100+ datasets found
  1. 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.

  2. T

    United States Stock Market Index Data

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +12more
    csv, excel, json, xml
    Updated May 15, 2025
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    TRADING ECONOMICS (2025). United States Stock Market Index Data [Dataset]. https://tradingeconomics.com/united-states/stock-market
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    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 - Jun 9, 2025
    Area covered
    United States
    Description

    The main stock market index of United States, the US500, rose to 6008 points on June 9, 2025, gaining 0.13% from the previous session. Over the past month, the index has climbed 2.80% and is up 12.07% 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 June of 2025.

  3. Nasdaq Stock Market Data

    • kaggle.com
    Updated Aug 5, 2024
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    xNezumi (2024). Nasdaq Stock Market Data [Dataset]. https://www.kaggle.com/datasets/xnezumi/nasdaq-stock-market-data
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 5, 2024
    Dataset provided by
    Kaggle
    Authors
    xNezumi
    License

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

    Description

    Description

    Historical daily stock market data for 4500+ Nasdaq listed companies. Dataset to be updated quarterly.


    Content

    Date: dates vary depending on stock, all in DD/MM/YYYY format Open: open price (in USD) High: high price (in USD) Low: low price (in USD) Close: close price (in USD) Adj close: adjusted close price (in USD) Volume: traded volume (in USD)


    Acknowledgements:

    Banner photo: https://www.pexels.com/photo/numbers-on-monitor-534216/

  4. b

    Stock Market Dataset

    • brightdata.com
    .json, .csv, .xlsx
    Updated Jun 9, 2025
    + more versions
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    Bright Data (2025). Stock Market Dataset [Dataset]. https://brightdata.com/products/datasets/financial/stock-market
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    .json, .csv, .xlsxAvailable download formats
    Dataset updated
    Jun 9, 2025
    Dataset authored and provided by
    Bright Data
    License

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

    Area covered
    Worldwide
    Description

    Use our Stock Market 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.

  5. w

    Dataset of stocks listed on the NASDAQ Sector Indices

    • workwithdata.com
    Updated Apr 11, 2025
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    Work With Data (2025). Dataset of stocks listed on the NASDAQ Sector Indices [Dataset]. https://www.workwithdata.com/datasets/stocks?f=1&fcol0=exchange&fop0=%3D&fval0=NASDAQ+Sector+Indices
    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 17 rows and is filtered where the exchange is NASDAQ Sector Indices. It features 8 columns including stock name, company, exchange, and exchange symbol.

  6. List of Companies in NASDAQ Exchanges

    • johnsnowlabs.com
    csv
    Updated Jan 20, 2021
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    John Snow Labs (2021). List of Companies in NASDAQ Exchanges [Dataset]. https://www.johnsnowlabs.com/marketplace/list-of-companies-in-nasdaq-exchanges/
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jan 20, 2021
    Dataset authored and provided by
    John Snow Labs
    Area covered
    N/A
    Description

    This dataset contains a detailed information on companies listed in the NASDAQ exchanges. The dataset also includes the market category as well as the financial status of the listed companies.

  7. d

    Stock Market Data North America ( End of Day Pricing dataset )

    • datarade.ai
    Updated Aug 24, 2023
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    Techsalerator (2023). Stock Market Data North America ( End of Day Pricing dataset ) [Dataset]. https://datarade.ai/data-products/stock-market-data-north-america-end-of-day-pricing-dataset-techsalerator
    Explore at:
    .json, .csv, .xls, .txtAvailable download formats
    Dataset updated
    Aug 24, 2023
    Dataset authored and provided by
    Techsalerator
    Area covered
    Greenland, Honduras, Belize, United States of America, Mexico, Bermuda, El Salvador, Saint Pierre and Miquelon, Guatemala, Panama, North America
    Description

    End-of-day prices refer to the closing prices of various financial instruments, such as equities (stocks), bonds, and indices, at the end of a trading session on a particular trading day. These prices are crucial pieces of market data used by investors, traders, and financial institutions to track the performance and value of these assets over time. The Techsalerator closing prices dataset is considered the most up-to-date, standardized valuation of a security trading commences again on the next trading day. This data is used for portfolio valuation, index calculation, technical analysis and benchmarking throughout the financial industry. The End-of-Day Pricing service covers equities, equity derivative bonds, and indices listed on 170 markets worldwide.

