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.

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

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

Free historical options data, dataset files in CSV format.

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

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This dataset is a combination of four years of Tesla ($TSLA) options end of day quotes ranging from 01-2019 to 12-2022. Each row represents the information associated with one contract's strike price and a given expiration date.

Dates quotes are given in in Unix and in "YYYY-MM-DD HH:MM" formats. Quote frequency is daily at 4:00 pm EST, which corresponds with end of day market closure.

REMEMBER: Tesla stock split on August 25th, 2022. This will be reflected in the data. Keep this in mind!

What is an option chain?

An option chain can be defined as the listing of all option contracts. It comes with two different sections: call and put. A call option means a contract that gives you the right but does not give you the obligation to buy an underlying asset at a particular price and within the option's expiration date. This means that in this dataset, there will be the entire option chain (all available option contracts for all expirations) for each business day between Q1 2019 and Q4 2022.

This dataset contains data for American options, which can be exercised on or before expiration data. This is unlike European options contracts, which can only be exercised on the expiration date.

I am also continuously working on the associated notebook to give a basic idea of how to load and explore the data. Stay tuned!

Similar Datasets: - $SPY Option Chains - $AAPL Option Chains - $NVDA Option Chains - $QQQ Option Chains

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

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This dataset is a combination of three years of SPDR S&P 500 ETF Trust ($SPY) options end of day quotes ranging from 01-2020 to 12-2022. Each row represents the information associated with one contract's strike price and a given expiration date.

Dates quotes are given in in Unix and in "YYYY-MM-DD HH:MM" formats. Quote frequency is daily at 4:00 pm EST, which corresponds with end of day market closure.

What is an option chain?

An option chain can be defined as the listing of all option contracts. It comes with two different sections: call and put. A call option means a contract that gives you the right but does not give you the obligation to buy an underlying asset at a particular price and within the option's expiration date. This means that in this dataset, there will be the entire option chain (all available option contracts for all expirations) for each business day between Q1 2020 and Q4 2022.

This dataset contains data for American options, which can be exercised on or before expiration data. This is unlike European options contracts, which can only be exercised on the expiration date.

I am also continuously working on the associated notebook to give a basic idea of how to load and explore the data. Stay tuned!

Similar Datasets: - $TSLA Option Chains - $AAPL Option Chains - $NVDA Option Chains - $QQQ Option Chains

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

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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
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• Unlimited internal users
• Unlimited internal & external display
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• Live chat & email support

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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
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• 9 supplementary fundamental data sets

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• Web API access
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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

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• 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

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Japan OSE: Turnover: Value: Nikkei 225 Call and Put Options data was reported at 516.962 JPY bn in Nov 2018. This records a decrease from the previous number of 749.344 JPY bn for Oct 2018. Japan OSE: Turnover: Value: Nikkei 225 Call and Put Options data is updated monthly, averaging 228.702 JPY bn from Jun 1989 (Median) to Nov 2018, with 354 observations. The data reached an all-time high of 1,544.252 JPY bn in May 2013 and a record low of 44.521 JPY bn in Jul 2005. Japan OSE: Turnover: Value: Nikkei 225 Call and Put Options data remains active status in CEIC and is reported by Japan Exchange Group. The data is categorized under Global Database’s Japan – Table JP.Z016: Osaka Exchange Inc: Futures and Options.

Index Time Series for Global X S&P 500® Covered Call ETF. The frequency of the observation is daily. Moving average series are also typically included. The fund invests at least 80% of its total assets in the securities of the underlying index. The underlying index measures the performance of a hypothetical portfolio that employs a covered call strategy. A covered call strategy is generally considered to be an investment strategy in which an investor buys a security, and sells (or writes) a call option on that security in an attempt to generate more income.

Korea KOSPI 200 Option: Put: Purchase: Contract: Security & Futures data was reported at 3,412.994 Unit th in Jun 2018. This records an increase from the previous number of 3,241.289 Unit th for May 2018. Korea KOSPI 200 Option: Put: Purchase: Contract: Security & Futures data is updated monthly, averaging 21,864.610 Unit th from Dec 1999 (Median) to Jun 2018, with 223 observations. The data reached an all-time high of 60,933.759 Unit th in Aug 2005 and a record low of 646.280 Unit th in Mar 2000. Korea KOSPI 200 Option: Put: Purchase: Contract: Security & Futures data remains active status in CEIC and is reported by Korea Exchange. The data is categorized under Global Database’s Korea – Table KR.Z020: Korea Exchange: Options Market: KOSPI 200 Options: Turnover by Type of Investors.

