"Crypto options data" covers a wider range of things than the phrase suggests: raw trade prints, full order-book depth with Greeks attached, implied volatility broken out by strike and expiry, open interest, and a handful of derived metrics like put/call ratio that most researchers end up computing themselves. Providers package these differently, price them differently, and update them on different schedules, which makes "just get some options data" a less useful starting point than it sounds.
This guide covers the core concepts behind crypto options historical data, how the provider landscape breaks down, what a crypto options data API typically costs, and where to look next depending on which exchange you actually need.
What crypto options data actually is
At the center of it are trades: individual executions on an options contract, with a price, a size, a direction, and a timestamp. Around that sits order-book data, the resting bid and ask depth at each price level, which is what you need if a research question involves execution rather than just observing where prices ended up. Layered on top of both is implied volatility, the number a pricing model needs to reproduce an option's observed market price, and the full set of those numbers across every strike and expiry is what's usually meant by a volatility surface.
A few derived metrics come up constantly in options research without being raw exchange fields. Open interest is the total number of contracts still outstanding for a given strike and expiry, a rough proxy for where positioning is concentrated. Put/call ratio compares put volume or open interest to call volume or open interest, and traders read it as a sentiment signal, though it's rarely something a provider hands you pre-computed. Strike price distribution shows how volume or open interest is spread across the available strikes, and the bid-ask spread at each level is what actually lets you estimate the cost of getting a position on or off, rather than assuming you'd trade at the mid.
None of this is unique to crypto. What's different from equity or FX options is coverage and standardization: fewer venues, younger market infrastructure, and less agreement between providers on exactly how Greeks get computed.
Greeks, IV, and the rest, explained once
Greeks measure how an option's price responds to different inputs, and a proper Greeks data API reports all five together rather than just one. Delta tracks the response to the underlying price, gamma tracks how delta itself changes as the underlying moves, vega tracks sensitivity to implied volatility, theta tracks the daily cost of time decay, and rho tracks sensitivity to interest rates, which matters far less in crypto than in traditional options markets. None of these are raw exchange fields; they're computed from a pricing model, so two providers can report slightly different Greeks for the same contract at the same moment if they use different model conventions or a different underlying reference price.
Implied volatility (IV) is the volatility input that makes a pricing model's output match an option's actual market price. A single IV number is a market-level summary; a full volatility surface keeps IV broken out by strike and expiry, which is what actually shows skew (why downside puts often carry a different IV than calls at the same distance from the money) and term structure (why near-dated and far-dated IV diverge). Deribit's DVOL index is a widely cited single-number summary built the same way the VIX is built for equities; useful for a quick read on "has volatility moved," but it compresses away exactly the strike-and-expiry detail a surface preserves.
Open interest and put/call ratio round out the set most research questions actually touch. Open interest tracked by strike over time shows where the market has built up exposure and how that shifts as expiry approaches. Put/call ratio is a coarser sentiment gauge, useful as a quick signal but rarely the primary input to a serious pricing or risk model.
Where crypto options actually trade
Deribit is the dominant venue for crypto options by volume, and most third-party historical datasets, this guide included, lean heavily on it for that reason: Bitcoin and Ether options history both go deepest there, since it's had the longest continuous options market of any crypto-native exchange. Binance also lists options, with different contract specifications and considerably lower volume than Deribit historically. CME offers regulated Bitcoin and Ether options for institutional participants who need a traditional, cash-settled futures-exchange structure.
The practical question behind a "Deribit vs Binance options" comparison usually isn't which is objectively better, it's which one actually has the liquidity and data history a specific research question needs. Deribit's depth and multi-year history make it the default for volatility surface and skew research; Binance options data is thinner and, as of this guide, isn't something Convex Lake covers.
Choosing a crypto options data provider
Providers in this space tend to fall into a few categories. Exchange APIs give you a live feed and a limited historical window directly from the source, with no normalization or bulk export built in. Cross-venue data resellers capture and normalize options data across multiple exchanges under one schema. Analytics platforms go a step further and pre-compute Greeks, IV surfaces, and risk indicators on top of the raw data, trading some flexibility for less work on your end.
What actually differs between them, beyond the marketing copy, is coverage (which venues and currencies), depth (top-of-book only vs. full order-book levels), history (how far back an archive actually goes, which is a function of when a provider started recording, not the age of the exchange), and delivery (REST download, streaming API, or a dashboard with no programmatic access at all).
