
    Explore at:
    excel, xml, json, csvAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 3, 1928 - Oct 7, 2025
    Area covered
    United States
    Description

    The main stock market index of United States, the US500, fell to 6738 points on October 7, 2025, losing 0.04% from the previous session. Over the past month, the index has climbed 3.73% and is up 17.15% 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 October of 2025.

  2. T

    United States Stock Market Index Data

    • tradingeconomics.com
    • ru.tradingeconomics.com
    • +5more
    csv, excel, json, xml
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    TRADING ECONOMICS (2025). United States Stock Market Index Data [Dataset]. https://tradingeconomics.com/united-states/stock-market??sa=u&ei=ffhqvnvmn5dloatmoocabw&ved=0cjmbebywfq&usg=afqjcngzbcc8p0owixmdsdjcu_endviwgg
    Explore at:
    csv, json, excel, xmlAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 3, 1928 - Oct 6, 2025
    Area covered
    United States
    Description

    The main stock market index of United States, the US500, rose to 6745 points on October 6, 2025, gaining 0.43% from the previous session. Over the past month, the index has climbed 3.85% and is up 18.42% 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 October of 2025.

  3. Stock Market Dataset for August 2025

    • kaggle.com
    Updated Aug 7, 2025
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    Kshitij Saini (2025). Stock Market Dataset for August 2025 [Dataset]. https://www.kaggle.com/datasets/kshitijsaini121/stock-market-prediction-for-july-2025-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 7, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Kshitij Saini
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Dataset Overview

    This dataset contains comprehensive stock market data for June 2025, capturing daily trading information across multiple companies and sectors. The dataset represents a substantial collection of market data with detailed financial metrics and trading statistics.

    Basic Dataset Information

    • Time Period: June 1-21, 2025 (21 trading days)
    • Total Records: Approximately 11,600+ entries
    • Companies Covered: 500+ unique stocks
    • Data Type: Daily stock market trading data with fundamental metrics

    Markdown Table Format

    Column NameData TypeDescriptionExample Values
    DateDateTrading date in DD-MM-YYYY format01-06-2025, 02-06-2025
    TickerStringStock ticker symbol (3-4 characters)AAPL, GOOGL, TSLA
    Open PriceFloatOpening price of the stock34.92, 206.5, 125.1

    Dataset Information Table

    Dataset Overview

    AttributeDetails
    Dataset NameStock Market Data - June 2025
    File FormatCSV
    File Size~2.5 MB
    Number of Records11,600+
    Number of Features13
    Time PeriodJune 1-21, 2025

    Data Schema

    Column NameData TypeDescriptionExample Values
    DateDateTrading date in DD-MM-YYYY format01-06-2025, 02-06-2025
    TickerStringStock ticker symbol (3-4 characters)AAPL, GOOGL, TSLA, SLH
    Open PriceFloatOpening price of the stock34.92, 206.5, 125.1
    Close PriceFloatClosing price of the stock34.53, 208.45, 124.03
    High PriceFloatHighest price during the trading day35.22, 210.51, 127.4
    Low PriceFloatLowest price during the trading day34.38, 205.12, 121.77
    Volume TradedIntegerNumber of shares traded2,966,611, 1,658,738
    Market CapFloatMarket capitalization in dollars57,381,363,838.88
    PE RatioFloatPrice-to-Earnings ratio29.63, 13.03, 29.19
    Dividend YieldFloatDividend yield percentage2.85, 2.73, 2.64
    EPSFloatEarnings per Share1.17, 16.0, 4.25
    52 Week HighFloatHighest price in the last 52 weeks39.39, 227.38, 138.35
    52 Week LowFloatLowest price in the last 52 weeks28.44, 136.79, 100.69
    SectorStringIndustry sector classificationIndustrials, Energy, Healthcare

    Market Capitalization Tiers

    • Mega Cap (>$1T): 6 companies (AAPL, MSFT, NVDA, AMZN, GOOGL, META)
    • Large Cap ($200B-$1T): 28 companies
    • Mid Cap ($50B-$200B): 47 companies

    Key Market Characteristics

    Price Volatility by Sector

    • Technology: Higher volatility (±3.5% daily range)
    • Energy: High volatility (±4.0% daily range)
    • Utilities: Lower volatility (±1.5% daily range)
    • Healthcare/Financials: Moderate volatility (±2.5% daily range)

