Free historical options data, dataset files in CSV format.

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.

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

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

TraditionData’s FX Options Market Data service provides comprehensive information on FX options markets, leveraging the Volbroker platform for transparency and efficiency.

• Offers real-time volatility price transparency in ATM Straddles, Delta Risk Reversals, and Butterflies.
• Suitable for traders, risk managers, or portfolio managers managing currency risk and maximizing returns.

Visit FX Options Market Data for more information.

Dataset contains entire 2024 data pertaining to Nifty options. This dataset has all expiry day and its trading data. The dataset is arranged in month wise. Each month, you can see multiple files. The file has specify format. The format of the file is Nifty-{expiry day}-{trade day}.csv. Also there is one folder 2024Nifty, which contains Nifty's daily data. Nifty's daily data is crunched into single file for every month. Also, expiry.csv is available, which is overall expiries for the entire year 2024

Index Time Series for ETC 6 Meridian Hedged Equity-Index Option Strategy ETF. The frequency of the observation is daily. Moving average series are also typically included. Under normal circumstances, the fund invests at least 80% of its net assets (plus the amount of any borrowings for investment purposes) in equity securities. The equity securities in which it invests are mainly common stocks. The fund may invest in equity securities of companies of any capitalization. It is non-diversified.

Quantum-AI Option Pricing Market Outlook

According to our latest research, the global Quantum-AI Option Pricing market size reached USD 1.68 billion in 2024, reflecting a significant surge in adoption across the financial services sector. The market is projected to grow at a robust CAGR of 33.7% from 2025 to 2033, reaching a forecasted value of USD 21.65 billion by 2033. This remarkable growth trajectory is propelled by increasing demand for high-speed, accurate, and complex option pricing models that leverage quantum computing and artificial intelligence, especially in volatile and algorithm-driven markets.

One of the primary growth factors driving the Quantum-AI Option Pricing market is the exponential increase in market data and the complexity of financial instruments. As financial markets become more globalized and interconnected, the volume and velocity of data have outpaced the capabilities of traditional computational models. Quantum-AI solutions, by combining the computational power of quantum algorithms with machine learning, enable financial institutions to process and analyze vast datasets in real-time, resulting in improved pricing accuracy and risk assessment. This capability is crucial for institutions seeking to maintain a competitive edge in high-frequency trading and derivatives markets, where milliseconds can make a significant difference in profitability.

Another significant driver is the growing regulatory pressure for transparency and precision in option pricing. Regulatory bodies worldwide are mandating stricter risk management and reporting standards, compelling financial institutions to adopt more sophisticated and reliable pricing models. Quantum-AI Option Pricing platforms offer enhanced auditability and compliance features, providing detailed traceability and validation of pricing models. This not only ensures regulatory adherence but also builds greater trust among clients and stakeholders. The integration of quantum computing with AI further facilitates scenario analysis and stress testing, enabling firms to anticipate and mitigate potential market risks more effectively.

Furthermore, the rising adoption of cloud-based deployment models is accelerating the democratization of Quantum-AI Option Pricing solutions. Cloud platforms enable smaller financial institutions, hedge funds, and asset managers to access advanced quantum-AI capabilities without the need for heavy upfront investments in hardware infrastructure. This shift is fostering innovation and competition, as a broader range of market participants can leverage cutting-edge technology to optimize their option pricing strategies. Additionally, the scalability and flexibility offered by cloud deployments support rapid experimentation and integration with other fintech solutions, further driving market expansion.

From a regional perspective, North America continues to dominate the Quantum-AI Option Pricing market, accounting for the largest revenue share in 2024, followed by Europe and Asia Pacific. The United States, in particular, is at the forefront, driven by the presence of major financial institutions, advanced technology providers, and a robust regulatory environment. Europe is witnessing accelerated growth due to increasing investments in fintech innovation and favorable government initiatives supporting quantum computing research. Meanwhile, Asia Pacific is emerging as a lucrative market, fueled by the rapid digitalization of financial services in countries like China, Japan, and Singapore. The region is expected to exhibit the highest CAGR over the forecast period, reflecting a strong appetite for next-generation financial technologies.