  8. United States US: Stocks Traded: Total Value

    • ceicdata.com
    Updated Mar 15, 2023
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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
    Mar 15, 2023
    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.

  9. Stock Market Dataset (NIFTY-500)

    • kaggle.com
    Updated Jun 10, 2023
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    Sourav Banerjee (2023). Stock Market Dataset (NIFTY-500) [Dataset]. https://www.kaggle.com/datasets/iamsouravbanerjee/nifty500-stocks-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 10, 2023
    Dataset provided by
    Kaggle
    Authors
    Sourav Banerjee
    Description

    Context

    NIFTY 500 is India’s first broad-based stock market index of the Indian stock market. It contains the top 500 listed companies on the NSE. The NIFTY 500 index represents about 96.1% of free-float market capitalization and 96.5% of the total turnover on the National Stock Exchange (NSE).

    NIFTY 500 companies are disaggregated into 72 industry indices. Industry weights in the index reflect industry weights in the market. For example, if the banking sector has a 5% weight in the universe of stocks traded on the NSE, banking stocks in the index would also have an approximate representation of 5% in the index. NIFTY 500 can be used for a variety of purposes such as benchmarking fund portfolios, launching index funds, ETFs, and other structured products.

    • Other Notable Indices -
      • NIFTY 50: Top 50 listed companies on the NSE. A diversified 50-stock index accounting for 13 sectors of the Indian economy.
      • NIFTY Next 50: Also called NIFTY Juniors. Represents 50 companies from NIFTY 100 after excluding the NIFTY 50 companies.
      • NIFTY 100: Diversified 100 stock index representing major sectors of the economy. NIFTY 100 represents the top 100 companies based on full market capitalization from NIFTY 500.
      • NIFTY 200: Designed to reflect the behavior and performance of large and mid-market capitalization companies.

    Content

    The dataset comprises various parameters and features for each of the NIFTY 500 Stocks, including Company Name, Symbol, Industry, Series, Open, High, Low, Previous Close, Last Traded Price, Change, Percentage Change, Share Volume, Value in Indian Rupee, 52 Week High, 52 Week Low, 365 Day Percentage Change, and 30 Day Percentage Change.

    Dataset Glossary (Column-Wise)

    Company Name: Name of the Company.

    Symbol: A stock symbol is a unique series of letters assigned to a security for trading purposes.

    Industry: Name of the industry to which the stock belongs.

    Series: EQ stands for Equity. In this series intraday trading is possible in addition to delivery and BE stands for Book Entry. Shares falling in the Trade-to-Trade or T-segment are traded in this series and no intraday is allowed. This means trades can only be settled by accepting or giving the delivery of shares.

    Open: It is the price at which the financial security opens in the market when trading begins. It may or may not be different from the previous day's closing price. The security may open at a higher price than the closing price due to excess demand for the security.

    High: It is the highest price at which a stock is traded during the course of the trading day and is typically higher than the closing or equal to the opening price.

    Low: Today's low is a security's intraday low trading price. Today's low is the lowest price at which a stock trades over the course of a trading day.

    Previous Close: The previous close almost always refers to the prior day's final price of a security when the market officially closes for the day. It can apply to a stock, bond, commodity, futures or option co-contract, market index, or any other security.

    Last Traded Price: The last traded price (LTP) usually differs from the closing price of the day. This is because the closing price of the day on NSE is the weighted average price of the last 30 mins of trading. The last traded price of the day is the actual last traded price.

    Change: For a stock or bond quote, change is the difference between the current price and the last trade of the previous day. For interest rates, change is benchmarked against a major market rate (e.g., LIBOR) and may only be updated as infrequently as once a quarter.

    Percentage Change: Take the selling price and subtract the initial purchase price. The result is the gain or loss. Take the gain or loss from the investment and divide it by the original amount or purchase price of the investment. Finally, multiply the result by 100 to arrive at the percentage change in the investment.

    Share Volume: Volume is an indicator that means the total number of shares that have been bought or sold in a specific period of time or during the trading day. It will also involve the buying and selling of every share during a specific time period.