    Trading Volume Patterns

    • Mega Cap: 25M - 90M shares daily
    • Large Cap: 8M - 35M shares daily
    • Mid Cap: 2M - 15M shares daily
    • Small Cap: 500K - 5M shares daily

    Financial Metrics Distribution

    • Average P/E Ratio: 25.9 (market-wide)
    • Average Dividend Yield: 1.25%
    • Price Range: $19 (T) to $3,850 (BKNG)
    • EPS Range: $1.50 to $70.00

    Notable Market Features

    High-Value Stocks

    • BKNG (Booking Holdings): $3,650-$3,850 range
    • AVGO (Broadcom): $1,650-$1,750 range
    • REGN (Regeneron): $1,050-$1,150 range
    • LLY (Eli Lilly): $920-$980 range

    High-Dividend Yielders

    • T (AT&T): 7.1% dividend yield
    • VZ (Verizon): 6.2% dividend yield
    • PFE (Pfizer): 5.8% dividend yield

    Growth & Technology Leaders

    • NOW (ServiceNow): P/E ratio of 85
    • NVDA (NVIDIA): P/E ratio of 45
    • TSLA (Tesla): P/E ratio of 55

    Data Quality & Realism Features

    ✅ Authentic Price Ranges: Based on realistic 2025 market projections ✅ Sector-Appropriate Volatility: Different volatility patterns by industry ✅ Correlated Metrics: P/E ratios, dividend yields, and EPS align with market caps ✅ Realistic Trading Volumes: Volume scaled appropriately to market cap ✅ Temporal Consistency: Logical price progression over 53-day period ✅ Market Cap Accuracy: Daily fluctuations reflect actual price movements

    Intended Use Cases

    • Financial Analysis & Modeling: Portfolio optimization, risk assessment
    • Machine Learning Applications: Predictive modeling, algorithmic trading
    • Educational Purposes: Finance courses, data science training
    • Algorithm Development: Backtesting trading strategies
    • Market Research: Sector analysis, correlation studies
    • Visualization Projects: Interactive dashboards, market trend analysis

    This dataset provides a comprehensive foundation for quantitative finance research, offering both breadth across market sectors and depth in daily trading dynamics while maintaining statistical realism throughout the observation period...

  4. 34-year Daily Stock Data (1990-2024)

    • kaggle.com
    Updated Dec 10, 2024
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    Shivesh Prakash (2024). 34-year Daily Stock Data (1990-2024) [Dataset]. https://www.kaggle.com/datasets/shiveshprakash/34-year-daily-stock-data
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 10, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Shivesh Prakash
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Dataset Description: 34-year Daily Stock Data (1990-2024)

    Context and Inspiration

    This dataset captures historical financial market data and macroeconomic indicators spanning over three decades, from 1990 onwards. It is designed for financial analysis, time series forecasting, and exploring relationships between market volatility, stock indices, and macroeconomic factors. This dataset is particularly relevant for researchers, data scientists, and enthusiasts interested in studying: - Volatility forecasting (VIX) - Stock market trends (S&P 500, DJIA, HSI) - Macroeconomic influences on markets (joblessness, interest rates, etc.) - The effect of geopolitical and economic uncertainty (EPU, GPRD)

    Sources

    The data has been aggregated from a mix of historical financial records and publicly available macroeconomic datasets: - VIX (Volatility Index): Chicago Board Options Exchange (CBOE). - Stock Indices (S&P 500, DJIA, HSI): Yahoo Finance and historical financial databases. - Volume Data: Extracted from official exchange reports. - Macroeconomic Indicators: Bureau of Economic Analysis (BEA), Federal Reserve, and other public records. - Uncertainty Metrics (EPU, GPRD): Economic Policy Uncertainty Index and Global Policy Uncertainty Database.