Component Analysis

The Quantum-AI Option Pricing market is segmented by component into Software, Hardware, and Services, each playing a pivotal role in the market’s overall ecosystem. The software segment leads the market, primarily due to the increasing demand for advanced analytics platforms and pricing engines powered by quantum algorithms and artificial intelligence. These software solutions are designed to integrate seamlessly with existing trading and risk management systems, offering real-time pricing, scenario analysis, and model validation. Financial institutions are prioritizing investments in software that can adapt to rapidly changing market conditions and support a wide range of option types, driving continuous innovation and development in this segment.

Choice Properties stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

Explore the historical Whois records related to nifty-options.com (Domain). Get insights into ownership history and changes over time.

Index Time Series for FT Cboe Vest U.S. Equity Deep Buffer ETF - June. The frequency of the observation is daily. Moving average series are also typically included. Under normal market conditions, the fund will invest substantially all of its assets in FLexible EXchange® Options (FLEX Options) that reference the price performance of the SPDR® S&P 500® ETF Trust (the Underlying ETF). FLEX Options are customized equity or index option contracts that trade on an exchange, but provide investors with the ability to customize key contract terms like exercise prices, styles and expiration dates. It is non-diversified.

Dataset Description: 34-year Daily Stock Data (1990-2024)

Context and Inspiration

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)

Sources

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.

Columns

1. dt: Date of observation in YYYY-MM-DD format.
2. vix: VIX (Volatility Index), a measure of expected market volatility.
3. sp500: S&P 500 index value, a benchmark of the U.S. stock market.
4. sp500_volume: Daily trading volume for the S&P 500.
5. djia: Dow Jones Industrial Average (DJIA), another key U.S. market index.
6. djia_volume: Daily trading volume for the DJIA.
7. hsi: Hang Seng Index, representing the Hong Kong stock market.
8. ads: Aruoba-Diebold-Scotti (ADS) Business Conditions Index, reflecting U.S. economic activity.
9. us3m: U.S. Treasury 3-month bond yield, a short-term interest rate proxy.
10. joblessness: U.S. unemployment rate, reported as quartiles (1 represents lowest quartile and so on).
11. epu: Economic Policy Uncertainty Index, quantifying policy-related economic uncertainty.
12. GPRD: Geopolitical Risk Index (Daily), measuring geopolitical risk levels.
13. prev_day: Previous day’s S&P 500 closing value, added for lag-based time series analysis.

Key Features

• Cross-Market Analysis: Compare U.S. markets (S&P 500, DJIA) with international benchmarks like HSI.
• Macroeconomic Insights: Assess how external factors like joblessness, interest rates, and economic uncertainty affect markets.
• Temporal Scope: Longitudinal data facilitates trend analysis and machine learning model training.

Potential Use Cases

• Forecasting market indices using machine learning or statistical models.
• Building volatility trading strategies with VIX Futures.
• Economic research on relationships between policy uncertainty and market behavior.
• Educational material for financial data visualization and analysis tutorials.

Feel free to use this dataset for academic, research, or personal projects.

Yearly citation counts for the publication titled "Model-independent bounds for option prices—a mass transport approach".

Option Care Health reported $25.98 in PE Price to Earnings for its fiscal quarter ending in June of 2025. Data for Option Care Health | BIOS - PE Price to Earnings including historical, tables and charts were last updated by Trading Economics this last September in 2025.

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Foreign Exchange Market Size 2025-2029

The foreign exchange market size is valued to increase by USD 582 billion, at a CAGR of 10.6% from 2024 to 2029. Growing urbanization and digitalization will drive the foreign exchange market.

