33 datasets found
  1. Real-Time Market Data & APIs | Databento

    • databento.com
    csv, dbn, json +1
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    Databento, Real-Time Market Data & APIs | Databento [Dataset]. https://databento.com/live
    Explore at:
    json, dbn, csv, parquetAvailable download formats
    Dataset provided by
    Databento Inc.
    Authors
    Databento
    Time period covered
    May 21, 2017 - Present
    Area covered
    Worldwide
    Description

    Leverage Databento's real-time stock API to get tick data with full order book depth (MBO). Offering seamless intraday market replay in a single API call.

  2. S

    Stock Market API Report

    • marketresearchforecast.com
    doc, pdf, ppt
    Updated Apr 24, 2025
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    Market Research Forecast (2025). Stock Market API Report [Dataset]. https://www.marketresearchforecast.com/reports/stock-market-api-534238
    Explore at:
    pdf, doc, pptAvailable download formats
    Dataset updated
    Apr 24, 2025
    Dataset authored and provided by
    Market Research Forecast
    License

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

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global Stock Market API market is experiencing robust growth, driven by the increasing demand for real-time and historical financial data across various sectors. The proliferation of algorithmic trading, quantitative analysis, and the development of sophisticated financial applications are key factors fueling this expansion. The market is segmented by deployment (cloud-based and on-premises) and user type (SMEs and large enterprises), with cloud-based solutions gaining significant traction due to their scalability, cost-effectiveness, and accessibility. Large enterprises, with their extensive data processing needs and investment in advanced analytics, currently dominate the market share, but the SME segment is exhibiting impressive growth potential as access to affordable and user-friendly APIs becomes increasingly widespread. Geographic expansion is also a significant driver, with North America and Europe holding substantial market shares, while Asia-Pacific is emerging as a rapidly growing region fueled by increasing technological adoption and economic expansion. While competitive pressures from numerous providers and data security concerns present some restraints, the overall market outlook remains highly positive, projected to maintain a strong Compound Annual Growth Rate (CAGR) over the forecast period (2025-2033). The competitive landscape is characterized by a diverse range of established players and emerging startups. Established players like Refinitiv and Bloomberg offer comprehensive data solutions, while smaller companies like Alpha Vantage and Marketstack provide specialized APIs focusing on specific data sets or user needs. This competitive environment fosters innovation, driving the development of new features and capabilities within Stock Market APIs. The increasing demand for integrated data solutions—combining market data with alternative data sources—is another key trend shaping the market. Future growth will likely be fueled by the expansion of fintech, the rise of robo-advisors, and increasing adoption of APIs in academic research and financial education. The market's continued evolution necessitates ongoing adaptation and innovation from both established players and new entrants to cater to the evolving needs of a dynamic and technology-driven financial ecosystem. This ongoing innovation and increasing demand will drive the market to significant growth over the next decade.

  3. S

    Stock Market API Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Feb 16, 2025
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    Archive Market Research (2025). Stock Market API Report [Dataset]. https://www.archivemarketresearch.com/reports/stock-market-api-30212
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    doc, pdf, pptAvailable download formats
    Dataset updated
    Feb 16, 2025
    Dataset authored and provided by
    Archive Market Research
    License

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

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The Stock Market API market is projected to experience a remarkable growth trajectory, with a market size of XX million in 2025 and an anticipated CAGR of XX% over the forecast period of 2025-2033. This growth is driven by the increasing demand for real-time and accurate financial data for informed investment decisions, as well as the rise of cloud-based technologies and the proliferation of API-driven applications. Key market trends shaping the Stock Market API landscape include the adoption of advanced technologies such as artificial intelligence (AI) and machine learning (ML) for data analysis and prediction, the growing popularity of mobile trading and fintech applications, and the increasing demand for personalized and tailored financial services. The market is also characterized by a competitive landscape with a wide range of API providers offering diverse data offerings and integration options. Prominent players in the market include Marketstack, Alpha Vantage, Finnhub, Barchart, Financial Modeling Prep, EOD Historical Data, Tiingo, Intrinio, Quandl, Polygon, Alpaca, Yahoo, IEX Cloud, FRED (Federal Reserve Economic Data) API, Ally Invest API, Xignite, Tradier, AlphaSense, Refinitiv Data Platform, E*TRADE, Koyfin, Investopedia, and more.