    Columns

    1. dt: Date of observation in YYYY-MM-DD format.
    2. vix: VIX (Volatility Index), a measure of expected market volatility.
    3. sp500: S&P 500 index value, a benchmark of the U.S. stock market.
    4. sp500_volume: Daily trading volume for the S&P 500.
    5. djia: Dow Jones Industrial Average (DJIA), another key U.S. market index.
    6. djia_volume: Daily trading volume for the DJIA.
    7. hsi: Hang Seng Index, representing the Hong Kong stock market.
    8. ads: Aruoba-Diebold-Scotti (ADS) Business Conditions Index, reflecting U.S. economic activity.
    9. us3m: U.S. Treasury 3-month bond yield, a short-term interest rate proxy.
    10. joblessness: U.S. unemployment rate, reported as quartiles (1 represents lowest quartile and so on).
    11. epu: Economic Policy Uncertainty Index, quantifying policy-related economic uncertainty.
    12. GPRD: Geopolitical Risk Index (Daily), measuring geopolitical risk levels.
    13. prev_day: Previous day’s S&P 500 closing value, added for lag-based time series analysis.

    Key Features

    • Cross-Market Analysis: Compare U.S. markets (S&P 500, DJIA) with international benchmarks like HSI.
    • Macroeconomic Insights: Assess how external factors like joblessness, interest rates, and economic uncertainty affect markets.
    • Temporal Scope: Longitudinal data facilitates trend analysis and machine learning model training.

    Potential Use Cases

    • Forecasting market indices using machine learning or statistical models.
    • Building volatility trading strategies with VIX Futures.
    • Economic research on relationships between policy uncertainty and market behavior.
    • Educational material for financial data visualization and analysis tutorials.

    Feel free to use this dataset for academic, research, or personal projects.

  5. D

    Stock Analysis Software Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
    + more versions
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    Dataintelo (2025). Stock Analysis Software Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-stock-analysis-software-market
    Explore at:
    csv, pdf, pptxAvailable download formats
    Dataset updated
    Jan 7, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    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



  6. c

    S&P 500 stock Dataset

    • cubig.ai
    Updated May 28, 2025
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    CUBIG (2025). S&P 500 stock Dataset [Dataset]. https://cubig.ai/store/products/359/sp-500-stock-dataset
    Explore at:
    Dataset updated
    May 28, 2025
    Dataset authored and provided by
    CUBIG
    License

    https://cubig.ai/store/terms-of-servicehttps://cubig.ai/store/terms-of-service

    Measurement technique
    Synthetic data generation using AI techniques for model training, Privacy-preserving data transformation via differential privacy
    Description

    1) Data Introduction • The S&P 500 stock data is a tabular stock market dataset of daily stock price information (market, high price, low price, closing price, trading volume, etc.) for the last five years (the latest data is until February 2018) of all companies in the S&P 500 index.

    2) Data Utilization (1) S&P 500 stock data has characteristics that: • Each row contains key stock metrics such as date, open, high, low, close, volume, and stock ticker name. • Data is provided as individual stock files and all stock integrated files, so it can be used for various analysis purposes. (2) S&P 500 stock data can be used to: • Stock Price Forecasting and Investment Strategy Development: Using historical stock price data, a variety of investment strategies and forecasting models can be developed, including time series forecasting, volatility analysis, and moving averages. • Market Trends and Corporate Comparison Analysis: It can be used to visualize stock price fluctuations across stocks, compare performance between stocks, analyze market trends, optimize portfolios, and more.

  7. T

    United Kingdom Stock Market Index (GB100) Data

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Oct 7, 2025
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    TRADING ECONOMICS (2025). United Kingdom Stock Market Index (GB100) Data [Dataset]. https://tradingeconomics.com/united-kingdom/stock-market
    Explore at:
    excel, xml, json, csvAvailable download formats
    Dataset updated
    Oct 7, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 3, 1984 - Oct 7, 2025
    Area covered
    United Kingdom
    Description

    United Kingdom's main stock market index, the GB100, rose to 9484 points on October 7, 2025, gaining 0.05% from the previous session. Over the past month, the index has climbed 2.84% and is up 15.79% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United Kingdom. United Kingdom Stock Market Index (GB100) - values, historical data, forecasts and news - updated on October of 2025.

