100+ datasets found
  1. Nasdaq Stocks Dataset

    • zenodo.org
    • explore.openaire.eu
    csv
    Updated Mar 20, 2022
    + more versions
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    Javier Advani; Javier Advani (2022). Nasdaq Stocks Dataset [Dataset]. http://doi.org/10.5281/zenodo.6368832
    Explore at:
    csvAvailable download formats
    Dataset updated
    Mar 20, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Javier Advani; Javier Advani
    License

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

    Description

    NASDAQ (National Association of Securities Dealers Automated Quotation) is the world's second largest automated and electronic stock exchange and securities market in the United States, the first being the New York Stock Exchange, with more than 8,000 companies and corporations. It has more trading volume per hour than any other stock exchange in the world. More than 7,000 small and mid-cap stocks are traded on the NASDAQ. It is characterized by comprising high-tech companies in electronics, computers, telecommunications, biotechnology, and many others.

    This dataset was created as a result of an automatic extraction of open & public data available in nasdaq.com, using web scraping techniques. The only purpose of creating it was for academic reasons

  2. T

    United States Stock Market Index Data

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +11more
    csv, excel, json, xml
    Updated May 15, 2025
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    TRADING ECONOMICS, United States Stock Market Index Data [Dataset]. https://tradingeconomics.com/united-states/stock-market
    Explore at:
    excel, xml, json, csvAvailable download formats
    Dataset updated
    May 15, 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, 1928 - Jul 1, 2025
    Area covered
    United States
    Description

    The main stock market index of United States, the US500, rose to 6211 points on July 1, 2025, gaining 0.10% from the previous session. Over the past month, the index has climbed 4.64% and is up 12.75% 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.

  3. United States US: Stocks Traded: Total Value

    • ceicdata.com
    Updated Nov 22, 2021
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    CEICdata.com (2023). United States US: Stocks Traded: Total Value [Dataset]. https://www.ceicdata.com/en/united-states/financial-sector/us-stocks-traded-total-value
    Explore at:
    Dataset updated
    Nov 22, 2021
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2006 - Dec 1, 2017
    Area covered
    United States
    Variables measured
    Turnover
    Description

    United States US: Stocks Traded: Total Value data was reported at 39,785.881 USD bn in 2017. This records a decrease from the previous number of 42,071.330 USD bn for 2016. United States US: Stocks Traded: Total Value data is updated yearly, averaging 17,934.293 USD bn from Dec 1984 (Median) to 2017, with 34 observations. The data reached an all-time high of 47,245.496 USD bn in 2008 and a record low of 1,108.421 USD bn in 1984. United States US: Stocks Traded: Total Value data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Financial Sector. The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

  4. R

    Data from: Analysis of Global Stock Market Development - Integration of...

    • repod.icm.edu.pl
    tsv, txt
    Updated Apr 28, 2025
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    Stawarz, Marcin (2025). Analysis of Global Stock Market Development - Integration of Clustering, Classification, and Shapley Values [Dataset]. http://doi.org/10.18150/OELMLK
    Explore at:
    tsv(13048), txt(1325), txt(21442)Available download formats
    Dataset updated
    Apr 28, 2025
    Dataset provided by
    RepOD
    Authors
    Stawarz, Marcin
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Dataset funded by
    National Science Centre (Poland)
    Description

    Files:- stock_exchanges_data.csv:This file provides data on key financial indicators for 82 global stock exchanges, including Market Capitalization, Capitalization-to-GDP Ratio, Value Traded, Value Traded to GDP Ratio, Share Turnover Velocity, Capitalization per Listed Company, and Number of Trades. The data reflects the year 2023 and serves as the foundation for clustering and classification analysis within the study, focusing on identifying development patterns and key factors influencing stock exchange stability and competitiveness.- research_code.ipynb:This Jupyter Notebook contains the complete Python code used for the analysis conducted in the study. It includes data preparation, clustering, classification, Shapley values calculation, and all other analytical steps described in the paper. The notebook is fully reproducible based on the provided dataset.Raw data (csv files). Source: The World Federation of Exchanges (WFE) and International Monetary Fund (IMF)

