Historical Options Replay for Event Studies

Event studies are where sloppy options data assumptions become obvious. Earnings releases, Fed decisions, CPI prints, product launches, biotech catalysts, and index rebalance days create clean stories. The stock moved. The option chain repriced. IV changed. Volume appeared. It is tempting to turn that into a simple "calls won" or "puts lost" article.

The better question is more technical: what did the market actually show before the event, which contracts were listed, what bid/ask quotes were available, what trades printed, and which rows should be rejected?

This guide turns the Historical Options Data API, contracts docs, quotes docs, trades docs, and historical options replay runbook into an event-study workflow.

Define the event timestamp

The event timestamp is not the whole study. It is the anchor. For earnings, it might be the release time or first tradable session after the release. For a stock strategy, it might be the bar close that created the signal.

Record:

• event source
• event timestamp
• pre-event observation window
• entry window
• exit window
• underlying price reference
• allowed expirations or DTE bucket
• fill policy
• reject policy

If you cannot define the timestamp windows, the event replay will drift into hindsight.

Rebuild the contract universe

The replay should not begin by typing an OCC symbol from memory. Use listed expirations, then contracts with as_of.

curl "https://api.cutemarkets.com/v1/tickers/expirations/NVDA/" \
  -H "Authorization: Bearer YOUR_API_KEY"

curl "https://api.cutemarkets.com/v1/options/contracts/?underlying_ticker=NVDA&as_of=2026-05-20&expiration_date.gte=2026-05-22&expiration_date.lte=2026-06-19&limit=100" \
  -H "Authorization: Bearer YOUR_API_KEY"

This protects the study from future-listing leakage. It also keeps adjusted contracts, weekly dates, monthly dates, and exact OCC identifiers visible.

For more detail, link the research note to point-in-time option contract selection, backtest options without stale contracts, and option symbols and contract identity.

Shortlist without cheating

The shortlist should be created before looking at post-event winners.

Useful shortlist rules:

The options chain API is useful for current candidate selection. For historical events, use historical options data and as_of contract discovery first.

Use quotes for fills

For every selected contract, pull quotes around the entry and exit windows.

curl "https://api.cutemarkets.com/v1/options/quotes/O:NVDA260522C00180000/?timestamp.gte=2026-05-20T19:40:00Z&timestamp.lt=2026-05-20T19:50:00Z&limit=1000" \
  -H "Authorization: Bearer YOUR_API_KEY"

Quote-aware terminology matters here:

• bid
• ask
• midpoint
• spread dollars
• spread percent
• quote age
• displayed size
• no-bid exit
• stale quote
• quote window

The why option quotes matter more than last price post explains the core reason. Around events, the last price can be stale because the chain reprices faster than every contract prints.

Use trades for activity validation

Trades show what printed:

curl "https://api.cutemarkets.com/v1/options/trades/O:NVDA260522C00180000/?timestamp.gte=2026-05-20T19:40:00Z&timestamp.lt=2026-05-21T14:00:00Z&limit=1000" \
  -H "Authorization: Bearer YOUR_API_KEY"

Use trades to answer:

• did the contract print near the event?
• were prints clustered before or after the release?
• was the trade size meaningful?
• do trade prices agree with the quote window?
• does tape activity support or contradict the chain rank?

Do not use trade prints as automatic fills. That shortcut is one reason event-study backtests overstate edge.

Report IV crush beside execution quality

An event study often talks about implied volatility crush. That is useful, but IV alone can mislead. Report IV beside the fields that decide tradability.

This is how the NVDA earnings replay and earnings options plays style of content becomes reproducible rather than narrative-only.

Publish the reject table

Rejects make the study more credible.

The backtesting data quality checklist, execution realism docs, and options slippage calculator all connect to these reject categories.

The conclusion should be a standard

A strong event-study article should not end with a trade recommendation. It should end with a research standard:

• exact contracts, not ticker-level ideas
• listed expirations, not guessed calendars
• quotes for fills, trades for activity
• IV beside spread and quote age
• rejected rows kept visible
• request URLs preserved

That is the subject area CuteMarkets should own: quote-aware, contract-aware, timestamp-aware options replay.

How the terminology applies

For Historical Options Replay for Event Studies, the backtesting workflow should treat Point-in-time contracts, Quote-aware fills, Reject reasons, Replay artifact, Cache key, and Signal timestamp as operational state rather than glossary decoration. That framing keeps the research claim causal: the strategy can only select instruments, prices, and labels that existed at the decision time.

A developer implementing this Deep Dive idea should persist Look-ahead leakage, Walk-forward test, Slippage model, Same-bar fill, Promotion gate, and Options data API beside the result, instead of leaving those words in a term card. It also turns attractive performance into an auditable record where fills, skips, thresholds, and replay inputs can be challenged independently.

The review artifact for Historical Options Replay for Event Studies becomes more useful when OPRA-originating data, OCC option symbol, Bid/ask spread, Midpoint, Quote/trade condition, and Quote vs trade semantics appear in the same body of evidence as the selected rows. When a result is promoted, these fields should appear in the run manifest, rather than a prose summary or final equity curve.

In production notes for this backtesting workflow, REST snapshot, WebSocket stream, Entitlement gate, Quote freshness, Timestamp semantics, and Pagination cursor define the checks that decide whether the workflow is reproducible. The result is a backtest that can be rerun, compared across threshold families, and rejected when the evidence is not strong enough.

For Historical Options Replay for Event Studies, the practical acceptance test is simple: another developer should be able to read the body, identify the exact inputs, reproduce the request sequence, and explain the accepted and rejected rows without relying on the bottom terminology grid. If a phrase appears in the page vocabulary, it should correspond to a stored field, a validation check, a replay step, or an implementation decision in the backtesting workflow.

This is also the reason the article should not measure success only by the final chart, table, or headline metric. The better standard is whether the data path, timing model, entitlement state, and evidence trail survive review. When those pieces are written directly into the body, the terminology becomes part of the workflow readers can implement.

Event replay needs two clocks

An event study should keep the event clock separate from the market-data clock. The event clock says when the earnings release, macro print, filing, or news item became observable. The market-data clock says which chain snapshot, quote row, trade row, and aggregate bar existed before or after that event. Mixing those clocks is a quiet form of look-ahead leakage.

The replay artifact should include event timestamp, market session, underlying ticker, point-in-time contract request, selected OCC option symbol, DTE bucket, strike, right, implied volatility, Greeks, open interest, NBBO quote, quote condition, trade condition, and top-of-book size. If the event window spans a close or half-day, keep the session label and timestamp semantics explicit.

For provider-style discipline, store the endpoint, dataset, response envelope, pagination cursor, and cache key for every historical window. A replay that cannot rebuild the same quote window from those fields is not ready to support a conclusion about IV crush, gap risk, or post-event drift.