https://optionmetrics.com/contact/https://optionmetrics.com/contact/
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.
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
https://optiondata.org/about.htmlhttps://optiondata.org/about.html
Historical option data in the last 24 years, dataset files in CSV format.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
https://optiondata.org/about.htmlhttps://optiondata.org/about.html
Free historical options data, dataset files in CSV format.
https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html
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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
https://optiondata.org/about.htmlhttps://optiondata.org/about.html
Historical option data in 2019 to 2021, dataset files in CSV format.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Option Care Health stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.
https://optiondata.org/about.htmlhttps://optiondata.org/about.html
Historical option EOD data in 2021, dataset files in CSV format.
https://whoisdatacenter.com/terms-of-use/https://whoisdatacenter.com/terms-of-use/
Explore the historical Whois records related to stock-option-calculators.org (Domain). Get insights into ownership history and changes over time.
https://option.discount/privacy.htmlhttps://option.discount/privacy.html
Historical option sample data at 2022-08-24, dataset files in CSV format.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
This dataset captures historical financial market data and macroeconomic indicators spanning over three decades, from 1990 onwards. It is designed for financial analysis, time series forecasting, and exploring relationships between market volatility, stock indices, and macroeconomic factors. This dataset is particularly relevant for researchers, data scientists, and enthusiasts interested in studying: - Volatility forecasting (VIX) - Stock market trends (S&P 500, DJIA, HSI) - Macroeconomic influences on markets (joblessness, interest rates, etc.) - The effect of geopolitical and economic uncertainty (EPU, GPRD)
The data has been aggregated from a mix of historical financial records and publicly available macroeconomic datasets: - VIX (Volatility Index): Chicago Board Options Exchange (CBOE). - Stock Indices (S&P 500, DJIA, HSI): Yahoo Finance and historical financial databases. - Volume Data: Extracted from official exchange reports. - Macroeconomic Indicators: Bureau of Economic Analysis (BEA), Federal Reserve, and other public records. - Uncertainty Metrics (EPU, GPRD): Economic Policy Uncertainty Index and Global Policy Uncertainty Database.
dt
: Date of observation in YYYY-MM-DD format.vix
: VIX (Volatility Index), a measure of expected market volatility.sp500
: S&P 500 index value, a benchmark of the U.S. stock market.sp500_volume
: Daily trading volume for the S&P 500.djia
: Dow Jones Industrial Average (DJIA), another key U.S. market index.djia_volume
: Daily trading volume for the DJIA.hsi
: Hang Seng Index, representing the Hong Kong stock market.ads
: Aruoba-Diebold-Scotti (ADS) Business Conditions Index, reflecting U.S. economic activity.us3m
: U.S. Treasury 3-month bond yield, a short-term interest rate proxy.joblessness
: U.S. unemployment rate, reported as quartiles (1 represents lowest quartile and so on).epu
: Economic Policy Uncertainty Index, quantifying policy-related economic uncertainty.GPRD
: Geopolitical Risk Index (Daily), measuring geopolitical risk levels.prev_day
: Previous day’s S&P 500 closing value, added for lag-based time series analysis.Feel free to use this dataset for academic, research, or personal projects.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required
Graph and download economic data for CBOE Volatility Index: VIX (VIXCLS) from 1990-01-02 to 2025-08-07 about VIX, volatility, stock market, and USA.
https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html
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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Croatia - Financial derivatives and employee stock options was MIO_NAC3.00 Million in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Croatia - Financial derivatives and employee stock options - last updated from the EUROSTAT on August of 2025. Historically, Croatia - Financial derivatives and employee stock options reached a record high of MIO_NAC1195.00 Million in December of 2016 and a record low of MIO_NAC-701.00 Million in December of 2013.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Poland - Financial derivatives and employee stock options: Financial Corporations other than MFIs was MIO_NAC-308.00 Million in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Poland - Financial derivatives and employee stock options: Financial Corporations other than MFIs - last updated from the EUROSTAT on July of 2025. Historically, Poland - Financial derivatives and employee stock options: Financial Corporations other than MFIs reached a record high of MIO_NAC1535.00 Million in December of 2023 and a record low of MIO_NAC-459.00 Million in December of 2008.
https://www.lseg.com/en/policies/website-disclaimerhttps://www.lseg.com/en/policies/website-disclaimer
Explore Options Price Reporting Authority (OPRA) through LSEG. OPRA collects, consolidates and disseminates information for US Options.
https://whoisdatacenter.com/terms-of-use/https://whoisdatacenter.com/terms-of-use/
Explore the historical Whois records related to plan-stock-options.mobi (Domain). Get insights into ownership history and changes over time.
https://optionmetrics.com/contact/https://optionmetrics.com/contact/
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.