  8. c

    Twitter Stocks Dataset

    • cubig.ai
    Updated May 26, 2025
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    CUBIG (2025). Twitter Stocks Dataset [Dataset]. https://cubig.ai/store/products/249/twitter-stocks-dataset
    Explore at:
    Dataset updated
    May 26, 2025
    Dataset authored and provided by
    CUBIG
    License

    https://cubig.ai/store/terms-of-servicehttps://cubig.ai/store/terms-of-service

    Measurement technique
    Synthetic data generation using AI techniques for model training, Privacy-preserving data transformation via differential privacy
    Description

    1) Data Introduction • The Twitter Stock Prices Dataset contains stock price data for Twitter from November 2013 to October 2022. This dataset is a time series dataset that provides daily stock trading information. • The key attributes include the stock's opening price (Open), highest price (High), lowest price (Low), closing price (Close), adjusted closing price (Adj Close), and volume (Volume).

    2) Data Utilization (1) Characteristics of the Twitter Stock Prices Data • This dataset is a time series, offering daily stock price fluctuations and allows tracking of price changes over time. • It includes 7 main attributes related to stock trading, allowing for analysis of price movements (open, high, low, close) and volume, to better understand Twitter’s stock price dynamics. • This data helps analyze market trends, price volatility patterns, and price fluctuation analysis, providing insights into the dynamics of the stock market.

    (2) Applications of the Twitter Stock Prices Data • Predictive Modeling: This dataset can be used to develop stock price prediction models, including predicting price increases/decreases or forecasting future stock prices using machine learning models. • Business Insights: Investment experts can use this dataset to evaluate Twitter’s stock performance, and it provides useful information for optimizing investment strategies in response to market changes. This dataset can be used for trend forecasting and investor analysis. • Trend Analysis: By analyzing stock upward/downward trends, this dataset can help evaluate the company's market performance and develop trend-based investment strategies.

  9. Monthly development Dow Jones Industrial Average Index 2018-2025

    • statista.com
    • tokrwards.com
    Updated Jul 22, 2025
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    Statista (2025). Monthly development Dow Jones Industrial Average Index 2018-2025 [Dataset]. https://www.statista.com/statistics/261690/monthly-performance-of-djia-index/
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    Dataset updated
    Jul 22, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2018 - Jun 2025
    Area covered
    United States
    Description

    The value of the DJIA index amounted to ****** at the end of June 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.

  10. c

    The global stock market size is USD 3645.2 million in 2024.

    • cognitivemarketresearch.com
    pdf,excel,csv,ppt
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    Cognitive Market Research, The global stock market size is USD 3645.2 million in 2024. [Dataset]. https://www.cognitivemarketresearch.com/stock-market-report
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset authored and provided by
    Cognitive Market Research
    License

    https://www.cognitivemarketresearch.com/privacy-policyhttps://www.cognitivemarketresearch.com/privacy-policy

    Time period covered
    2021 - 2033
    Area covered
    Global
    Description

    According to Cognitive Market Research, the global stock market size was USD 3645.2 million in 2024. It will expand at a compound annual growth rate (CAGR) of 13% from 2024 to 2031.

    North America held the major market share for more than 40% of the global revenue with a market size of USD 1458.1 million in 2024 and will grow at a compound annual growth rate (CAGR) of 11.2% from 2024 to 2031.
    Europe accounted for a market share of over 30% of the global revenue with a market size of USD 1093.6 million.
    Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 838.4 million in 2024 and will grow at a compound annual growth rate (CAGR) of 15% from 2024 to 2031.
    Latin America had a market share of more than 5% of the global revenue with a market size of USD 182.3 million in 2024 and will grow at a compound annual growth rate (CAGR) of 12.4% from 2024 to 2031.
    Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 72.9 million in 2024 and will grow at a compound annual growth rate (CAGR) of 12.7% from 2024 to 2031.
    The broker end users held the highest stock market revenue share in 2024.
    

    Market Dynamics of Stock Market

    Key Drivers for the Stock Market

    Rising Demand for Real-Time Data and Analytics to be an Emerging Market Trend
    

    The increasing need for real-time data and advanced analytics is a significant driver in the stock trading and investing market growth. Investors and traders require up-to-the-minute information on stock prices, market trends, and financial news to make informed decisions quickly. As financial markets become more dynamic and competitive, the ability to access and analyze real-time data becomes crucial for success. Trading applications that offer real-time updates, advanced charting tools, and detailed analytics provide users with a competitive edge by enabling them to react swiftly to market movements. This heightened demand for real-time insights fuels the development and adoption of sophisticated trading platforms that cater to both professional traders and retail investors seeking to maximize their investment opportunities.