| Provider type | Depth | Greeks / IV surface | Typical delivery | Best for |
|---|---|---|---|---|
| Exchange official API | Live book only, short historical window | Rarely pre-computed | REST/WebSocket, no bulk export | Teams building their own capture pipeline |
| Cross-venue data resellers | Full order-book depth, multi-venue | Sometimes included | REST download, bulk files | Research spanning more than one exchange |
| Options-analytics platforms | Varies, often summarized | Pre-computed Greeks and IV surface | API or dashboard | Skew/surface research without building Greeks |
| Convex Lake | Trades, 10-level order book, volatility surface (Deribit BTC/ETH) | Greeks in order-book data; IV surface as a dedicated endpoint | REST, downloadable CSV | Options research alongside prediction-market data in one place |
Delivery formats and update cadence
CSV remains the most common delivery format for historical crypto options data, readable directly by pandas or a spreadsheet without extra parsing. JSON shows up mainly in live REST and WebSocket responses rather than bulk historical files. For research spanning a large date range or many instruments at once, a columnar format like Parquet compresses and queries substantially faster than CSV once a dataset runs into the millions of rows. Some providers also offer bulk delivery via cloud storage for datasets too large to pull through a REST API one file at a time.
Update frequency depends on what's being updated. Trade and order-book capture is typically continuous. Volatility surfaces are usually recomputed on a snapshot cadence, anywhere from every few minutes to once daily, since building a full surface from raw quotes is more computationally involved than logging a trade. Reference data like instrument listings and expiry calendars updates whenever the exchange adds or removes contracts, which for short-dated crypto options can mean daily. Worth asking a provider directly what "updated" means for the specific dataset in question.
How much does crypto options data cost
Pricing varies widely by scope. Free tiers are common for limited history, a single currency, or delayed data, useful for evaluating a provider before committing. Paid tiers scale with history depth, update frequency, number of instruments or venues covered, and whether the data includes computed fields like Greeks and IV surfaces rather than just raw trades. Enterprise pricing for institutional-grade, low-latency, multi-venue coverage can run considerably higher, sometimes into the tens of thousands of dollars a month for the broadest packages.
Convex Lake's Deribit coverage runs on a tiered API-key model: trades and order-book access are available on lower tiers, while the volatility surface endpoint requires a Research or Pro key. Current pricing lives on the docs and pricing pages rather than being restated here, since plan structures change more often than this guide does.
Common research use cases
Volatility surface and skew research is probably the most common use, comparing how IV varies across strikes and expiries over time to spot mispricing or shifts in market positioning. A full option chain pull, every strike and expiry on a given day, is usually the starting point for that work. Backtesting an options strategy means simulating fills against recorded order-book depth rather than assuming a fill at the mid price, which is where genuinely tick-level data matters more than a daily summary. Risk teams often track DVOL or a realized-vs-implied volatility spread as a standing signal. Cross-venue and cross-asset work compares options pricing on one exchange against spot, futures, or even prediction-market pricing for correlated events.
Data quality pitfalls to watch for
Greeks computed under different conventions. Since Greeks aren't raw exchange fields, two datasets can legitimately disagree on delta or vega for the same contract at the same timestamp if they use different pricing-model assumptions or underlying reference prices.
Coin-denominated vs. USD-notional pricing. Crypto options are frequently priced and settled in the underlying coin rather than USD, and providers convert to USD notional differently. Mixing conventions across a dataset silently distorts P&L and volume figures.
Survivorship and coverage gaps in "historical" archives. A provider's historical depth is bounded by when it started capturing data, not by how long the exchange has existed. An archive that looks comprehensive can still be missing years of history for less-traded instruments or older expiries.
Update-cadence mismatches inside one dataset. Trades might update continuously while a derived surface updates once a day. A pipeline that treats every field as equally fresh can end up joining a live trade against a stale surface snapshot without anyone noticing.
FAQ
What is crypto options data?
It covers trades, order-book depth, Greeks, implied volatility (often as a full surface by strike and expiry), and open interest for options contracts on crypto assets like Bitcoin and Ether. Most research questions need more than one of these pieces together, not just a single price feed.
How much does crypto options data cost?
It ranges from free tiers with limited history to enterprise packages that can run into the tens of thousands of dollars a month, depending on history depth, update frequency, venue coverage, and whether Greeks and IV surfaces are included pre-computed.
How is crypto options data updated?
It depends on the specific dataset. Trades and order-book snapshots from actively-capturing providers tend to update continuously; derived data like a volatility surface is usually recomputed on a snapshot schedule, anywhere from every few minutes to daily.
How is crypto options data delivered?
Most commonly as downloadable CSV files for historical data, with JSON used for live REST or WebSocket feeds. Parquet and cloud-storage bulk delivery show up for the largest datasets.
Is Deribit or Binance better for crypto options data?
For most quant research, Deribit: it has the deeper liquidity and longer historical record, and it's what most third-party datasets, this one included, are actually built on. Binance lists options too, but with less depth and history, and it isn't currently part of Convex Lake's coverage.
Getting started with Convex Lake's crypto options data
Convex Lake currently covers Deribit BTC and ETH options: trades, a 10-level order book with Greeks attached, and a volatility surface endpoint, alongside historical data forKalshi, Polymarket, predict.fun, and Limitless under the same API. See the API docs for the current endpoint reference, or create an account to get access.