  4. 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

  5. ETF Market Data & APIs - NYSE Arca Integrated | Databento

    • databento.com
    csv, dbn, json +1
    Updated Jan 18, 2025
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    Databento (2025). ETF Market Data & APIs - NYSE Arca Integrated | Databento [Dataset]. https://databento.com/datasets/ARCX.PILLAR
    Explore at:
    csv, dbn, parquet, jsonAvailable download formats
    Dataset updated
    Jan 18, 2025
    Dataset provided by
    Databento Inc.
    Authors
    Databento
    Time period covered
    May 21, 2017 - Present
    Area covered
    United States
    Description

    Access NYSE Arca Integrated market data feed for ETPs and ETFs with enhanced granularity and determinism not available via the SIPs or the Openbook feed.

    NYSE Arca Integrated is a proprietary data feed that provides full order book updates, including every quote and order at each price level, on the Arca market (formerly ArcaEX, the Archipelago Exchange). It operates on NYSE's Pillar platform and disseminates all order book activity in an order-by-order view of events, including trade executions, order modifications, cancellations, and other book updates.

    NYSE Arca is the leading US exchange for listing and trading exchange-traded funds (ETFs), offering the narrowest quoted spreads and maintaining the highest percentage of time (71.1%) at the NBBO for all U.S. ETFs. As of January 2025, it represented approximately 9.96% of the average daily volume (ADV) across all exchange-listed US securities, including those listed on Nasdaq, other NYSE venues, and Cboe exchanges.

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

    Full depth of book data on Arca is particularly valuable over the SIPs for modeling pre-market, after-market and sweep-to-fill liquidity on U.S. exchange-traded products (ETPs) and ETFs.

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

    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

  6. I

    Global Stock Market API Market Strategic Recommendations 2025-2032

    • statsndata.org
    excel, pdf
    Updated May 2025
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    Stats N Data (2025). Global Stock Market API Market Strategic Recommendations 2025-2032 [Dataset]. https://www.statsndata.org/report/stock-market-api-market-8555
    Explore at:
    pdf, excelAvailable download formats
    Dataset updated
    May 2025
    Dataset authored and provided by
    Stats N Data
    License

    https://www.statsndata.org/how-to-orderhttps://www.statsndata.org/how-to-order

    Area covered
    Global
    Description

    The stock market serves as the backbone of modern economies, facilitating the buying and selling of shares in publicly traded companies. This dynamic marketplace allows investors to own a piece of a company and share in its success, providing essential liquidity and capital for businesses. As a pivotal element in th

  7. d

    Stock Analyst Ratings API by Finnworlds

    • datarade.ai
    Updated Jun 4, 2024
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    Finnworlds (2024). Stock Analyst Ratings API by Finnworlds [Dataset]. https://datarade.ai/data-products/analyst-ratings-api-buy-sell-hold-and-price-consensus-finnworlds
    Explore at:
    Dataset updated
    Jun 4, 2024
    Dataset authored and provided by
    Finnworlds
    Area covered
    Azerbaijan, Saint Pierre and Miquelon, Nigeria, Nauru, Belarus, Bermuda, Tuvalu, Lithuania, Virgin Islands (British), Antarctica
    Description

    You can obtain the data from the Analyst Ratings through our API and databases. It is available through JSON REST API or downloadable as a csv or excel file. We obtain the data from analysts and financial experts in all sectors and industries which we constantly up date as analysts release new reports and statements. We then compile this data in an intuitively API that is easily used by developers to build systems for your platforms and applications.

    Filtering Parameters: - Stock Ticker Symbol - ISIN identifier - Analyst name - Analyst firm - Analyst success rate - Analyst return rate - date ranges from when you want output

    Output example:

    },
    "results": [
      {
      "basics": {
        "name": "Apple Inc",
        "stock_ticker_symbol": "AAPL"
        "isin_identifier": "US0378331005"
        "exchange": "nasdaq"
        },
      "output": {
        "averageRecommendation": {
          "current": "1.33",
          "one_month_ago": "1.29",
          "two_months_ago": "1.35",
          "three_months_ago": "1.35"
        },
        "strongBuy": {
          "current": "18",
          "one_month_ago": "19",
          "two_months_ago": "20",
          "three_months_ago": "20"
        },
        "hold": {
          "current": "2",
          "one_month_ago": "2",
          "two_months_ago": "3",
          "three_months_ago": "3"
        },
        "strongSell": {
          "current": "0",
          "one_month_ago": "0",
          "two_months_ago": "0",
          "three_months_ago": "0"
        }
      }
    

    You can find the detailed documentation on finnworlds.com/documentation. Be sure to let us know you found us through Datarade, which helps this platform in return.

