76 datasets found
  1. 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/

  2. b

    Stock Market Dataset

    • brightdata.com
    .json, .csv, .xlsx
    Updated Feb 5, 2023
    + more versions
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    Bright Data (2023). Stock Market Dataset [Dataset]. https://brightdata.com/products/datasets/financial/stock-market
    Explore at:
    .json, .csv, .xlsxAvailable download formats
    Dataset updated
    Feb 5, 2023
    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.

  3. Stock Market Dataset

    • kaggle.com
    zip
    Updated Apr 2, 2020
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    Oleh Onyshchak (2020). Stock Market Dataset [Dataset]. http://doi.org/10.34740/kaggle/dsv/1054465
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    zip(547714524 bytes)Available download formats
    Dataset updated
    Apr 2, 2020
    Authors
    Oleh Onyshchak
    License

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

    Description

    Overview

    This dataset contains historical daily prices for all tickers currently trading on NASDAQ. The up to date list is available from nasdaqtrader.com. The historic data is retrieved from Yahoo finance via yfinance python package.

    It contains prices for up to 01 of April 2020. If you need more up to date data, just fork and re-run data collection script also available from Kaggle.

    Data Structure

    The date for every symbol is saved in CSV format with common fields:

    • Date - specifies trading date
    • Open - opening price
    • High - maximum price during the day
    • Low - minimum price during the day
    • Close - close price adjusted for splits
    • Adj Close - adjusted close price adjusted for both dividends and splits.
    • Volume - the number of shares that changed hands during a given day

    All that ticker data is then stored in either ETFs or stocks folder, depending on a type. Moreover, each filename is the corresponding ticker symbol. At last, symbols_valid_meta.csv contains some additional metadata for each ticker such as full name.

  4. 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
    Explore at:
    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 .

  5. T

    United States Stock Market Index Data

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +12more
    csv, excel, json, xml
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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 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 27, 2025
    Area covered
    United States
    Description

    The main stock market index of United States, the US500, rose to 6159 points on June 27, 2025, gaining 0.30% from the previous session. Over the past month, the index has climbed 4.60% and is up 12.80% 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.

  6. List of Companies in The New York Stock Exchange

    • johnsnowlabs.com
    csv
    Updated Jan 20, 2021
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    John Snow Labs (2021). List of Companies in The New York Stock Exchange [Dataset]. https://www.johnsnowlabs.com/marketplace/list-of-companies-in-the-new-york-stock-exchange/
    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 NYSE (The New York Stock Exchange).

  7. 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.

  8. Get OHLCV, MBO, equities market events, and more from NYSE Integrated

    • databento.com
    csv, dbn, json
    Updated Jan 15, 2025
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    Databento (2025). Get OHLCV, MBO, equities market events, and more from NYSE Integrated [Dataset]. https://databento.com/datasets/XNYS.PILLAR
    Explore at:
    json, dbn, csvAvailable download formats
    Dataset updated
    Jan 15, 2025
    Dataset provided by
    Databento Inc.
    Authors
    Databento
    Time period covered
    Mar 28, 2023 - Present
    Area covered
    United States
    Description

    NYSE Integrated is a proprietary data feed that disseminates full order book updates from the New York Stock Exchange (XNYS). 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.

    NYSE is the leading venue for listing blue-chip companies and large-cap stocks. Powered by NYSE's Pillar platform, its hybrid market model of floor-based auction and electronic trading allows it to capture a significant portion of trading activity during the US equity market open and close. As of January 2025, the NYSE represented approximately 6.31% of the average daily volume (ADV) across all exchange-listed US securities, including those listed on Nasdaq, other NYSE venues, and Cboe exchanges.

    NYSE is also the only exchange to offer Designated Market Maker (DMM) privileges, allowing the floor to send D-Quote Orders, short for Discretionary Orders, throughout the day. Most D-Quote Orders execute in the closing auction, where they're known as Closing D Orders and allow traders to access the NYSE closing auction after 3:50 PM. This creates significant price discovery during the NYSE Closing Auction, where interest represented via the floor contributes more than 40% of total volume.

    NYSE is also unique for being the only exchange with a Parity/Priority Allocation model for matching. This resembles a mixed FIFO and pro-rata matching algorithm, where the participant who sets the best price is matched first, and then the remaining shares are allocated to other orders entered by floor brokers at that price (parity allocation). Floor brokers may utilize e-Quotes to to receive such parity allocation of incoming executions.

    With L3 granularity, NYSE Integrated captures information beyond the L1, top-of-book data available through SIP feeds, enabling accurate modeling of the book imbalances, queue dynamics, and the auction process. This data includes explicit trade aggressor side, odd lots, and imbalances. Auction imbalances offer valuable insights into NYSE’s opening and closing auctions by providing details like imbalance quantity, paired quantity, imbalance reference price, and book clearing price.

    Historical data is available for usage-based rates or with any Databento US Equities subscription. Visit our pricing page for more details or to upgrade your plan.

    Asset class: 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, TBBO, Trades, BBO-1s, BBO-1m, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Imbalance, Statistics, Status (Learn more)

    Resolution: Immediate publication, nanosecond-resolution timestamps

  9. 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
    Bermuda, Guatemala, Belize, Honduras, United States of America, El Salvador, Panama, Mexico, Greenland, Saint Pierre and Miquelon, 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.