    Value (Indian Rupee): Market value—also known as market cap—is calculated by multiplying a company's outstanding shares by its current market price.

    52-Week High: A 52-week high is the highest share price that a stock has traded at during a passing year. Many market aficionados view the 52-week high as an important factor in determining a stock's current value and predicting future price movement. 52-week High prices are adjusted for Bonus, Split & Rights Corporate actions.

    52-Week Low: A 52-week low is the lowest ...

  10. Nasdaq Iceland Listed Companies

    • financialreports.eu
    Updated Dec 28, 2023
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    Nasdaq Iceland (2023). Nasdaq Iceland Listed Companies [Dataset]. https://financialreports.eu/companies/exchanges/nasdaq-iceland/
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    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Nasdaqhttp://www.nasdaq.com/
    Authors
    Nasdaq Iceland
    Time period covered
    1985 - Present
    Area covered
    Iceland
    Variables measured
    Trading Hours, Trading Volume, Listed Companies, Market Capitalization
    Description

    Comprehensive dataset of 28 companies listed on Nasdaq Iceland, including detailed financial information, market data, and corporate filings. This dataset provides real-time updates on trading metrics, company profiles, financial statements, regulatory filings, and market performance indicators. Updated every 30 minutes, it covers key data points such as market capitalization, trading volume, stock prices, company fundamentals, and regulatory compliance information for all listed securities on Nasdaq Iceland.

  11. Stock Market Data Asia ( End of Day Pricing dataset )

    • datarade.ai
    Updated Aug 24, 2023
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    Techsalerator (2023). Stock Market Data Asia ( End of Day Pricing dataset ) [Dataset]. https://datarade.ai/data-products/stock-market-data-asia-end-of-day-pricing-dataset-techsalerator
    Explore at:
    .json, .csv, .xls, .txtAvailable download formats
    Dataset updated
    Aug 24, 2023
    Dataset provided by
    Techsalerator LLC
    Authors
    Techsalerator
    Area covered
    Korea (Democratic People's Republic of), Vietnam, Uzbekistan, Maldives, Macao, Nepal, Malaysia, Kyrgyzstan, Cyprus, Indonesia, Asia
    Description

    End-of-day prices refer to the closing prices of various financial instruments, such as equities (stocks), bonds, and indices, at the end of a trading session on a particular trading day. These prices are crucial pieces of market data used by investors, traders, and financial institutions to track the performance and value of these assets over time. The Techsalerator closing prices dataset is considered the most up-to-date, standardized valuation of a security trading commences again on the next trading day. This data is used for portfolio valuation, index calculation, technical analysis and benchmarking throughout the financial industry. The End-of-Day Pricing service covers equities, equity derivative bonds, and indices listed on 170 markets worldwide.

  12. United States US: No of Listed Domestic Companies: Total

    • ceicdata.com
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    CEICdata.com, United States US: No of Listed Domestic Companies: Total [Dataset]. https://www.ceicdata.com/en/united-states/financial-sector/us-no-of-listed-domestic-companies-total
    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: Number of Listed Domestic Companies: Total data was reported at 4,336.000 Unit in 2017. This records an increase from the previous number of 4,331.000 Unit for 2016. United States US: Number of Listed Domestic Companies: Total data is updated yearly, averaging 5,930.000 Unit from Dec 1980 (Median) to 2017, with 38 observations. The data reached an all-time high of 8,090.000 Unit in 1996 and a record low of 4,102.000 Unit in 2012. United States US: Number of Listed Domestic Companies: Total 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. Listed domestic companies, including foreign companies which are exclusively listed, are those which have shares listed on an exchange at the end of the year. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status, are excluded. A company with several classes of shares is counted once. Only companies admitted to listing on the exchange are included.; ; 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. Nasdaq Stock Market Data (Nasdaq TotalView-ITCH feed)

    • databento.com
    csv, dbn, json
    Updated Jan 14, 2025
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    Databento (2025). Nasdaq Stock Market Data (Nasdaq TotalView-ITCH feed) [Dataset]. https://databento.com/datasets/XNAS.ITCH
    Explore at:
    dbn, json, csvAvailable download formats
    Dataset updated
    Jan 14, 2025
    Dataset provided by
    Databento Inc.
    Authors
    Databento
    Time period covered
    May 1, 2018 - Present
    Area covered
    United States
    Description

    Get Nasdaq real-time and historical data with support for fast market replay at over 19 million book updates per second. Test our data for free with only 4 lines of code.