  5. Stock Portfolio Data with Prices and Indices

    • kaggle.com
    Updated Mar 23, 2025
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    Nikita Manaenkov (2025). Stock Portfolio Data with Prices and Indices [Dataset]. http://doi.org/10.34740/kaggle/dsv/11140976
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 23, 2025
    Dataset provided by
    Kaggle
    Authors
    Nikita Manaenkov
    License

    https://www.gnu.org/licenses/gpl-3.0.htmlhttps://www.gnu.org/licenses/gpl-3.0.html

    Description

    This dataset consists of five CSV files that provide detailed data on a stock portfolio and related market performance over the last 5 years. It includes portfolio positions, stock prices, and major U.S. market indices (NASDAQ, S&P 500, and Dow Jones). The data is essential for conducting portfolio analysis, financial modeling, and performance tracking.

    1. Portfolio

    This file contains the portfolio composition with details about individual stock positions, including the quantity of shares, sector, and their respective weights in the portfolio. The data also includes the stock's closing price.

    • Columns:
      • Ticker: The stock symbol (e.g., AAPL, TSLA)
      • Quantity: The number of shares in the portfolio
      • Sector: The sector the stock belongs to (e.g., Technology, Healthcare)
      • Close: The closing price of the stock
      • Weight: The weight of the stock in the portfolio (as a percentage of total portfolio)

    2. Portfolio Prices

    This file contains historical pricing data for the stocks in the portfolio. It includes daily open, high, low, close prices, adjusted close prices, returns, and volume of traded stocks.

    • Columns:
      • Date: The date of the data point
      • Ticker: The stock symbol
      • Open: The opening price of the stock on that day
      • High: The highest price reached on that day
      • Low: The lowest price reached on that day
      • Close: The closing price of the stock
      • Adjusted: The adjusted closing price after stock splits and dividends
      • Returns: Daily percentage return based on close prices
      • Volume: The volume of shares traded that day

    3. NASDAQ

    This file contains historical pricing data for the NASDAQ Composite index, providing similar data as in the Portfolio Prices file, but for the NASDAQ market index.

    • Columns:
      • Date: The date of the data point
      • Ticker: The stock symbol (for NASDAQ index, this will be "IXIC")
      • Open: The opening price of the index
      • High: The highest value reached on that day
      • Low: The lowest value reached on that day
      • Close: The closing value of the index
      • Adjusted: The adjusted closing value after any corporate actions
      • Returns: Daily percentage return based on close values
      • Volume: The volume of shares traded

    4. S&P 500

    This file contains similar historical pricing data, but for the S&P 500 index, providing insights into the performance of the top 500 U.S. companies.

    • Columns:
      • Date: The date of the data point
      • Ticker: The stock symbol (for S&P 500 index, this will be "SPX")
      • Open: The opening price of the index
      • High: The highest value reached on that day
      • Low: The lowest value reached on that day
      • Close: The closing value of the index
      • Adjusted: The adjusted closing value after any corporate actions
      • Returns: Daily percentage return based on close values
      • Volume: The volume of shares traded

    5. Dow Jones

    This file contains similar historical pricing data for the Dow Jones Industrial Average, providing insights into one of the most widely followed stock market indices in the world.

    • Columns:
      • Date: The date of the data point
      • Ticker: The stock symbol (for Dow Jones index, this will be "DJI")
      • Open: The opening price of the index
      • High: The highest value reached on that day
      • Low: The lowest value reached on that day
      • Close: The closing value of the index
      • Adjusted: The adjusted closing value after any corporate actions
      • Returns: Daily percentage return based on close values
      • Volume: The volume of shares traded

    Personal Portfolio Data

    This data is received using a custom framework that fetches real-time and historical stock data from Yahoo Finance. It provides the portfolio’s data based on user-specific stock holdings and performance, allowing for personalized analysis. The personal framework ensures the portfolio data is automatically retrieved and updated with the latest stock prices, returns, and performance metrics.

    This part of the dataset would typically involve data specific to a particular user’s stock positions, weights, and performance, which can be integrated with the other files for portfolio performance analysis.