  10. 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
    Macao, Kyrgyzstan, Korea (Democratic People's Republic of), Cyprus, Nepal, Uzbekistan, Maldives, Vietnam, Indonesia, Malaysia, 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.

  11. Nasdaq Listed Companies

    • financialreports.eu
    Updated Jul 21, 2023
    + more versions
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    Nasdaq (2023). Nasdaq Listed Companies [Dataset]. https://financialreports.eu/companies/exchanges/nasdaq/
    Explore at:
    Dataset updated
    Jul 21, 2023
    Dataset authored and provided by
    Nasdaqhttp://www.nasdaq.com/
    Time period covered
    1971 - Present
    Variables measured
    Trading Hours, Trading Volume, Listed Companies, Market Capitalization
    Description

    Comprehensive dataset of 5 companies listed on Nasdaq, 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.

  12. 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
    Explore at:
    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.

  13. Slovenia SI: No of Listed Domestic Companies: Total

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Slovenia SI: No of Listed Domestic Companies: Total [Dataset]. https://www.ceicdata.com/en/slovenia/financial-sector/si-no-of-listed-domestic-companies-total
    Explore at:
    Dataset updated
    Jan 15, 2025
    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, 2011 - Dec 1, 2022
    Area covered
    Slovenia
    Variables measured
    Turnover
    Description

    Slovenia SI: Number of Listed Domestic Companies: Total data was reported at 24.000 Unit in 2022. This records a decrease from the previous number of 25.000 Unit for 2021. Slovenia SI: Number of Listed Domestic Companies: Total data is updated yearly, averaging 63.500 Unit from Dec 1993 (Median) to 2022, with 30 observations. The data reached an all-time high of 151.000 Unit in 2001 and a record low of 16.000 Unit in 1993. Slovenia SI: 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 Slovenia – Table SI.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.

  14. Austria AT: No of Listed Domestic Companies: Total

    • ceicdata.com
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    CEICdata.com, Austria AT: No of Listed Domestic Companies: Total [Dataset]. https://www.ceicdata.com/en/austria/financial-sector/at-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, 2011 - Dec 1, 2022
    Area covered
    Austria
    Variables measured
    Turnover
    Description

    Austria AT: Number of Listed Domestic Companies: Total data was reported at 66.000 Unit in 2022. This records a decrease from the previous number of 69.000 Unit for 2021. Austria AT: Number of Listed Domestic Companies: Total data is updated yearly, averaging 83.000 Unit from Dec 1975 (Median) to 2022, with 48 observations. The data reached an all-time high of 112.000 Unit in 1992 and a record low of 62.000 Unit in 1983. Austria AT: 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 Austria – Table AT.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.

  15. f

    London Stock Exchange Listed Companies

    • financialreports.eu
    Updated Jan 1, 2024
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    London Stock Exchange (2024). London Stock Exchange Listed Companies [Dataset]. https://financialreports.eu/companies/exchanges/london-stock-exchange/
    Explore at:
    Dataset updated
    Jan 1, 2024
    Dataset authored and provided by
    London Stock Exchange
    Time period covered
    1801 - Present
    Area covered
    London
    Variables measured
    Trading Hours, Trading Volume, Listed Companies, Market Capitalization
    Description

    Comprehensive dataset of 1481 companies listed on London Stock Exchange, 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 London Stock Exchange.

  16. d

    Yacodata: S&P 500 Companies Data (up-to-date intelligence on US largest 500...

    • datarade.ai
    .csv
    Updated May 23, 2021
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    Yacodata (2021). Yacodata: S&P 500 Companies Data (up-to-date intelligence on US largest 500 companies) [Dataset]. https://datarade.ai/data-products/s-p500-companies-informations-up-to-date-yacodata
    Explore at:
    .csvAvailable download formats
    Dataset updated
    May 23, 2021
    Dataset authored and provided by
    Yacodata
    Area covered
    United States
    Description

    The dataset consists of companies listed in the S&P500, stock market index that measures the stock performance of 500 large companies listed on stock exchanges in the United State.

    The S&P 500 stock market index, maintained by S&P Dow Jones Indices, comprises 505 common stocks issued by 500 large-cap companies and traded on American stock exchanges (including the 30 companies that compose the Dow Jones Industrial Average)

    The S&P500 or SPX is the most commonly followed equity index, it covers about 80 percent of the American equity market by capitalization.

    The index constituents and the constituent weights are updated regularly using rules published by S&P Dow Jones Indices. Although called the S&P 500, the index contains 505 stocks

  17. Stock Market Data Europe ( End of Day Pricing dataset )

    • datarade.ai
    Updated Aug 24, 2023
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    Techsalerator (2023). Stock Market Data Europe ( End of Day Pricing dataset ) [Dataset]. https://datarade.ai/data-products/stock-market-data-europe-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
    Lithuania, Slovenia, Italy, Andorra, Latvia, Croatia, Switzerland, Belgium, Denmark, Finland, Europe
    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.

  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 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
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    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 ...

  20. 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
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    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.

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xNezumi (2024). Nasdaq Stock Market Data [Dataset]. https://www.kaggle.com/datasets/xnezumi/nasdaq-stock-market-data
Organization logo

Nasdaq Stock Market Data

Historical stock market data for 4500+ Nasdaq listed companies

Explore at:
30 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
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/

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