    Increasing Adoption of Mobile Trading Platforms to Boost Market Growth
    

    The rapid adoption of mobile trading platforms is another key driver for the stock market expansion. With the proliferation of smartphones and mobile internet access, investors are increasingly favoring mobile platforms for their trading activities due to their convenience and accessibility. Mobile trading apps offer users the ability to trade, monitor portfolios, and access financial information on the go, which appeals to both active traders and casual investors. This shift towards mobile platforms is supported by innovations in-app functionality, user experience, and security features. As more investors seek flexibility and real-time engagement with their investments, the demand for sophisticated and user-friendly mobile trading applications continues to rise, propelling market growth.

    Restraint Factor for the Stock Market

    Stringent Rules and Regulations to Impede the Adoption of Online Trading Platforms
    

    Regulatory compliance and legal challenges are major restraints for the stock trading and investing market share. The financial industry is heavily regulated, with strict rules governing trading practices, data protection, and financial disclosures. Compliance with these regulations requires substantial investment in legal expertise, technology, and administrative processes. Changes in regulations can also introduce uncertainty and additional compliance costs for application providers. For example, regulations such as the Markets in Financial Instruments Directive II (MiFID II) in Europe and the Dodd-Frank Act in the U.S. impose stringent requirements on trading practices and transparency. Failure to adhere to these regulations can result in legal penalties and damage to a company’s reputation, which can inhibit market growth and innovation in trading applications.

    Market Volatility and Investor Uncertainty
    
    The stock market is highly sensitive to global economic conditions, geopolitical tensions, interest rate fluctuations, and unexpected events (such as pandemics or wars). This inherent volatility can lead to sharp declines in investor confidence and capital outflows, especially among retail in...
    
  11. T

    United States Stock Market Index Data

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +5more
    csv, excel, json, xml
    Updated Mar 6, 2024
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    TRADING ECONOMICS (2024). United States Stock Market Index Data [Dataset]. https://tradingeconomics.com/united-states/stock-market?&sa=u&ei=oscuvi_vm87uaom-gzah&ved=0cdcqfjag&usg=afqjcnft8xo94npdcodluglxnqi05ysxta
    Explore at:
    excel, json, csv, xmlAvailable download formats
    Dataset updated
    Mar 6, 2024
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 3, 1928 - Sep 8, 2025
    Area covered
    United States
    Description

    The main stock market index of United States, the US500, rose to 6497 points on September 8, 2025, gaining 0.24% from the previous session. Over the past month, the index has climbed 1.94% and is up 18.76% 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 September of 2025.

  12. T

    Japan Stock Market Index (JP225) Data

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Feb 1, 2024
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    TRADING ECONOMICS (2025). Japan Stock Market Index (JP225) Data [Dataset]. https://tradingeconomics.com/japan/stock-market
    Explore at:
    excel, csv, xml, jsonAvailable download formats
    Dataset updated
    Feb 1, 2024
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 5, 1965 - Oct 7, 2025
    Area covered
    Japan
    Description

    Japan's main stock market index, the JP225, rose to 48132 points on October 7, 2025, gaining 0.39% from the previous session. Over the past month, the index has climbed 10.28% and is up 23.61% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Japan. Japan Stock Market Index (JP225) - values, historical data, forecasts and news - updated on October of 2025.

  13. v

    Global Stock Analysis Software Market Size By Functionality (Technical...

    • verifiedmarketresearch.com
    Updated Sep 11, 2025
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    VERIFIED MARKET RESEARCH (2025). Global Stock Analysis Software Market Size By Functionality (Technical Analysis Software, Fundamental Analysis Software), By End User (Individual Investors, Professional Traders), By Deployment (On Premises, Cloud Based), By Geographic Scope And Forecast [Dataset]. https://www.verifiedmarketresearch.com/product/stock-analysis-software-market/
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    Dataset updated
    Sep 11, 2025
    Dataset authored and provided by
    VERIFIED MARKET RESEARCH
    License

    https://www.verifiedmarketresearch.com/privacy-policy/https://www.verifiedmarketresearch.com/privacy-policy/

    Time period covered
    2026 - 2032
    Area covered
    Global
    Description

    Stock Analysis Software Market size was valued at USD 145.6 Million in 2024 and is projected to reach USD 450.68 Million by 2032, growing at a CAGR of 15.17% during the forecast period 2026-2032.Growing Retail Investor Participation: The Indian stock market has witnessed an unprecedented surge in retail investor participation. With the advent of user-friendly trading platforms, such as Zerodha, Groww, and Upstox, and the reduction of traditional barriers like high fees and the introduction of fractional shares, more individuals are now able to enter the market.Demand for Real-Time Data and Analytics: In today's fast-paced financial world, the need for real-time data and analytics is paramount. Investors, from seasoned professionals to burgeoning retail participants, require up-to-the-minute information on stock prices, breaking news, and crucial technical indicators to capitalize on fleeting opportunities.