    Nasdaq TotalView-ITCH is a proprietary data feed that disseminates full order book depth and last sale data from the Nasdaq stock market (XNAS). It delivers every quote and order at each price level, along with any event that updates the order book after an order is placed, such as trade executions, modifications, or cancellations. Nasdaq is the most active US equity exchange by volume and represented 13.03% of the average daily volume (ADV) as of January 2025.

    With its L3 granularity, Nasdaq TotalView-ITCH captures information beyond the L1, top-of-book data available through SIP feeds and enables more accurate modeling of book imbalances, trade directionality, quote lifetimes, and more. This includes explicit trade aggressor side, odd lots, auction imbalance data, and the Net Order Imbalance Indicator (NOII) for the Nasdaq Opening and Closing Crosses and Nasdaq IPO/Halt Cross—the best predictor of Nasdaq opening and closing prices available. Other key advantages of Nasdaq TotalView-ITCH over SIP data include faster real-time dissemination and precise exchange-side timestamping directly from Nasdaq.

    Real-time Nasdaq TotalView-ITCH data is included with a Plus or Unlimited subscription through our Databento US Equities service. Historical data is available for usage-based rates or with any subscription. Visit our pricing page for more details or to upgrade your plan.

    Breadth of coverage: 20,329 products

    Asset class(es): Equities

    Origin: Directly captured at Equinix NY4 (Secaucus, NJ) with an FPGA-based network card and hardware timestamping. Synchronized to UTC with PTP.

    Supported data encodings: DBN, CSV, JSON Learn more

    Supported market data schemas: MBO, MBP-1, MBP-10, BBO-1s, BBO-1m, TBBO, Trades, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Statistics, Status, Imbalance Learn more

    Resolution: Immediate publication, nanosecond-resolution timestamps

  14. T

    United States Stock Market Index Data

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +4more
    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=ffhqvnvmn5dloatmoocabw&ved=0cjmbebywfq&usg=afqjcngzbcc8p0owixmdsdjcu_endviwgg
    Explore at:
    csv, json, excel, 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 - Jun 6, 2025
    Area covered
    United States
    Description

    The main stock market index of United States, the US500, rose to 6000 points on June 6, 2025, gaining 1.03% from the previous session. Over the past month, the index has climbed 6.55% and is up 12.22% 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 June of 2025.

  15. Nasdaq Basic + Nasdaq Last Sale (NLS) Plus Data Feed

    • databento.com
    csv, dbn, json
    Updated Jan 14, 2025
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    Databento (2025). Nasdaq Basic + Nasdaq Last Sale (NLS) Plus Data Feed [Dataset]. https://databento.com/datasets/XNAS.BASIC
    Explore at:
    dbn, csv, jsonAvailable download formats
    Dataset updated
    Jan 14, 2025
    Dataset provided by
    Databento Inc.
    Authors
    Databento
    Time period covered
    Jul 1, 2024 - Present
    Area covered
    United States
    Description

    Nasdaq Basic with NLS Plus is our most cost-effective solution for real-time US equities, offering the broadest coverage and added granularity—such as trade aggressor side—for a fraction of the cost of consolidated feed alternatives like SIP data.

    This proprietary, consolidated data feed disseminates top-of-book (L1) data from every Nasdaq-operated venue and covers all US stocks and ETFs, including those listed on the NYSE, NYSE Arca, NYSE American, and Cboe exchanges. As the premium tier of Nasdaq's Basic product, it combines Nasdaq Last Sale (NLS) Plus and Nasdaq BBO (QBBO) to provide: - Best bid and offer (BBO) quotes for the Nasdaq stock market (XNAS), which are within 1% of the NBBO 99.22% of the time. - Tick-by-tick price and size for orders executed on Nasdaq (XNAS), Nasdaq BX (XBOS), and Nasdaq PSX (XPSX). - All off-exchange trades reported to FINRA/Nasdaq's Carteret and Chicago Trade Reporting Facilities (TRFs), which aggregate data from most of the 30 ATSs and account for approximately 45% to 49% of the average daily volume (ADV) in all exchange-listed securities.