  8. d

    Real-time Candlestick OHLC API

    • datarade.ai
    .json, .csv, .xls
    Updated Sep 27, 2022
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    Finnworlds (2022). Real-time Candlestick OHLC API [Dataset]. https://datarade.ai/data-products/real-time-candlestick-ohlc-api-finnworlds
    Explore at:
    .json, .csv, .xlsAvailable download formats
    Dataset updated
    Sep 27, 2022
    Dataset authored and provided by
    Finnworlds
    Area covered
    Ireland, Denmark, Tajikistan, Gabon, Micronesia (Federated States of), Croatia, South Sudan, Guinea-Bissau, Turkmenistan, Turkey
    Description

    The Real-time Candlestick OHLC API provides current candlestick data that covers all major stock exchanges including NYSE, NASDAQ, LSE, Euronext to NSE of India, TSE, and a few more. Users can choose from candlestick data with 1 min, 2 min, 5 min, 15 min, 30 min, 1 hour, 4 hour, 1 day, 1 week, 1 month and 1 year interval. By using the real-time candlestick OHLC data, they can visualize data on candlestick charts and build financial products.

  9. d

    Africa & Middle East | Insider Trading Data | 25+ Years Historic Data |...

    • datarade.ai
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    Smart Insider, Africa & Middle East | Insider Trading Data | 25+ Years Historic Data | Stock Market Data | Public Equity Market Data for Investment Management [Dataset]. https://datarade.ai/data-products/africa-insider-trading-data-25-years-historic-data-sto-smart-insider
    Explore at:
    .xml, .csv, .xls, .txtAvailable download formats
    Dataset authored and provided by
    Smart Insider
    Area covered
    Africa
    Description

    When there is a vast variety of metrics and tools available to gain market insight, Insider trading offers valuable clues to investors related to future share performance. We at Smart Insider provide global insider trading data and analysis on share transactions made by directors & senior staff in the shares of their own companies.

    Monitoring all the insider trading activity is a huge task, we identify 'Smart Insiders' through specialist desktop and quantitative feeds that enable our clients to generate alpha.

    Our experienced analyst team uses quantitative and qualitative methods to identify the stocks most likely to outperform based on deep analysis of insider trades, and the insiders themselves. Using our easy-to-read derived data we help our clients better understand insider transactions activity to make informed investment decisions.

    We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as XML, XLSX or API via SFTP or Snowflake.

    Sample dataset for Desktop Service has been provided with some proprietary fields concealed. Upon request, we can provide a detailed Quant sample.

    Tags: Stock Market Data, Equity Market Data, Insider Transactions Data, Insider Trading Intelligence, Trading Data, Investment Management, Alternative Investment, Asset Management, Equity Research, Market Analysis, Africa

  10. F

    S&P 500

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

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

    Description

    View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

  11. NYSE Arca Integrated

    • databento.com
    Updated Jan 18, 2025
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    New York Stock Exchange (NYSE) (2025). NYSE Arca Integrated [Dataset]. https://databento.com/datasets/ARCX.PILLAR
    Explore at:
    Dataset updated
    Jan 18, 2025
    Dataset provided by
    NYSE Euronexthttp://www.nyx.com/
    Description

    The NYSE Arca Integrated Feed provides a comprehensive order-by-order view of events in the NYSE Arca equities market. This single high-performance product integrates orders and trades in sequence, providing a more deterministic and transparent view of the order book and related activity.

  12. d

    Africa | Corporate Buyback Data | Transactions and Intentions | 10 Years...