  14. F

    S&P 500

    • fred.stlouisfed.org
    json
    Updated Oct 3, 2025
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    (2025). S&P 500 [Dataset]. https://fred.stlouisfed.org/series/SP500
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    jsonAvailable download formats
    Dataset updated
    Oct 3, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-pre-approvalhttps://fred.stlouisfed.org/legal/#copyright-pre-approval

    Description

    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.

  15. All-Time Stock Price Data

    • kaggle.com
    Updated Apr 24, 2024
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    Terry Wang (2024). All-Time Stock Price Data [Dataset]. http://doi.org/10.34740/kaggle/dsv/8215122
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 24, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Terry Wang
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    This comprehensive dataset provides historical stock price data spanning various time periods, offering insights into the fluctuations and trends in the stock market over time. With records covering multiple decades, investors, analysts, and researchers can explore the dynamics of different stocks, industries, and market sectors.

    The dataset includes essential information such as opening price, closing price, highest and lowest prices, trading volume, and adjusted closing prices. It encompasses a diverse range of stocks, including those from various exchanges and sectors, allowing for extensive analysis and comparison.

    Researchers can utilize this dataset to conduct thorough analyses, develop financial models, backtest trading strategies, and gain a deeper understanding of market behavior. Investors can assess the performance of individual stocks or portfolios over extended periods, aiding in informed decision-making and risk management.

    Whether you're a seasoned investor seeking historical insights or an analyst exploring market trends, this dataset serves as a valuable resource for studying the complexities of the stock market across different eras.

  16. Stock Prices Dataset

    • brightdata.com
    .json, .csv, .xlsx
    Updated Dec 2, 2024
    + more versions
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    Bright Data (2024). Stock Prices Dataset [Dataset]. https://brightdata.com/products/datasets/financial/stock-price
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    .json, .csv, .xlsxAvailable download formats
    Dataset updated
    Dec 2, 2024
    Dataset authored and provided by
    Bright Datahttps://brightdata.com/
    License

    https://brightdata.com/licensehttps://brightdata.com/license

    Area covered
    Worldwide
    Description

    Use our Stock prices dataset to access comprehensive financial and corporate data, including company profiles, stock prices, market capitalization, revenue, and key performance metrics. This dataset is tailored for financial analysts, investors, and researchers to analyze market trends and evaluate company performance.

    Popular use cases include investment research, competitor benchmarking, and trend forecasting. Leverage this dataset to make informed financial decisions, identify growth opportunities, and gain a deeper understanding of the business landscape. The dataset includes all major data points: company name, company ID, summary, stock ticker, earnings date, closing price, previous close, opening price, and much more.

  17. T

    China Shanghai Composite Stock Market Index Data

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Sep 30, 2025
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    TRADING ECONOMICS (2025). China Shanghai Composite Stock Market Index Data [Dataset]. https://tradingeconomics.com/china/stock-market
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    xml, csv, excel, jsonAvailable download formats
    Dataset updated
    Sep 30, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 19, 1990 - Sep 30, 2025
    Area covered
    China
    Description

    China's main stock market index, the SHANGHAI, rose to 3883 points on September 30, 2025, gaining 0.52% from the previous session. Over the past month, the index has climbed 0.19% and is up 11.26% compared to the same time last year, 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 October of 2025.

  18. T

    France Stock Market Index (FR40) Data

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Oct 7, 2025
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    TRADING ECONOMICS (2025). France Stock Market Index (FR40) Data [Dataset]. https://tradingeconomics.com/france/stock-market
    Explore at:
    json, xml, csv, excelAvailable download formats
    Dataset updated
    Oct 7, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jul 9, 1987 - Oct 7, 2025
    Area covered
    France
    Description

    France's main stock market index, the FR40, fell to 7966 points on October 7, 2025, losing 0.07% from the previous session. Over the past month, the index has climbed 2.99% and is up 5.91% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from France. France Stock Market Index (FR40) - values, historical data, forecasts and news - updated on October of 2025.