  6. Egypt EG: Stocks Traded: Total Value

    • ceicdata.com
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    CEICdata.com, Egypt EG: Stocks Traded: Total Value [Dataset]. https://www.ceicdata.com/en/egypt/financial-sector/eg-stocks-traded-total-value
    Explore at:
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2006 - Dec 1, 2017
    Area covered
    Egypt
    Variables measured
    Turnover
    Description

    Egypt EG: Stocks Traded: Total Value data was reported at 14.429 USD bn in 2017. This records an increase from the previous number of 10.080 USD bn for 2016. Egypt EG: Stocks Traded: Total Value data is updated yearly, averaging 21.767 USD bn from Dec 2006 (Median) to 2017, with 12 observations. The data reached an all-time high of 95.827 USD bn in 2008 and a record low of 10.080 USD bn in 2016. Egypt EG: Stocks Traded: Total Value data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Egypt – Table EG.World Bank.WDI: Financial Sector. The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

  7. T

    Japan Stock Market Index (JP225) Data

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 28, 2025
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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
    Jun 28, 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 5, 1965 - Jun 27, 2025
    Area covered
    Japan
    Description

    Japan's main stock market index, the JP225, rose to 40151 points on June 27, 2025, gaining 1.43% from the previous session. Over the past month, the index has climbed 6.44% and is up 1.43% 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 June of 2025.

  8. Global Stock Exchanges (Cap = 1 trillion+) 04-23

    • kaggle.com
    Updated Nov 30, 2024
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    Daniel Tafmizi (2024). Global Stock Exchanges (Cap = 1 trillion+) 04-23 [Dataset]. https://www.kaggle.com/datasets/danieltafmizi/global-stock-exchange-cap-1-trillion-04-23/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 30, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Daniel Tafmizi
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    Data retrieved from world-exchanges.org Statistics portal. It comprises of 19 of the largest market capitalization stock exchanges from around the world, with a minimum 1 trillion USD valuation in 2023. The cleaned version is a wide dataframe with exchange name, region, and its valuation across the years.

    My work can be seen at:

    Code: https://github.com/DanielDataGit/daniel.R/blob/main/Work.R/LIS4370Rprog/4317FinalProjectCode.R

    Blog: https://danieltlis4317.blogspot.com/2024/11/final-project.html

  9. h

    global-top-Index-exploring-trends-in-stock-Market

    • huggingface.co
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    PETTAH AI, global-top-Index-exploring-trends-in-stock-Market [Dataset]. https://huggingface.co/datasets/pettah/global-top-Index-exploring-trends-in-stock-Market
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Authors
    PETTAH AI
    License

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

    Description

    Global Top Index: Exploring Trends in Stock Markets

      About the Dataset
    

    The Global Top Index dataset offers a detailed view of daily trading activities from several of the world's leading stock market indices. This dataset is ideal for conducting comprehensive analyses to uncover insights and predictive trends in the international stock markets.

      Dataset Contents
    

    The dataset encompasses the following key data points for each trading session across multiple dates… See the full description on the dataset page: https://huggingface.co/datasets/pettah/global-top-Index-exploring-trends-in-stock-Market.

  10. T

    China Shanghai Composite Stock Market Index Data

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 30, 2025
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    TRADING ECONOMICS (2025). China Shanghai Composite Stock Market Index Data [Dataset]. https://tradingeconomics.com/china/stock-market
    Explore at:
    xml, csv, excel, jsonAvailable download formats
    Dataset updated
    Jun 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 - Jul 1, 2025
    Area covered
    China
    Description

    China's main stock market index, the SHANGHAI, rose to 3448 points on July 1, 2025, gaining 0.11% from the previous session. Over the past month, the index has climbed 2.57% and is up 15.06% 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 July of 2025.