    • datarade.ai
    Updated Feb 15, 2024
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    Smart Insider (2024). Africa | Corporate Buyback Data | Transactions and Intentions | 10 Years Historical Data | Public Equity Market Data | Stock Market Data Africa [Dataset]. https://datarade.ai/data-products/africa-corporate-buyback-data-transactions-and-intentions-smart-insider-455d
    Explore at:
    .xml, .csv, .xls, .txtAvailable download formats
    Dataset updated
    Feb 15, 2024
    Dataset authored and provided by
    Smart Insider
    Area covered
    Maldives, Uganda, Congo (Democratic Republic of the), Mozambique, Ethiopia, Sri Lanka, Ghana, Azerbaijan, Mauritania, Comoros
    Description

    Smart Insider’s Global Share Buyback Database offers invaluable insights to investors on public equity market data. We provide detailed, up-to-date share buyback data covering over 55,000 companies globally including Africa, that’s every company that reports Buybacks through regulatory processes.

    Our Share buyback data includes detailed information on all major buyback transactions including source announcements and derived analysis fields. Our platform adds a visual representation of the data, allowing investors to quickly identify patterns and make decisions based on their findings.

    Get detailed share buyback insights with Smart Insider and stay ahead of the curve with accurate, historical buyback insight that helps you make better investment decisions.

    We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as CSV, XML or XLSX via SFTP, API or Snowflake.

    Sample dataset for Desktop Service has been provided with limited fields. Upon request, we can provide a detailed Quant sample.

    Tags: Equity Market Data, Stock Market Data, Corporate Actions Data, Corporate Buyback Data, Company Financial Data, Insider Trading Data, Africa

  13. API Group Soaring: (APG) Stock Forecast (Forecast)

    • kappasignal.com
    Updated Nov 18, 2024
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    KappaSignal (2024). API Group Soaring: (APG) Stock Forecast (Forecast) [Dataset]. https://www.kappasignal.com/2024/11/api-group-soaring-apg-stock-forecast.html
    Explore at:
    Dataset updated
    Nov 18, 2024
    Dataset authored and provided by
    KappaSignal
    License

    https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html

    Description

    This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

    API Group Soaring: (APG) Stock Forecast

    Financial data:

    • Historical daily stock prices (open, high, low, close, volume)

    • Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

    • Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

    Machine learning features:

    • Feature engineering based on financial data and technical indicators

    • Sentiment analysis data from social media and news articles

    • Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

    Potential Applications:

    • Stock price prediction

    • Portfolio optimization

    • Algorithmic trading

    • Market sentiment analysis

    • Risk management

    Use Cases:

    • Researchers investigating the effectiveness of machine learning in stock market prediction

    • Analysts developing quantitative trading Buy/Sell strategies

    • Individuals interested in building their own stock market prediction models

    • Students learning about machine learning and financial applications

    Additional Notes:

    • The dataset may include different levels of granularity (e.g., daily, hourly)

    • Data cleaning and preprocessing are essential before model training

    • Regular updates are recommended to maintain the accuracy and relevance of the data

  14. f

    Apis Spolka Akcyjna Financial Reports

    • financialreports.eu
    Updated Jan 17, 2025
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    FinancialReports UG (2025). Apis Spolka Akcyjna Financial Reports [Dataset]. https://financialreports.eu/companies/apis-spolka-akcyjna/
    Explore at:
    Dataset updated
    Jan 17, 2025
    Dataset authored and provided by
    FinancialReports UG
    License

    https://financialreports.eu/https://financialreports.eu/

    Time period covered
    2022 - Present
    Description

    Comprehensive collection of financial reports and documents for Apis Spolka Akcyjna (ASA)

  15. LON:API Target Price Prediction (Forecast)

    • kappasignal.com
    Updated Nov 19, 2022
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    KappaSignal (2022). LON:API Target Price Prediction (Forecast) [Dataset]. https://www.kappasignal.com/2022/11/lonapi-target-price-prediction.html
    Explore at:
    Dataset updated
    Nov 19, 2022
    Dataset authored and provided by
    KappaSignal
    License

    https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html

    Description

    This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

    LON:API Target Price Prediction

    Financial data:

    • Historical daily stock prices (open, high, low, close, volume)

    • Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

    • Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

    Machine learning features:

    • Feature engineering based on financial data and technical indicators

    • Sentiment analysis data from social media and news articles

    • Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

    Potential Applications:

    • Stock price prediction

    • Portfolio optimization

    • Algorithmic trading

    • Market sentiment analysis

    • Risk management

    Use Cases:

    • Researchers investigating the effectiveness of machine learning in stock market prediction

    • Analysts developing quantitative trading Buy/Sell strategies

    • Individuals interested in building their own stock market prediction models

    • Students learning about machine learning and financial applications

    Additional Notes:

    • The dataset may include different levels of granularity (e.g., daily, hourly)

    • Data cleaning and preprocessing are essential before model training

    • Regular updates are recommended to maintain the accuracy and relevance of the data

  16. Equities Data & APIs - ETF and Stock Market Data | Databento

    • databento.com
    csv, dbn, json +1
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    Databento, Equities Data & APIs - ETF and Stock Market Data | Databento [Dataset]. https://databento.com/equities
    Explore at:
    csv, json, dbn, parquetAvailable download formats
    Dataset provided by
    Databento Inc.
    Authors
    Databento
    Time period covered
    May 1, 2018 - Present
    Area covered
    United States
    Description

    Download real-time and historical stock price data, including all buy and sell orders at every price level. Get each trade tick-by-tick and order queue composition at all prices. Access high-fidelity US equities stock market data using our Python, Rust, and C++ APIs. Providing full order book depth (MBO), OHLC aggregates, and more.

  17. d

    Historical stock prices | Level 1,2,3 Data and System events

    • datarade.ai
    .json, .csv
    Updated Mar 13, 2025
    + more versions
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    CoinAPI (2025). Historical stock prices | Level 1,2,3 Data and System events [Dataset]. https://datarade.ai/data-products/historical-stock-prices-level-1-2-3-data-and-system-events-coinapi
    Explore at:
    .json, .csvAvailable download formats
    Dataset updated
    Mar 13, 2025
    Dataset provided by
    Coinapi Ltd
    Authors
    CoinAPI
    Area covered
    Libya, Namibia, Peru, Sierra Leone, Thailand, Niue, Bermuda, American Samoa, Germany, Bouvet Island
    Description

    FinFeedAPI provides equity market data covering over 11,000 symbols, featuring historical T+1 data with an unlimited loopback period. We deliver everything from detailed trade records and multiple levels of order book depth (Level 1-3) to crucial regulatory and system messages.

    Our data is engineered for performance, featuring nano-second precision timestamps. This ensures a competitive edge for high-frequency trading by enabling fair, accurate, and auditable transaction sequencing, critical for regulatory compliance. Access comprehensive equity market intelligence directly through our robust API offerings.

    Why FinFeedAPI?

    Market Coverage & Data Depth: - Historical Data: T+1 data on 11K+ symbols with unlimited historical lookback. - Trade Feeds: Detailed trade records including timestamps, sizes, prices, and conditions (e.g., odd lot, intermarket sweep, extended hours). - Level 1 Quotes: Best bid/ask prices, sizes, and timestamps. - Level 2 Price Book: Market depth with multiple bid/ask prices and aggregate order sizes. - Level 3 Order Book: The complete order book detailing individual orders.

    Essential Messages: - Admin Messages: Trading status, official open/close prices, auction states, short sale restrictions, retail liquidity indicators, security directory. - System Events: Exchange-level notifications for key trading session phases.

    Precision & Reliability: - Nano-second Timestamps: Ensuring fair, accurate, and auditable transaction sequencing for HFT and compliance. - Institutional Trust: Relied upon by financial institutions for dependable equity market information.

    Financial institutions and trading firms rely on FinFeedAPI for mission-critical equity market intelligence. We are committed to delivering clean, precise, and comprehensive data when it matters most. If you require dependable and granular stock market data, FinFeedAPI provides the actionable insights you need.

  18. d

    USA & Canada Corporate Buyback Data | Transactions and Intentions | 10 Years...

    • datarade.ai
    Updated Nov 28, 2023
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    Smart Insider (2023). USA & Canada Corporate Buyback Data | Transactions and Intentions | 10 Years Historical Data | 12,200+ companies | Public Equity / Stock Market Data [Dataset]. https://datarade.ai/data-products/usa-canada-corporate-buyback-data-transactions-and-intent-smart-insider
    Explore at:
    .xml, .csv, .xls, .txtAvailable download formats
    Dataset updated
    Nov 28, 2023
    Dataset authored and provided by
    Smart Insider
    Area covered
    United States, Canada
    Description

    Smart Insider’s Global Share Buyback Database offers invaluable insights to investors. We provide detailed, up-to-date share buyback data covering over 55,000 companies globally and over 12,200 from US & Canada (North America), that’s every company that reports Buybacks through regulatory processes.