    With the addition of TRF data, Nasdaq Basic with NLS Plus captures the majority of the trading activity and liquidity within US equity markets. As of January 2025, this dataset represented 62.9% ADV, including both on-exchange and off-exchange trades.

    This dataset is an ideal choice for market participants who need an accurate BBO but don't directly execute trades or display quotes for FINRA broker-dealer obligations. It also features substantially lower exchange license fees for real-time data compared to Nasdaq TotalView-ITCH, with pricing designed for distribution use cases and per-user rates that are reduced by more than 65%.

    Real-time Nasdaq Basic with NLS Plus data is included with a Plus or Unlimited subscription through our Databento US Equities service. Historical data is available for usage-based rates or with any subscription. Visit our pricing page for more details.

    Breadth of coverage: 11,595 products

    Asset class(es): Equities

    Origin: Directly captured at Equinix NY4 (Secaucus, NJ) with an FPGA-based network card and hardware timestamping. Synchronized to UTC with PTP.

    Supported data encodings: DBN, CSV, JSON Learn more

    Supported market data schemas: MBP-1, TBBO, Trades, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Statistics Learn more

    Resolution: Immediate publication, nanosecond-resolution timestamps

  16. o

    Listed Companies in Amman Stock Market - Dataset - Open Government Data

    • opendata.gov.jo
    Updated Feb 18, 2020
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    (2020). Listed Companies in Amman Stock Market - Dataset - Open Government Data [Dataset]. https://opendata.gov.jo/dataset/listed-companies-in-amman-stock-market-364-2020
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    Dataset updated
    Feb 18, 2020
    Description

    this group contains a list of listed companies in Amman stock exchange and their sector , .symbol, code , market and number of shares .

  17. Nifty 50 Stock Market Dataset (2018-2023)

    • kaggle.com
    Updated Aug 5, 2023
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    Aamir Kalimi (2023). Nifty 50 Stock Market Dataset (2018-2023) [Dataset]. https://www.kaggle.com/datasets/codekalimi/nifty-50-2018-2023
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 5, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Aamir Kalimi
    License

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

    Description

    This dataset contains a comprehensive collection of historical data for the Nifty 50 stocks, a diversified stock market index in India. The data covers the period from January 2018 to August 2023, providing valuable insights into the performance of the Indian stock market over the years.

    Features: - Stock Symbol: The unique stock symbol of the company listed in the Nifty 50 index - Date: The date of the stock market data. - Open: The opening price of the stock on the given date. - High: The highest price reached by the stock during the trading session. - Low: The lowest price reached by the stock during the trading session. - Close: The closing price of the stock on the given date. - Volume: The trading volume of the stock on the given date.

  18. AMEX, NYSE, NASDAQ stock histories

    • kaggle.com
    Updated Jul 4, 2020
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    Jiun Yen (2020). AMEX, NYSE, NASDAQ stock histories [Dataset]. https://www.kaggle.com/qks1lver/amex-nyse-nasdaq-stock-histories/home
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 4, 2020
    Dataset provided by
    Kaggle
    Authors
    Jiun Yen
    License

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

    Description

    AMEX, NYSE, and NASDAQ stocks histories

    Update every Satur... Sun... I mean Friday... >_< sometime during the weekend. I lied, I've been too busy the past few months and haven't updated in forever until today (2020.6.14) - Last scrape 2020.06.12 Friday evening (p.s. Download shows 3GB unzipped, zipped file is ~600MB)

    Full history of stock symbols:

    • Unzip fh_< version_date >.zip
    • Each stock symbol has a .csv file under full_history/
      • i.e. AMD.csv
    • Columns in .csv
      • date - year-month-day, 2018-08-08
      • volume - int, volume of the day
      • open - float, opening price of the day
      • close - float, closing price of the day
      • high - float, highest price of the day
      • low - float, lowest price of the day
      • adjclose - float, adjusted closing price of the day

    Other files:

    • all_symbols.txt - All the stock symbols with history
    • excluded_symbols.txt - All the ones that I couldn't retrieve data for
    • NASDAQ.txt - NASDAQ listing
    • NYSE.txt - NYSE listing
    • AMEX.txt - AMEX listing

    Disclaimer

    This dataset contains almost all the stocks listed on these exchanges as of the date shown in the file name. Some of the symbols cannot be found on Yahoo Finance, which I plan on using CNN Money to scrape. There are other symbols that have different classes that require some modification before I can make them queryable... I have yet to decide on the best course of action. If you want to know what these excluded symbols are, see excluded_symbols.txt.

