100+ datasets found
  1. o

    IvyDB Signed Volume - Daily Options Trading Volume Data

    • optionmetrics.com
    Updated Nov 15, 2023
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    OptionMetrics (2023). IvyDB Signed Volume - Daily Options Trading Volume Data [Dataset]. https://optionmetrics.com/
    Explore at:
    Dataset updated
    Nov 15, 2023
    Dataset authored and provided by
    OptionMetrics
    License

    https://optionmetrics.com/contact/https://optionmetrics.com/contact/

    Time period covered
    Jan 1, 2016 - Present
    Description

    The IvyDB Signed Volume dataset, available as an add-on product for IvyDB US, contains daily data on detailed option trading volume. Trades in the IvyDB US dataset are assigned as either buyer-initiated or seller-initiated based on the trade price and the bid-ask quote at the time of the trade. The total assigned daily volume is aggregated and updated nightly.

  2. o

    Free Data

    • optiondata.org
    Updated Sep 3, 2022
    + more versions
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    (2022). Free Data [Dataset]. https://optiondata.org/
    Explore at:
    Dataset updated
    Sep 3, 2022
    License

    https://optiondata.org/about.htmlhttps://optiondata.org/about.html

    Time period covered
    Jan 1, 2013 - Jun 30, 2013
    Description

    Free historical options data, dataset files in CSV format.

  3. o

    Datasets in the last 24 years

    • optiondata.org
    Updated Sep 3, 2022
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    (2022). Datasets in the last 24 years [Dataset]. https://optiondata.org/
    Explore at:
    Dataset updated
    Sep 3, 2022
    License

    https://optiondata.org/about.htmlhttps://optiondata.org/about.html

    Time period covered
    May 1, 2002 - Present
    Description

    Historical option data in the last 24 years, dataset files in CSV format.

  4. d

    Historical volatility time series and Live prices on Equity Options

    • datarade.ai
    Updated Mar 9, 2023
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    Canari (2023). Historical volatility time series and Live prices on Equity Options [Dataset]. https://datarade.ai/data-products/historical-volatility-time-series-and-live-prices-on-equity-o-canari
    Explore at:
    Dataset updated
    Mar 9, 2023
    Dataset authored and provided by
    Canari
    Area covered
    Belgium, Sweden, Spain, United Kingdom, Switzerland, Italy, Netherlands, France, Germany, Norway
    Description

    This dataset offers both live (delayed) prices and End Of Day time series on equity options

    1/ Live (delayed) prices for options on European stocks and indices including: Reference spot price, bid/ask screen price, fair value price (based on surface calibration), implicit volatility, forward Greeks : delta, vega Canari.dev computes AI-generated forecast signals indicating which option is over/underpriced, based on the holders strategy (buy and hold until maturity, 1 hour to 2 days holding horizon...). From these signals is derived a "Canari price" which is also available in this live tables.
    Visit our website (canari.dev ) for more details about our forecast signals.

    The delay ranges from 15 to 40 minutes depending on underlyings.

    2/ Historical time series: Implied vol Realized vol Smile Forward
    See a full API presentation here : https://youtu.be/qitPO-SFmY4 .

    These data are also readily accessible in Excel thanks the provided Add-in available on Github: https://github.com/canari-dev/Excel-macro-to-consume-Canari-API

    If you need help, contact us at: contact@canari.dev

    User Guide: You can get a preview of the API by typing "data.canari.dev" in your web browser. This will show you a free version of this API with limited data.

    Here are examples of possible syntaxes:

    For live options prices: data.canari.dev/OPT/DAI data.canari.dev/OPT/OESX/0923 The "csv" suffix to get a csv rather than html formating, for example: data.canari.dev/OPT/DB1/1223/csv For historical parameters: Implied vol : data.canari.dev/IV/BMW

    data.canari.dev/IV/ALV/1224

    data.canari.dev/IV/DTE/1224/csv

    Realized vol (intraday, maturity expressed as EWM, span in business days): data.canari.dev/RV/IFX ... Implied dividend flow: data.canari.dev/DIV/IBE ... Smile (vol spread between ATM strike and 90% strike, normalized to 1Y with factor 1/√T): data.canari.dev/SMI/DTE ... Forward: data.canari.dev/FWD/BNP ...