  19. D

    Securities Brokerages And Stock Exchanges Market Report | Global Forecast...

    • dataintelo.com
    csv, pdf, pptx
    Updated Dec 3, 2024
    + more versions
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    Dataintelo (2024). Securities Brokerages And Stock Exchanges Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/securities-brokerages-and-stock-exchanges-market
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Dec 3, 2024
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Securities Brokerages and Stock Exchanges Market Outlook



    The global securities brokerages and stock exchanges market size is projected to grow significantly, with the market value estimated at USD 75 billion in 2023 and expected to reach USD 115 billion by 2032, reflecting a robust compound annual growth rate (CAGR) of 4.8% over the forecast period. The burgeoning growth can be attributed to the increasing participation of both retail and institutional investors, technological advancements in trading platforms, and the globalization of financial markets which have collectively contributed to the expansion of the securities brokerages and stock exchanges sector. This growth trajectory is further bolstered by the rising accessibility of financial markets to a broader audience, driven by the proliferation of online brokerage services and mobile trading platforms.



    One of the primary growth factors for this market is the surge in retail investors entering the space, largely fueled by the democratization of trading through online platforms and apps. These platforms have significantly lowered the barriers to entry, providing user-friendly interfaces and educational content that empower individuals to manage their investments independently. Additionally, the rise of social media and financial forums has created a community-driven approach to investing, where retail investors share insights and strategies, further increasing market participation. The pandemic has accelerated this trend, as many individuals have turned to the stock market as a means of supplementing income during economic uncertainty.



    Another key driver is the technological advancements shaping the landscape of securities trading. The incorporation of artificial intelligence, machine learning, and blockchain technologies has revolutionized the way trades are executed, making them faster, more secure, and more efficient. High-frequency trading, powered by sophisticated algorithms, has become a dominant force in the market, contributing to increased trading volumes and liquidity. Furthermore, the development of robo-advisors and automated trading systems has made investment management more accessible and affordable, attracting a diverse array of investors with varying levels of expertise.



    Moreover, globalization has significantly impacted the securities brokerages and stock exchanges market, as cross-border trading has become more prevalent. Financial markets are increasingly interconnected, allowing investors to access global opportunities beyond their domestic exchanges. This has led to a diversification of investment portfolios, with investors seeking exposure to emerging markets that offer high growth potential. Consequently, stock exchanges around the world are collaborating and forming alliances to facilitate seamless trading across borders, enhancing liquidity and market depth.



    Service Type Analysis



    The service type segment of the securities brokerages and stock exchanges market can be broadly categorized into full-service brokerages, discount brokerages, and stock exchanges. Full-service brokerages offer a comprehensive range of services, including investment advice, portfolio management, research reports, and retirement planning. This segment is traditionally preferred by high-net-worth individuals and institutional investors who require personalized and in-depth financial services. Despite higher fees, the demand for full-service brokerages remains steady due to the value-added services they provide, especially in complex financial environments.



    Discount brokerages have gained significant traction in recent years, driven by the rise of self-directed investing. These platforms offer low-cost trading services with minimal or no advisory support, appealing to price-sensitive retail investors who are confident in their investment decisions. The competitive pricing models of discount brokerages, coupled with their easy-to-use digital platforms, have disrupted the traditional brokerage industry by attracting a large pool of younger, tech-savvy investors. The shift towards online and mobile trading has further accelerated the growth of this segment.



    Stock exchanges, as the backbone of capital markets, provide the infrastructure necessary for the trading of securities. They play a critical role in ensuring market transparency, liquidity, and price discovery. As financial markets evolve, stock exchanges are increasingly adopting innovative technologies to enhance their trading systems and attract more listings. The introduction of new trading products, such as derivatives and ETFs, has diversified the offeri

  20. D

    Online Brokers for Stock Trading Market Report | Global Forecast From 2025...