  11. c

    Yahoo Stocks Dataset

    • crawlfeeds.com
    csv, zip
    Updated Apr 27, 2025
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    Crawl Feeds (2025). Yahoo Stocks Dataset [Dataset]. https://crawlfeeds.com/datasets/yahoo-stocks-dataset
    Explore at:
    zip, csvAvailable download formats
    Dataset updated
    Apr 27, 2025
    Dataset authored and provided by
    Crawl Feeds
    License

    https://crawlfeeds.com/privacy_policyhttps://crawlfeeds.com/privacy_policy

    Description

    The Yahoo Stocks Dataset is an invaluable resource for analysts, traders, and developers looking to enhance their financial data models or trading strategies. Sourced from Yahoo Finance, this dataset includes historical stock prices, market trends, and financial indicators. With its accurate and comprehensive data, it empowers users to analyze patterns, forecast trends, and build robust machine learning models.

    Whether you're a seasoned stock market analyst or a beginner in financial data science, this dataset is tailored to meet diverse needs. It features details like stock prices, trading volume, and market capitalization, enabling a deep dive into investment opportunities and market dynamics.

    For machine learning and AI enthusiasts, the Yahoo Stocks Dataset is a goldmine. It’s perfect for developing predictive models, such as stock price forecasting and sentiment analysis. The dataset's structured format ensures seamless integration into Python, R, and other analytics platforms, making data visualization and reporting effortless.

    Additionally, this dataset supports long-term trend analysis, helping investors make informed decisions. It’s also an essential resource for those conducting research in algorithmic trading and portfolio management.

    Key benefits include:

    • Historical Stock Data: Access years of trading data to analyze market behaviors.
    • Versatile Applications: Use it for financial modeling, data analytics, or academic research.
    • SEO Benefits for Finance Websites: Boost your content with insights derived from this dataset.

    Download the Yahoo Stocks Dataset today and harness the power of financial data for your projects. Whether for AI, financial reporting, or trend analysis, this dataset equips you with the tools to succeed in the dynamic world of stock markets.

  12. United States US: Market Capitalization: Listed Domestic Companies

    • ceicdata.com
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    CEICdata.com, United States US: Market Capitalization: Listed Domestic Companies [Dataset]. https://www.ceicdata.com/en/united-states/financial-sector/us-market-capitalization-listed-domestic-companies
    Explore at:
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2006 - Dec 1, 2017
    Area covered
    United States
    Variables measured
    Turnover
    Description

    United States US: Market Capitalization: Listed Domestic Companies data was reported at 32,120.703 USD bn in 2017. This records an increase from the previous number of 27,352.201 USD bn for 2016. United States US: Market Capitalization: Listed Domestic Companies data is updated yearly, averaging 11,322.354 USD bn from Dec 1980 (Median) to 2017, with 38 observations. The data reached an all-time high of 32,120.703 USD bn in 2017 and a record low of 1,263.561 USD bn in 1981. United States US: Market Capitalization: Listed Domestic Companies data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Financial Sector. Market capitalization (also known as market value) is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies are excluded. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

  13. Yahoo Finance - Industries - Dataset

    • kaggle.com
    Updated May 13, 2023
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    Belayet HossainDS (2023). Yahoo Finance - Industries - Dataset [Dataset]. http://doi.org/10.34740/kaggle/dsv/5678079
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 13, 2023
    Dataset provided by
    Kaggle
    Authors
    Belayet HossainDS
    Description

    https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcSO20g5cBn_b3UvD4HrPSKMrujGXq8LfT2NQP3LC3F3k8ufSV6TP97l7Har-625Bju08bc&usqp=CAU" alt="File:Yahoo Finance Logo 2013.svg - Wikipedia">

    Yahoo! Finance is a media property that is part of the Yahoo! network. It provides financial news, data and commentary including stock quotes, press releases, financial reports, and original content. It also offers some online tools for personal finance management. In addition to posting partner content from other web sites, it posts original stories by its team of staff journalists. It is ranked 20th by Similar Web on the list of largest news and media websites.

    Description: This dataset contains financial information for companies listed on major stock exchanges around the world, as provided by Yahoo Finance. The data covers a range of industries and includes key financial metrics such as price, volume, market capitalization, P/E ratio, and more.

    ### python 1.Content: 2.Symbol: 3.Name: 4.Price: 5.Volume: 6.Market cap: 7.P/E ratio:

    The data is sourced from Yahoo Finance and is updated daily, providing users with the most up-to-date financial information for each company listed.