    List of available underlyings: Code Name OESX Eurostoxx50 ODAX DAX OSMI SMI (Swiss index) OESB Eurostoxx Banks OVS2 VSTOXX ITK AB Inbev ABBN ABB ASM ASML ADS Adidas AIR Air Liquide EAD Airbus ALV Allianz AXA Axa BAS BASF BBVD BBVA BMW BMW BNP BNP BAY Bayer DBK Deutsche Bank DB1 Deutsche Boerse DPW Deutsche Post DTE Deutsche Telekom EOA E.ON ENL5 Enel INN ING IBE Iberdrola IFX Infineon IES5 Intesa Sanpaolo PPX Kering LOR L Oreal MOH LVMH LIN Linde DAI Mercedes-Benz MUV2 Munich Re NESN Nestle NOVN Novartis PHI1 Philips REP Repsol ROG Roche SAP SAP SNW Sanofi BSD2 Santander SND Schneider SIE Siemens SGE Société Générale SREN Swiss Re TNE5 Telefonica TOTB TotalEnergies UBSN UBS CRI5 Unicredito SQU Vinci VO3 Volkswagen ANN Vonovia ZURN Zurich Insurance Group

  5. o

    Datasets in 2012 to 2024

    • optiondata.org
    Updated Sep 3, 2022
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    (2022). Datasets in 2012 to 2024 [Dataset]. https://optiondata.org/
    Explore at:
    Dataset updated
    Sep 3, 2022
    License

    https://optiondata.org/about.htmlhttps://optiondata.org/about.html

    Description

    Historical option data in 2019 to 2021, dataset files in CSV format.

  6. o

    Datasets in 2024

    • optiondata.org
    Updated Sep 3, 2022
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    (2022). Datasets in 2024 [Dataset]. https://optiondata.org/
    Explore at:
    Dataset updated
    Sep 3, 2022
    License

    https://optiondata.org/about.htmlhttps://optiondata.org/about.html

    Time period covered
    Jan 1, 2024 - Dec 31, 2024
    Description

    Historical option EOD data in 2021, dataset files in CSV format.

  7. PEAK Options & Futures Prediction (Forecast)

    • kappasignal.com
    Updated Oct 19, 2022
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    KappaSignal (2022). PEAK Options & Futures Prediction (Forecast) [Dataset]. https://www.kappasignal.com/2022/10/peak-options-futures-prediction.html
    Explore at:
    Dataset updated
    Oct 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.

    PEAK Options & Futures 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

  8. M

    Option Care Health - 29 Year Stock Price History | OPCH

    • macrotrends.net
    csv
    Updated Jul 31, 2025
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    MACROTRENDS (2025). Option Care Health - 29 Year Stock Price History | OPCH [Dataset]. https://www.macrotrends.net/stocks/charts/OPCH/option-care-health/stock-price-history
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jul 31, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

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

    Time period covered
    2010 - 2025
    Area covered
    United States
    Description

    The latest closing stock price for Option Care Health as of July 03, 2025 is 31.16. An investor who bought $1,000 worth of Option Care Health stock at the IPO in 1996 would have $-377 today, roughly 0 times their original investment - a -1.62% compound annual growth rate over 29 years. The all-time high Option Care Health stock closing price was 90.00 on April 22, 2002. The Option Care Health 52-week high stock price is 35.53, which is 14% above the current share price. The Option Care Health 52-week low stock price is 21.39, which is 31.4% below the current share price. The average Option Care Health stock price for the last 52 weeks is 29.92. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

  9. o

    Sample Data at 2022-08-24

    • optiondata.org
    Updated Sep 3, 2022
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    (2022). Sample Data at 2022-08-24 [Dataset]. https://optiondata.org/
    Explore at:
    Dataset updated
    Sep 3, 2022
    License

    https://option.discount/privacy.htmlhttps://option.discount/privacy.html

    Time period covered
    Aug 24, 2022
    Description

    Historical option sample data at 2022-08-24, dataset files in CSV format.

