Best Options Data Providers for Systematic Trading Research

Best Options Data Providers for Systematic Trading Research

Raw options chains are just the beginning. Here is what you actually need to build, test, and deploy options-based systematic strategies.

The Complexity of Options Data

Options data is fundamentally more complex than equity price data. An equity has one price series. A single underlying equity can have hundreds of associated options contracts at any given time, spanning multiple expiration dates, strike prices, and exercise styles. Each of those contracts has its own bid, ask, last trade, volume, open interest, and a set of model-derived Greeks that change continuously.

This complexity means that the data requirements for options-focused systematic strategies are substantially different from those of equity-only strategies. It also means that provider selection requires more nuance, because different providers excel at different aspects of the options data stack.

At a high level, we can distinguish between two categories of options data. The first is raw options market data: trade and quote data at various levels of granularity, from end-of-day snapshots to tick-level feeds. The second is derived options analytics: implied volatility surfaces, computed Greeks, skew metrics, and structural information about the options universe itself. Most providers focus on one category or the other. Very few address both well.

Raw Options Market Data Providers

Polygon.io (Massive)

Massive provides real-time and historical options data for U.S. equity options, including trades, quotes, and aggregates. Their options data goes back to approximately 2014, with tick-level precision. The flat monthly pricing model means you can query options chains extensively without worrying about per-request costs.

Massive is a strong choice for researchers who need raw options prices and want the same developer experience they are already using for equity data. The limitation is that Massive delivers raw data only — no pre-computed Greeks, no implied volatility surfaces, no analytics layer.

Databento

Databento provides institutional-grade options data sourced from direct exchange feeds, covering all U.S. equity options and options on futures. The data includes full order book depth (L1/L2/L3), nanosecond timestamps, and normalized symbology. For microstructure research involving options, Databento is the most accessible institutional-quality source.

The tradeoff is the same as with their equity data: the data is raw and usage-based pricing applies. For researchers pulling options chains across thousands of underlyings, costs can scale quickly.

IVolatility

IVolatility provides historical and real-time options data with a focus on implied volatility metrics. Their database includes options prices, implied volatilities, Greeks, and open interest data. The coverage is primarily U.S. options, with some international coverage. IVolatility has been in operation since 1999, which gives them one of the longer historical track records in the space.

Derived Options Analytics Providers

ORATS

ORATS is the specialized choice for options analytics. Their product suite includes historical implied volatility surfaces, earnings volatility estimates, skew analytics, dividend forecasts, and a proprietary fair value model for options pricing. The data is designed for researchers who are building volatility trading strategies, earnings plays, or any workflow that requires a deep understanding of the options pricing surface.

ORATS pricing starts at roughly $100 per month for basic access, with institutional tiers for heavier usage. For pure options research, the analytical depth is difficult to match.

OptionMetrics

OptionMetrics is the gold standard in academic options research. Their IVY database has been used in hundreds of published academic papers and is the default data source for options-focused PhD research. Coverage includes U.S. equity and index options with clean implied volatilities, Greeks, and standardized formatting.

The limitation for non-academic users is accessibility. OptionMetrics primarily serves institutions and universities through annual licensing agreements. Individual researchers may find the pricing and procurement process challenging.

CBOE DataShop

CBOE DataShop provides data directly from the CBOE exchanges, including historical options quotes, volatility indices (VIX and related), and market statistics. As the exchange operator, CBOE is the authoritative source for listed options and volatility products. Their LiveVol subsidiary offers additional analytics including implied volatility surfaces and Greeks.

CBOE DataShop is a strong choice when you need exchange-sourced data with high confidence in accuracy, particularly for index options and VIX-related products.

Comparison Table

The Research Layer for Options Strategies

There is a category of data that none of the providers above address directly: the structural metadata about the options universe itself. This is data about which options exist, when they exist, and how the market environment affects strategy selection — as opposed to the prices and analytics of individual contracts.

If you are building a systematic options strategy, some of the first questions you face are universe construction questions. Which underlyings should you consider? Specifically, which equities actually had listed weekly options available at the time you are backtesting? If you are running a 0-DTE strategy on the S&P 500, what strike range should you focus on given the current implied probability distribution? If you are selling volatility, is the current market regime historically favorable for that approach?

Alphanume provides several datasets designed specifically for these research needs. Their historical optionable tickers dataset is a monthly point-in-time record of which equities had listed options, including whether weekly expirations were available. This is foundational for any systematic options strategy backtest — without it, you risk constructing a universe that includes tickers that were not actually tradeable at the time. Their S&P 500 0-DTE strike band provides a model-derived expected intraday range for the S&P 500, calculated from implied probability distributions and risk factors, designed for strike selection in same-day options strategies. Their S&P 500 risk regime endpoint classifies each trading day into a binary risk state, which researchers can use to filter or condition options strategies based on the prevailing market environment. And their next-day movers dataset identifies equities most likely to produce large realized moves the following day, which is directly useful for researchers exploring short-dated directional or volatility strategies.

These are not alternatives to ORATS or OptionMetrics — they serve a different function. ORATS gives you the volatility surface; Alphanume tells you which underlyings to build that surface for, and under what market conditions your strategy is historically viable.

Matching Provider to Workflow

For raw options prices and quotes to feed into your own pricing models, Polygon or Databento serve the primary data layer. For pre-computed implied volatility surfaces, Greeks, and earnings analytics, ORATS provides the deepest coverage accessible to non-institutional users. For academic research requiring the most established and widely-cited options database, OptionMetrics remains the standard.

And for the structural research inputs that determine which options to analyze in the first place — universe definitions, regime signals, strike selection aids, and movement forecasts — Alphanume fills a gap that the raw data and analytics providers leave open.