Index Time Series for Global X NASDAQ 100® Risk Managed Income ETF. The frequency of the observation is daily. Moving average series are also typically included. The fund invests at least 80% of its total assets in the securities of the Nasdaq-100 Monthly Net Credit Collar 95-100 Index (underlying index). The underlying index measures the performance of a risk managed income strategy that holds the underlying stocks of the NASDAQ 100® Index and applies an options collar strategy (i.e., a mix of short (sold) call options and long (purchased) put options) on the NASDAQ 100® Index. The fund is non-diversified.

This thesis examines the market efficiency of the Swedish index option (OMX) market. The empirical tests are carried out on an ex-ante basis using the index future contracts to hedge the index options. Two efficiency tests have been performed, explicitly lower boundary and put call parity conditions test and dynamic hedging strategy. The first test shows that the discovered deviations from the lower boundary conditions and put call parity condition do not generate abnormal returns, particularly after all transaction costs have been accounted for. The second test, delta neutral dynamic hedging strategy, is simulated by comparing option market prices with the Black Scholes prices calculated using two volatility estimators, namely historical volatility (HSD) and weighted implied standard deviation (WISD). The strategy evidences that no systematic abnormal returns can be found in the OMX option market, therefore supporting the hypothesis of no arbitrage opportunity and market efficiency.

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.

What is a put option?

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

Index Time Series for TrueShares Structured Outcome (April) ETF. The frequency of the observation is daily. Moving average series are also typically included. The fund is an actively-managed ETF that seeks to achieve its investment objective by investing substantially all of its assets in options on the S&P 500 Price Index. It will purchase call options and sell put options on the S&P 500 Price Index or an ETF that seeks to track the performance of the S&P 500 Price Index on each Initial Investment Day with an expiration on the next Roll Date.

Korea KOSPI 200 Option: Call: Purchase: Contract data was reported at 37,422.129 Unit th in Nov 2018. This records a decrease from the previous number of 42,119.090 Unit th for Oct 2018. Korea KOSPI 200 Option: Call: Purchase: Contract data is updated monthly, averaging 85,305.882 Unit th from Dec 1999 (Median) to Nov 2018, with 228 observations. The data reached an all-time high of 207,569.641 Unit th in Aug 2011 and a record low of 3,267.178 Unit th in Dec 1999. Korea KOSPI 200 Option: Call: Purchase: Contract data remains active status in CEIC and is reported by Korea Exchange. The data is categorized under Global Database’s South Korea – Table KR.Z020: Korea Exchange: Options Market: KOSPI 200 Options: Turnover by Type of Investors.

India BSE: Turnover: Value: Derivatives: Index Options: Call data was reported at 0.000 INR mn in Oct 2018. This stayed constant from the previous number of 0.000 INR mn for Sep 2018. India BSE: Turnover: Value: Derivatives: Index Options: Call data is updated monthly, averaging 0.000 INR mn from Jun 2001 (Median) to Oct 2018, with 209 observations. The data reached an all-time high of 19,434,300.000 INR mn in Nov 2014 and a record low of 0.000 INR mn in Oct 2018. India BSE: Turnover: Value: Derivatives: Index Options: Call data remains active status in CEIC and is reported by Securities and Exchange Board of India. The data is categorized under Global Database’s India – Table IN.ZB001: Derivatives: Bombay Stock Exchange: Turnover.

Korea KOSPI 200 Option: Call: Purchase: Contract: Pension Fund data was reported at 0.019 Unit th in Jun 2018. This records a decrease from the previous number of 0.650 Unit th for May 2018. Korea KOSPI 200 Option: Call: Purchase: Contract: Pension Fund data is updated monthly, averaging 28.040 Unit th from Dec 1999 (Median) to Jun 2018, with 223 observations. The data reached an all-time high of 1,046.663 Unit th in Oct 2008 and a record low of 0.000 Unit th in Mar 2018. Korea KOSPI 200 Option: Call: Purchase: Contract: Pension Fund data remains active status in CEIC and is reported by Korea Exchange. The data is categorized under Global Database’s Korea – Table KR.Z020: Korea Exchange: Options Market: KOSPI 200 Options: Turnover by Type of Investors.

Korea KOSPI 200 Option: Call: Purchase: Individual data was reported at 1,340,352.000 KRW mn in Jun 2018. This records an increase from the previous number of 1,180,953.000 KRW mn for May 2018. Korea KOSPI 200 Option: Call: Purchase: Individual data is updated monthly, averaging 2,981,019.000 KRW mn from Dec 1999 (Median) to Jun 2018, with 223 observations. The data reached an all-time high of 7,818,083.000 KRW mn in Aug 2011 and a record low of 316,861.000 KRW mn in Jan 2000. Korea KOSPI 200 Option: Call: Purchase: Individual data remains active status in CEIC and is reported by Korea Exchange. The data is categorized under Global Database’s Korea – Table KR.Z020: Korea Exchange: Options Market: KOSPI 200 Options: Turnover by Type of Investors.