  10. T

    Option Care Health | BIOS - Stock Price | Live Quote | Historical Chart

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Dec 14, 2015
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    TRADING ECONOMICS (2015). Option Care Health | BIOS - Stock Price | Live Quote | Historical Chart [Dataset]. https://tradingeconomics.com/bios:us
    Explore at:
    xml, json, excel, csvAvailable download formats
    Dataset updated
    Dec 14, 2015
    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 1, 2000 - Aug 2, 2025
    Area covered
    United States
    Description

    Option Care Health stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

  11. NSE LEMONTREE Options & Futures Prediction (Forecast)

    • kappasignal.com
    Updated Sep 27, 2022
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    KappaSignal (2022). NSE LEMONTREE Options & Futures Prediction (Forecast) [Dataset]. https://www.kappasignal.com/2022/09/nse-lemontree-options-futures-prediction.html
    Explore at:
    Dataset updated
    Sep 27, 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.

    NSE LEMONTREE Options & Futures 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

  12. T

    Finland - Total financial sector liabilities: Financial derivatives and...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Oct 18, 2021
    + more versions
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    TRADING ECONOMICS (2021). Finland - Total financial sector liabilities: Financial derivatives and employee stock options [Dataset]. https://tradingeconomics.com/finland/total-financial-sector-liabilities-financial-derivatives-employee-stock-options-non-consolidated-eurostat-data.html
    Explore at:
    excel, json, xml, csvAvailable download formats
    Dataset updated
    Oct 18, 2021
    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 1, 1976 - Dec 31, 2025
    Area covered
    Finland
    Description

    Finland - Total financial sector liabilities: Financial derivatives and employee stock options was 13.90 % of GDP in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Finland - Total financial sector liabilities: Financial derivatives and employee stock options - last updated from the EUROSTAT on July of 2025. Historically, Finland - Total financial sector liabilities: Financial derivatives and employee stock options reached a record high of 90.10 % of GDP in December of 2011 and a record low of -0.40 % of GDP in December of 1995.

  13. F

    CBOE Volatility Index: VIX

    • fred.stlouisfed.org
    json
    Updated Jul 31, 2025
    + more versions
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    (2025). CBOE Volatility Index: VIX [Dataset]. https://fred.stlouisfed.org/series/VIXCLS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 31, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Description

    Graph and download economic data for CBOE Volatility Index: VIX (VIXCLS) from 1990-01-02 to 2025-07-30 about VIX, volatility, stock market, and USA.

  14. Options Price Reporting Authority

    • lseg.com
    Updated Feb 18, 2025
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    LSEG (2025). Options Price Reporting Authority [Dataset]. https://www.lseg.com/en/data-analytics/financial-data/pricing-and-market-data/options-data/options-price-reporting-authority
    Explore at:
    csv,delimited,gzip,html,json,pcap,pdf,parquet,python,sql,string format,text,user interface,xml,zip archiveAvailable download formats
    Dataset updated
    Feb 18, 2025
    Dataset provided by
    London Stock Exchange Grouphttp://www.londonstockexchangegroup.com/
    Authors
    LSEG
    License

    https://www.lseg.com/en/policies/website-disclaimerhttps://www.lseg.com/en/policies/website-disclaimer

    Description

    Explore Options Price Reporting Authority (OPRA) through LSEG. OPRA collects, consolidates and disseminates information for US Options.