    The dataset is suitable for anyone interested in analyzing or predicting stock market trends and is particularly useful for financial analysts, investors, and traders.

  14. Vietnam VN: Stocks Traded: Total Value

    • ceicdata.com
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    CEICdata.com, Vietnam VN: Stocks Traded: Total Value [Dataset]. https://www.ceicdata.com/en/vietnam/financial-sector/vn-stocks-traded-total-value
    Explore at:
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2008 - Dec 1, 2017
    Area covered
    Vietnam
    Variables measured
    Turnover
    Description

    Vietnam VN: Stocks Traded: Total Value data was reported at 38.060 USD bn in 2017. This records an increase from the previous number of 22.272 USD bn for 2016. Vietnam VN: Stocks Traded: Total Value data is updated yearly, averaging 19.144 USD bn from Dec 2008 (Median) to 2017, with 9 observations. The data reached an all-time high of 38.060 USD bn in 2017 and a record low of 7.057 USD bn in 2008. Vietnam VN: Stocks Traded: Total Value data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Vietnam – Table VN.World Bank.WDI: Financial Sector. The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

  15. w

    Dataset of book subjects that contain Global stock markets : a strategic...

    • workwithdata.com
    Updated Nov 7, 2024
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    Work With Data (2024). Dataset of book subjects that contain Global stock markets : a strategic guide [Dataset]. https://www.workwithdata.com/datasets/book-subjects?f=1&fcol0=j0-book&fop0=%3D&fval0=Global+stock+markets+%3A+a+strategic+guide&j=1&j0=books
    Explore at:
    Dataset updated
    Nov 7, 2024
    Dataset authored and provided by
    Work With Data
    License

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

    Description

    This dataset is about book subjects. It has 1 row and is filtered where the books is Global stock markets : a strategic guide. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

  16. w

    Dataset of stocks from Global

    • workwithdata.com
    Updated Apr 11, 2025
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    Work With Data (2025). Dataset of stocks from Global [Dataset]. https://www.workwithdata.com/datasets/stocks?f=1&fcol0=company&fop0=%3D&fval0=Global
    Explore at:
    Dataset updated
    Apr 11, 2025
    Dataset authored and provided by
    Work With Data
    License

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

    Description

    This dataset is about stocks. It has 4 rows and is filtered where the company is Global. It features 8 columns including stock name, company, exchange, and exchange symbol.

  17. Stock Market Performance and Corporate Board

    • kaggle.com
    Updated Jan 12, 2023
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    The Devastator (2023). Stock Market Performance and Corporate Board [Dataset]. https://www.kaggle.com/datasets/thedevastator/stock-market-performance-and-corporate-board-mem/suggestions
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 12, 2023
    Dataset provided by
    Kaggle
    Authors
    The Devastator
    Description

    Stock Market Performance and Corporate Board Member Profiles

    Analyzing the Influences of Leadership on Stock Market Performance

    By Jon Loyens [source]

    About this dataset

    This powerful dataset brings together publically-available information from leading stock markets with extensive details about corporate board members. For each company, discover not only their board composition and background, but also current market dynamics, trends and rule changes affecting them. Whether you're a teacher looking to add more detail to a class presentation or an investor seeking a competitive edge in the market - this dataset provides comprehensive insights into the world of stocks and those that play an influential role on its direction. Unprecedented access awaits as you explore hypothetical investments and strategies or actual risks associated with established entities today

    More Datasets

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    How to use the dataset

    Using this dataset, you can gain a better understanding of the relationship between corporate board members and stock market performance. You can analyze the data to determine the average performance of board members at different companies and compare it to the overall performance of other stocks. In addition, you can look into correlations between individual stocks, various industries, and different groups of companies with similar board membership profiles. This dataset provides an overview of all major stocks across multiple industries with detailed insights on each stock's current and past market performance as well as corporate boards

    Research Ideas

    • Analyzing the performance of individual board members in relation to their company’s stock market performance.
    • Determining if certain board members are better at making decisions that benefit the company’s stock market position across all companies they have a stake in.
    • Identifying correlations between trends in different companies' stocks and external factors such as the influence of particular board members or other events associated with that company's sectors or markets

    Acknowledgements

    If you use this dataset in your research, please credit the original authors. Data Source

    License

    See the dataset description for more information.