    Our Share buyback data includes detailed information on all major buyback transactions including source announcements and derived analysis fields. Our platform adds a visual representation of the data, allowing investors to quickly identify patterns and make decisions based on their findings.

    Get detailed share buyback insights with Smart Insider and stay ahead of the curve with accurate, historical buyback insight that helps you make better investment decisions.

    We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as CSV, XML or XLSX via SFTP, API or Snowflake.

    Sample dataset for Desktop Service has been provided with limited fields. Upon request, we can provide a detailed Quant sample.

    Tags: Equity Market Data, Stock Market Data, Corporate Actions Data, Corporate Buyback Data, Company Financial Data, Insider Trading Data

  19. Get small and mid-cap market data with NYSE American Integrated

    • databento.com
    csv, dbn, json
    Updated Jan 15, 2025
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    Databento (2025). Get small and mid-cap market data with NYSE American Integrated [Dataset]. https://databento.com/datasets/XASE.PILLAR
    Explore at:
    csv, dbn, jsonAvailable 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 American Integrated is a proprietary data feed that provides full order book depth, including every quote and order at each price level, on the American market (formerly AMEX, the American Stock Exchange). It operates on NYSE's Pillar platform and disseminates all order book activity in an order-by-order view of events, including trade executions, order modifications, cancellations, and other book updates.

    NYSE American specializes in listing growing companies and is the leading exchange for small-cap stocks, as well as offering mid-cap insights. As of January 2025, it represented approximately 0.23% of the average daily volume (ADV) across all exchange-listed securities.

    With L3 granularity, NYSE American Integrated captures information beyond the L1, top-of-book data available through SIP feeds, enabling accurate modeling of the book imbalances, trade directionality, quote lifetimes, and more. This data includes explicit trade aggressor side, odd lots, and auction imbalances. Auction imbalances offer valuable insights into NYSE American’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, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Imbalance (Learn more)

    Resolution: Immediate publication, nanosecond-resolution timestamps

  20. k

    (API) Abrdn Property Income: Renting Out the Future? (Forecast)

    • kappasignal.com
    Updated Aug 28, 2024
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    KappaSignal (2024). (API) Abrdn Property Income: Renting Out the Future? (Forecast) [Dataset]. https://www.kappasignal.com/2024/08/api-abrdn-property-income-renting-out.html
    Explore at:
    Dataset updated
    Aug 28, 2024
    Dataset authored and provided by
    KappaSignal
    License

    https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html

    Description

    This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

    (API) Abrdn Property Income: Renting Out the Future?

    Financial data:

    • Historical daily stock prices (open, high, low, close, volume)

    • Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

    • Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

    Machine learning features:

    • Feature engineering based on financial data and technical indicators

    • Sentiment analysis data from social media and news articles

    • Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

    Potential Applications:

    • Stock price prediction

    • Portfolio optimization

    • Algorithmic trading

    • Market sentiment analysis

    • Risk management

    Use Cases:

    • Researchers investigating the effectiveness of machine learning in stock market prediction

    • Analysts developing quantitative trading Buy/Sell strategies

    • Individuals interested in building their own stock market prediction models

    • Students learning about machine learning and financial applications

    Additional Notes:

    • The dataset may include different levels of granularity (e.g., daily, hourly)

    • Data cleaning and preprocessing are essential before model training

    • Regular updates are recommended to maintain the accuracy and relevance of the data

Share
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Databento, Real-Time Market Data & APIs | Databento [Dataset]. https://databento.com/live
Organization logo

Real-Time Market Data & APIs | Databento

Real-time stock market API - Access indices data and more

Explore at:
json, dbn, csv, parquetAvailable download formats
Dataset provided by
Databento Inc.
Authors
Databento
Time period covered
May 21, 2017 - Present
Area covered
Worldwide
Description

Leverage Databento's real-time stock API to get tick data with full order book depth (MBO). Offering seamless intraday market replay in a single API call.

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