  15. T

    Slovakia - Financial derivatives and employee stock options

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 23, 2021
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    TRADING ECONOMICS (2021). Slovakia - Financial derivatives and employee stock options [Dataset]. https://tradingeconomics.com/slovakia/financial-derivatives-employee-stock-options-eurostat-data.html
    Explore at:
    json, xml, excel, csvAvailable download formats
    Dataset updated
    Mar 23, 2021
    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 1, 1976 - Dec 31, 2025
    Area covered
    Slovakia
    Description

    Slovakia - Financial derivatives and employee stock options was MIO_NAC-500.30 Million in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Slovakia - Financial derivatives and employee stock options - last updated from the EUROSTAT on August of 2025. Historically, Slovakia - Financial derivatives and employee stock options reached a record high of MIO_NAC186.60 Million in December of 2008 and a record low of MIO_NAC-1775.10 Million in December of 2021.

  16. CBOE Volatility Index Options & Futures Prediction (Forecast)

    • kappasignal.com
    Updated Oct 16, 2022
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    KappaSignal (2022). CBOE Volatility Index Options & Futures Prediction (Forecast) [Dataset]. https://www.kappasignal.com/2022/10/cboe-volatility-index-options-futures.html
    Explore at:
    Dataset updated
    Oct 16, 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.

    CBOE Volatility Index Options & Futures 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

  17. US Equities Packages - Stock Prices & Fundamentals

    • datarade.ai
    Updated Dec 26, 2021
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    Intrinio (2021). US Equities Packages - Stock Prices & Fundamentals [Dataset]. https://datarade.ai/data-products/us-equities-packages-stock-prices-fundamentals-intrinio
    Explore at:
    Dataset updated
    Dec 26, 2021
    Dataset authored and provided by
    Intrinio
    Area covered
    United States
    Description

    We offer three easy-to-understand equity data packages to fit your business needs. Visit intrinio.com/pricing to compare packages.

    Bronze

    The Bronze package is ideal for developing your idea and prototyping your platform with high-quality EOD equity pricing data, standardized financial statement data, and supplementary fundamental datasets.

    When you’re ready for launch, it’s a seamless transition to our Silver package for additional data sets, 15-minute delayed equity pricing data, expanded history, and more.

    • Historical EOD equity prices & technicals (10 years history)
    • Security reference data
    • Standardized & as-reported financial statements (5 years history)
    • 7 supplementary fundamental data sets

    Bronze Benefits:

    • Web API access
    • 300 API calls/minute limit
    • Unlimited internal users
    • Unlimited internal & external display
    • Built-in ticketing system
    • Live chat & email support

    Silver

    The Silver package is ideal for startups that are in development, testing, or in the beta launch phase. Hit the ground running with 15-minute delayed and historical intraday and EOD equity prices, plus our standardized and as-reported financial statement data with nine supplementary data sets, including insider transactions and institutional ownership.

    When you’re ready to scale, easily move up to the Gold package for our full range of data sets and full history, real-time equity pricing data, premium support options, and much more.

    • 15-minute delayed & historical intraday equity prices
    • Historical EOD equity prices & technicals (full history)
    • Security reference data
    • Standardized & as-reported financial statements (10 years history)
    • 9 supplementary fundamental data sets

    Silver Benefits:

    • Web API access
    • 2,000 API calls/minute limit
    • Access to third-party datasets via Intrinio API (additional fees required)
    • Unlimited internal users
    • Unlimited internal & external display
    • Built-in ticketing system
    • Live chat & email support

    Gold

    The Gold package is ideal for funded companies that are in the growth or scaling stage, as well as institutions that are innovating within the fintech space. This full-service solution offers our complete collection of equity pricing data feeds, from real-time to historical EOD, plus standardized financial statement data and nine supplementary feeds.

    You’ll also have access to our wide range of modern access methods, third-party data via Intrinio’s API with licensing assistance, support from our team of expert engineers, custom delivery architectures, and much more.