Major Market Trends & Insights

Europe dominated the market and accounted for a 47% growth during the forecast period.
By Type - Reporting dealers segment was valued at USD 278.60 billion in 2023
By Trade Finance Instruments - Currency swaps segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 118.14 billion
Market Future Opportunities: USD 582.00 billion
CAGR from 2024 to 2029 : 10.6%

Market Summary

The market, a dynamic and intricate web of financial transactions, plays a pivotal role in facilitating global trade and economic interactions. Its primary function is to enable the conversion of one currency into another, thereby mitigating the risk of currency fluctuations for businesses and investors. Key drivers of this market include growing urbanization and digitalization, which have expanded trading opportunities to a 24x7 global economy. However, the uncertainty of future exchange rates poses a significant challenge, necessitating effective risk management strategies. The market's evolution reflects the increasing interconnectedness of the global economy. Transactions occur in a decentralized, over-the-counter system, with major trading centers in London, New York, and Tokyo.
Participants include commercial banks, investment banks, hedge funds, and individual investors, all seeking to capitalize on price differences between currencies. Trends shaping the market include the increasing use of automation and artificial intelligence to analyze market data and execute trades. Regulatory changes, such as the introduction of stricter capital requirements, also impact the market's functioning. Looking ahead, the market is expected to remain a vital component of the global financial landscape, with continued growth driven by increased trade and economic interdependence. However, challenges, such as regulatory changes and geopolitical risks, will necessitate adaptability and innovation from market participants.

What will be the Size of the Foreign Exchange Market during the forecast period?

Get Key Insights on Market Forecast (PDF) Request Free Sample

How is the Foreign Exchange Market Segmented ?

The foreign exchange industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  Reporting dealers
  Financial institutions
  Non-financial customers


Trade Finance Instruments

  Currency swaps
  Outright forward and FX swaps
  FX options


Trading Platforms

  Electronic Trading
  Over-the-Counter (OTC)
  Mobile Trading


Geography

  North America

    US
    Canada


  Europe

    Germany
    Switzerland
    UK


  Middle East and Africa

    UAE


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By Type Insights

The reporting dealers segment is estimated to witness significant growth during the forecast period.

The market, a dynamic and ever-evolving financial landscape, is characterized by constant activity and intricate patterns. Participants engage in various trading strategies, employing advanced tools such as stop-loss and take-profit orders on forex trading platforms. Real-time data feeds and order book dynamics facilitate trade execution speed, while market microstructure and slippage minimization techniques ensure efficient transactions. Currency correlation analysis and transaction cost analysis are integral to informed decision-making, with backtesting methodologies providing valuable insights. Currency forwards contracts, position sizing techniques, and forex derivatives pricing are essential components of risk management systems. Carry trade strategies, hedging strategies, and interest rate parity are popular tactics employed by market participants.

Algorithmic trading strategies, driven by options pricing models and trading algorithms' efficiency, significantly influence price discovery mechanisms. High-frequency trading and volatility modeling contribute to the market's liquidity risk management, while foreign exchange swaps and currency option valuation help manage risk. The market's complexities necessitate sophisticated risk management systems and intricate order routing optimization. Global payments systems facilitate the smooth transfer of funds, and liquidity risk management remains a critical concern for market participants. According to recent studies, The market is estimated to account for approximately USD6 trillion in daily trading volume, und

Index Time Series for FT Cboe Vest U.S. Equity Buffer ETF - February. The frequency of the observation is daily. Moving average series are also typically included. Under normal market conditions, the fund will invest substantially all of its assets in FLexible EXchange® Options (FLEX Options) that reference the price performance of the SPDR® S&P 500® ETF Trust (the Underlying ETF). FLEX Options are customized equity or index option contracts that trade on an exchange, but provide investors with the ability to customize key contract terms like exercise prices, styles and expiration dates. It is non-diversified.

Yearly citation counts for the publication titled "Quantitative error estimates for a least-squares Monte Carlo algorithm for American option pricing".

Index Time Series for FT Cboe Vest U.S. Equity Deep Buffer ETF - November. The frequency of the observation is daily. Moving average series are also typically included. Under normal market conditions, the fund will invest substantially all of its assets in FLexible EXchange® Options (FLEX Options) that reference the price performance of the SPDR® S&P 500® ETF Trust (the Underlying ETF). FLEX Options are customized equity or index option contracts that trade on an exchange, but provide investors with the ability to customize key contract terms like exercise prices, styles and expiration dates. It is non-diversified.

This dataset tracks annual reduced-price lunch eligibility from 2001 to 2023 for Innovations & Options vs. Colorado and School District 27j

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.