    Columns

    File: boardmembers.csv | Column name | Description | |:--------------------|:-----------------------------------| | BoardMemberName | Name of the board member. (String) | | CompanyName | Name of the company. (String) | | Source | Source of the data. (String) |

    Acknowledgements

    If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Jon Loyens.

  18. T

    France Stock Market Index (FR40) Data

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 30, 2025
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    TRADING ECONOMICS (2025). France Stock Market Index (FR40) Data [Dataset]. https://tradingeconomics.com/france/stock-market
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    json, xml, csv, excelAvailable download formats
    Dataset updated
    Jun 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
    Jul 9, 1987 - Jun 30, 2025
    Area covered
    France
    Description

    France's main stock market index, the FR40, rose to 7694 points on June 30, 2025, gaining 0.03% from the previous session. Over the past month, the index has declined 0.56%, though it remains 1.76% higher than a year ago, 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 June of 2025.

  19. Corporate Actions Data South Korea Techsalerator

    • kaggle.com
    Updated Aug 22, 2023
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    Techsalerator (2023). Corporate Actions Data South Korea Techsalerator [Dataset]. https://www.kaggle.com/datasets/techsalerator/corporate-actions-data-south-korea-techsalerator
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 22, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Techsalerator
    Area covered
    South Korea
    Description

    Techsalerator's Corporate Actions Dataset in South Korea offers a comprehensive collection of data fields related to corporate actions, providing valuable insights for investors, traders, and financial institutions. This dataset includes crucial information about the various financial instruments of all 2445 companies traded on the Korea Stock Exchange (XKRX).

    Top 5 used data fields in the Corporate Actions Dataset for South Korea:

    • Dividend Declaration Date: The date on which a company's board of directors announces the dividend payout to its shareholders. This information is crucial for investors who rely on dividends as a source of income.

    • Stock Split Ratio: The ratio by which a company's shares are split to increase liquidity and affordability. This field is essential for understanding changes in share structure.

    • Merger Announcement Date: The date on which a company officially announces its intention to merge with another entity. This field is crucial for investors assessing the impact of potential mergers on their investments.

    • Rights Issue Record Date: The date on which shareholders must be on the company's books to be eligible for participating in a rights issue. This data helps investors plan their participation in fundraising events.

    • Bonus Issue Ex-Date: The date on which a company's shares start trading without the value of the bonus issue. This information is vital for investors to adjust their portfolios accordingly.

    Top 5 corporate actions in South Korea:

    Mergers and Acquisitions (M&A): South Korea's business landscape has seen various corporate actions related to mergers, acquisitions, and corporate restructuring, contributing to industry consolidation and market dynamics.

    Technological Innovation: Corporate actions involving investments in technology, research and development, and innovation have been prominent in South Korea's efforts to maintain its position as a global technology leader.

    Global Expansion: South Korean companies have undertaken corporate actions to expand their global footprint, including entering new markets, forming strategic partnerships, and exploring joint ventures.

    Renewable Energy Initiatives: Corporate actions related to the renewable energy sector, including investments in solar, wind, and other green technologies, align with South Korea's push for sustainable development.

    Financial Sector Developments: Corporate actions involving financial institutions, fintech advancements, and regulatory changes contribute to the modernization and competitiveness of South Korea's financial industry.

    Top 5 financial instruments with corporate action Data in South Korea

    Seoul Stock Exchange (SSE) Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Seoul Stock Exchange. This index would provide insights into the performance of the South Korean stock market.

    Seoul Stock Exchange (SSE) Foreign Company Index: The index that tracks the performance of foreign companies listed on the Seoul Stock Exchange, if foreign listings were present. This index would give an overview of foreign business involvement in South Korea.

    KorMart: A South Korea-based online marketplace with operations in multiple regions. KorMart focuses on connecting buyers and sellers and contributing to the growth of e-commerce in South Korea.