    Note: there used to be some tickers missing because of poor connection, that's been solved now.

    I've also been asked why I don't put everything into one table, and here's my rationale (copy/pasted from my email):

    It is possible and I've debated this before, but I've decided to go with individual files for quite a number of reasons, and I highly recommend you consider these before combining them: 1) I don't need to load everything into memory or search for the right rows if I only want to work with particular sets, 2) easier and faster to manipulate (append, remove, or whatever) when all the data of a ticker is in the same place, 3) I don't need to repeat ticker names for each row just to know which row belongs to which ticker, 4) reduce risk, latency, and waits during parallel processing of different ticker data, 5) in case of any unforeseen bad writes or termination, this way reduces the chances of affecting the entire dataset and allows for restart anytime without the need to keep backup things up every 5 minutes. I get all these benefits only at the cost of slightly larger compressed file and a few more lines of code. To me it's worth it, but I can understand if you are frustrated, but it is possible to concatenate everything.

    Github - for you to DIY:

    https://github.com/qks1lver/redtide

    Data source

    Listing files (i.e. NYSE.txt) are from http://eoddata.com/symbols.aspx

    Daily historical data compiled from Yahoo Finance

    Need someone to talk to?

    If you have questions, e-mail me: jiunyyen@gmail.com

    Happy mining!

  19. Stock market statistics, Canada and United States, Bank of Canada

    • ouvert.canada.ca
    • data.urbandatacentre.ca
    • +3more
    csv, html, xml
    Updated Jan 17, 2023
    + more versions
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    Statistics Canada (2023). Stock market statistics, Canada and United States, Bank of Canada [Dataset]. https://ouvert.canada.ca/data/dataset/e037b4dd-4c13-4cc2-b8c4-0262083dbbd0
    Explore at:
    csv, xml, htmlAvailable download formats
    Dataset updated
    Jan 17, 2023
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Area covered
    Canada, United States
    Description

    This table contains 14 series, with data starting from 1953 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Stock market statistics (14 items: Toronto Stock Exchange; value of shares traded; United States common stocks; Dow-Jones industrials; high; United States common stocks; Dow-Jones industrials; low; Toronto Stock Exchange; volume of shares traded ...).

  20. Denmark Number of Listed Company: OMX Copenhagen Stock Exchange

    • ceicdata.com
    Updated Feb 3, 2018
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    CEICdata.com (2018). Denmark Number of Listed Company: OMX Copenhagen Stock Exchange [Dataset]. https://www.ceicdata.com/en/denmark/nasdaq-copenhagen-number-of-listed-companies
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    Dataset updated
    Feb 3, 2018
    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
    Jan 1, 2024 - Dec 1, 2024
    Area covered
    Denmark
    Variables measured
    Number of Listed Companies
    Description

    Number of Listed Company: OMX Copenhagen Stock Exchange data was reported at 119.000 Unit in Mar 2025. This records a decrease from the previous number of 120.000 Unit for Feb 2025. Number of Listed Company: OMX Copenhagen Stock Exchange data is updated monthly, averaging 174.000 Unit from Feb 2000 (Median) to Mar 2025, with 302 observations. The data reached an all-time high of 261.000 Unit in Jun 2000 and a record low of 119.000 Unit in Mar 2025. Number of Listed Company: OMX Copenhagen Stock Exchange data remains active status in CEIC and is reported by Nasdaq Copenhagen. The data is categorized under Global Database’s Denmark – Table DK.Z002: Nasdaq Copenhagen: Number of Listed Companies.

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Nikita Manaenkov (2025). Stock Portfolio Data with Prices and Indices [Dataset]. http://doi.org/10.34740/kaggle/dsv/11140976
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Stock Portfolio Data with Prices and Indices

Comprehensive Dataset of Stock Portfolio, Historical Prices, and Major US Market

Explore at:
2 scholarly articles cite this dataset (View in Google Scholar)
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.

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