    • Real-time equity prices
    • Historical intraday equity prices
    • Historical EOD equity prices & technicals (full history)
    • Security reference data
    • Standardized & as-reported financial statements (full history)
    • 9 supplementary fundamental data sets

    Gold Benefits:

    • No exchange fees
    • No user reporting or variable per-user exchange fees
    • High liquidity (6%+)
    • Web API & WebSocket access
    • 2,000 API calls/minute limit
    • Customizable access methods (Snowflake, FTP, etc.)
    • Access to third-party datasets via Intrinio API (additional fees required)
    • Unlimited internal users
    • Unlimited internal & external display
    • Built-in ticketing system
    • Live chat & email support
    • Access to engineering team
    • Concierge customer success team
    • Comarketing & promotional initiatives

    Platinum

    Don’t see a package that fits your needs? Our team can design premium custom packages for institutions.

  18. T

    Option Care Health | BIOS - Stock

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 15, 2025
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    TRADING ECONOMICS (2025). Option Care Health | BIOS - Stock [Dataset]. https://tradingeconomics.com/bios:us:stock
    Explore at:
    excel, json, xml, csvAvailable download formats
    Dataset updated
    Jun 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 1, 2000 - Aug 2, 2025
    Area covered
    United States
    Description

    Option Care Health reported $403.54M in Stock for its fiscal quarter ending in June of 2025. Data for Option Care Health | BIOS - Stock including historical, tables and charts were last updated by Trading Economics this last August in 2025.

  19. TER Options & Futures Prediction (Forecast)

    • kappasignal.com
    Updated Sep 2, 2022
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    KappaSignal (2022). TER Options & Futures Prediction (Forecast) [Dataset]. https://www.kappasignal.com/2022/09/ter-options-futures-prediction.html
    Explore at:
    Dataset updated
    Sep 2, 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.

    TER Options & Futures 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

  20. d

    Gamma Exposure (GEX) measurement of US stocks and options by Trading...

    • datarade.ai
    .json, .csv
    Updated Feb 4, 2021
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    Trading Volatility (2021). Gamma Exposure (GEX) measurement of US stocks and options by Trading Volatility [Dataset]. https://datarade.ai/data-products/gamma-exposure-gex-measurement-of-us-companies-and-indexes-tickerized-trading-volatility
    Explore at:
    .json, .csvAvailable download formats
    Dataset updated
    Feb 4, 2021
    Dataset authored and provided by
    Trading Volatility
    Area covered
    United States
    Description

    Our proprietary Skew-Adjusted Gamma Exposure measurements make adjustments to Naive GEX calculations to more accurately reflect actual gamma positioning of Market Makers who employ delta-hedging strategies. When Market Makers carry substantial negative gamma a security will often "over-react" to fundamental news. Conversely, when MMs carry substantial positive gamma a security will often "under-react" to news. Our data includes a quantified segmentation of a security's gamma distribution across all option strikes as well as across relevant expiration dates. Our website provides numerical, graphical, and historical views of all gamma data in our database. Additionally, our API access allows for easy download of csv files or import into Excel for further analysis and custom applications.

Share
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Link copied
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OptionMetrics (2023). IvyDB Signed Volume - Daily Options Trading Volume Data [Dataset]. https://optionmetrics.com/

IvyDB Signed Volume - Daily Options Trading Volume Data

IvyDB Signed Volume

Explore at:
94 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Nov 15, 2023
Dataset authored and provided by
OptionMetrics
License

https://optionmetrics.com/contact/https://optionmetrics.com/contact/

Time period covered
Jan 1, 2016 - Present
Description

The IvyDB Signed Volume dataset, available as an add-on product for IvyDB US, contains daily data on detailed option trading volume. Trades in the IvyDB US dataset are assigned as either buyer-initiated or seller-initiated based on the trade price and the bid-ask quote at the time of the trade. The total assigned daily volume is aggregated and updated nightly.

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