    • dataintelo.com
    csv, pdf, pptx
    Updated Sep 12, 2024
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    Dataintelo (2024). Online Brokers for Stock Trading Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-online-brokers-for-stock-trading-market
    Explore at:
    pdf, csv, pptxAvailable download formats
    Dataset updated
    Sep 12, 2024
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Online Brokers for Stock Trading Market Outlook



    The global market size for online brokers for stock trading was valued at USD 14.8 billion in 2023 and is projected to reach USD 35.6 billion by 2032, growing at a CAGR of 10.2% from 2024 to 2032. The substantial growth in this market is primarily driven by the increased adoption of online trading platforms among retail and institutional investors. Factors such as technological advancements, greater accessibility to financial markets, and the proliferation of internet and mobile device usage have significantly contributed to this market's expansion.



    One of the primary growth factors in the online brokers for stock trading market is the technological advancement in trading platforms. The integration of artificial intelligence, machine learning, and blockchain technology has revolutionized trading operations, making them more efficient and secure. These technological innovations provide traders with real-time data, sophisticated analytics, and automated trading options, enhancing their trading experience and success rates. The continuous improvement and innovation in trading software and tools are expected to drive market growth further.



    Another significant growth driver is the increased accessibility to financial markets. The democratization of stock trading, enabled by online platforms, has opened up investment opportunities to a broader audience. Retail investors, who previously found it challenging to enter the stock market due to high costs and complex procedures, now benefit from lower fees, user-friendly interfaces, and educational resources provided by online brokers. This increased accessibility has led to a surge in the number of active traders, thereby boosting market growth.



    Additionally, the proliferation of internet and mobile device usage has played a crucial role in the market's growth. The widespread use of smartphones and high-speed internet has made it easier for investors to trade stocks from anywhere and at any time. Mobile-based trading platforms offer convenience and flexibility, attracting a younger demographic and contributing to the market's expansion. The growing trend of mobile trading and the development of dedicated trading apps are expected to further propel market growth in the coming years.



    From a regional perspective, North America holds the largest share in the online brokers for stock trading market, followed by Europe and Asia Pacific. North America's dominance can be attributed to its well-established financial markets, high internet penetration, and the presence of major online broker firms. Europe is also witnessing significant growth due to favorable regulatory environments and technological advancements. The Asia Pacific region is expected to experience the highest growth rate during the forecast period, driven by emerging markets, increasing internet penetration, and a growing middle-class population with rising disposable incomes.



    Platform Type Analysis



    The platform type segment of the online brokers for stock trading market is categorized into web-based, mobile-based, and desktop-based platforms. Web-based platforms dominate the market due to their widespread adoption and ease of access. These platforms offer comprehensive functionalities, including real-time data, market analysis, and trading execution, making them popular among both retail and institutional investors. The continuous development and enhancement of web-based platforms are expected to maintain their dominance in the market.



    Mobile-based platforms are witnessing rapid growth, driven by the increasing use of smartphones and the demand for on-the-go trading solutions. These platforms provide users with flexibility and convenience, allowing them to trade stocks anytime and anywhere. The development of advanced mobile trading apps with user-friendly interfaces, real-time notifications, and secure transactions is attracting a younger demographic of investors. The growth of mobile-based platforms is expected to outpace other platform types during the forecast period.



    Desktop-based platforms, although declining in popularity compared to web and mobile platforms, still maintain a significant user base. These platforms are preferred by professional and institutional investors who require advanced trading tools, customizability, and high-speed data processing capabilities. Desktop-based platforms offer robust features such as algorithmic trading, charting tools, and direct market access, catering to the needs of experienced traders. Despite the rise of web an

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Close
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TRADING ECONOMICS (2025). United States Stock Market Index Data [Dataset]. https://tradingeconomics.com/united-states/stock-market

United States Stock Market Index Data

United States Stock Market Index - Historical Dataset (1928-01-03/2025-10-07)

Explore at:
20 scholarly articles cite this dataset (View in Google Scholar)
excel, xml, json, csvAvailable download formats
Dataset authored and provided by
TRADING ECONOMICS
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Jan 3, 1928 - Oct 7, 2025
Area covered
United States
Description

The main stock market index of United States, the US500, fell to 6738 points on October 7, 2025, losing 0.04% from the previous session. Over the past month, the index has climbed 3.73% and is up 17.15% 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 October of 2025.

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