    FinanceKorea: A financial services provider in South Korea with a focus on promoting financial inclusion and access to banking services, particularly among underserved communities.

    TechInnovate Korea: A company dedicated to advancing technological innovation in South Korea, focusing on research and development, and fostering a culture of innovation to support the country's technology sector.

    If you're interested in accessing Techsalerator's End-of-Day Pricing Data for South Korea, 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:

    Dividend Declaration Date Stock Split Ratio Merger Announcement Date Rights Issue Record Date Bonus Issue Ex-Date Stock Buyback Date Spin-Off Announcement Date Dividend Record Date Merger Effective Date Rights Issue Subscription Price ‍

    Q&A:

    How much does the Corporate Actions Dataset cost in South Korea?

    The cost of the Corporate Actions 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.

    How complete is the Corporate Actions Dataset coverage in South Korea?

    Techsalerator provides comprehensive coverage of Corporate Act...

  20. d

    TagX - Stock market data | End of Day Pricing Data | Shares, Equities &...

    • datarade.ai
    .json, .csv, .xls
    Updated Feb 27, 2024
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    TagX (2024). TagX - Stock market data | End of Day Pricing Data | Shares, Equities & bonds | Global Coverage | 10 years historical data [Dataset]. https://datarade.ai/data-products/stock-market-data-end-of-day-pricing-data-shares-equitie-tagx
    Explore at:
    .json, .csv, .xlsAvailable download formats
    Dataset updated
    Feb 27, 2024
    Dataset authored and provided by
    TagX
    Area covered
    Yemen, Pakistan, Niue, Guam, Mauritius, Equatorial Guinea, Japan, Kiribati, Guadeloupe, Germany
    Description

    TagX is your trusted partner for stock market and financial data solutions. We specialize in delivering real-time and end-of-day data feeds that power software, trading algorithms, and risk management systems globally. Whether you're a financial institution, hedge fund, or individual investor, our reliable datasets provide essential insights into market trends, historical pricing, and key financial metrics.

    TagX is committed to precision and reliability in stock market data. Our comprehensive datasets include critical information such as date, open/close/high/low prices, trading volume, EPS, P/E ratio, dividend yield, and more. Tailor your dataset to match your specific requirements, choosing from a wide range of parameters and coverage options across primary listings on NASDAQ, AMEX, NYSE, and ARCA exchanges.

    Key Features of TagX Stock Market Data:

    Custom Dataset Requests: Customize your data feed to focus on specific metrics and parameters crucial to your trading strategy.

    Extensive Coverage: Access data from reputable exchanges and market participants, ensuring accuracy and completeness in your analyses.

    Flexible Pricing Models: Choose pricing structures based on your selected parameters, offering cost-effective solutions tailored to your needs.

    Why Choose TagX? Partner with TagX for precise, dependable, and customizable stock market data solutions. Whether you require real-time updates or end-of-day valuations, our datasets are designed to support informed decision-making and enhance your competitive edge in the financial markets. Trust TagX to deliver the data integrity and accuracy essential for maximizing your trading potential.

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Javier Advani; Javier Advani (2022). Nasdaq Stocks Dataset [Dataset]. http://doi.org/10.5281/zenodo.6368832
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Nasdaq Stocks Dataset

Explore at:
csvAvailable download formats
Dataset updated
Mar 20, 2022
Dataset provided by
Zenodohttp://zenodo.org/
Authors
Javier Advani; Javier Advani
License

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

Description

NASDAQ (National Association of Securities Dealers Automated Quotation) is the world's second largest automated and electronic stock exchange and securities market in the United States, the first being the New York Stock Exchange, with more than 8,000 companies and corporations. It has more trading volume per hour than any other stock exchange in the world. More than 7,000 small and mid-cap stocks are traded on the NASDAQ. It is characterized by comprising high-tech companies in electronics, computers, telecommunications, biotechnology, and many others.

This dataset was created as a result of an automatic extraction of open & public data available in nasdaq.com, using web scraping techniques. The only purpose of creating it was for academic reasons

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