Flow for quant research

Options Flow API for Quant Research

Design flow features on the live WebSocket, then prove them on the same field schema in historical SQL. avoiding train/serve skew between research and production.

For quant researchers who need both a live options tape (~10M/day) and a SQL warehouse (2.8B+ trades from Feb 2025+) with consistent Greeks/IV/premium semantics.

Quant research hub Historical SQL docs

Live feature → historical proof → production

Keep one definition of premium, delta bands, and DTE filters across stream and SQL.

Prototype on the stream

Use server-side filters to sample high-premium or short-dated flow without drowning notebooks in every print.

Log feature vectors

Persist minute bars or event features (premium, |delta|, IV) with the same formulas you will run live.

Backtest in ClickHouse

Replay multi-week windows via historical SQL with row/timeout guardrails appropriate to research jobs.

Deploy unchanged thresholds

Promote filters to production WebSocket params and monitor drift against the SQL baseline.

Quant-specific flow concerns

Train/serve consistency between SQL and WebSocket fields
AGGREGATED vs RAW choice affects sweep statistics
Trial SQL row caps. use full plan for serious backtests
Chain snapshots for surface context at event time
OPRA-licensed prints for professional research use under plan terms
See also: options data API for quant hub

Example: validate a live premium/sentiment feature in SQL

SELECT
  toStartOfMinute(time) AS minute,
  sumIf(toFloat64(price) * size * 100, put_call = 'CALL') AS call_premium,
  sumIf(toFloat64(price) * size * 100, put_call = 'PUT') AS put_premium,
  avg(abs(delta)) AS avg_abs_delta
FROM RawOptionTrades
WHERE date = (SELECT max(date) FROM RawOptionTrades)
  AND symbol = 'SPY'
  AND toFloat64(price) * size * 100 >= 50000
GROUP BY minute
ORDER BY minute
LIMIT 1000

Quant stack links

See also the quant hub and UOA-for-quant pages.

Options flow for quants FAQ

Can I research only on historical SQL without the live feed?

Yes. Many studies start in SQL. The layered value is promoting the same features to WebSocket without redefining fields.

Does AGGREGATED mode change research results?

Yes. AGGREGATED merges same-contract same-instant prints; RAW keeps every exchange print. Pick one mode and keep it consistent from backtest to prod.

How far back does history go?

OptionData stores option trades from February 2025 onward. 2.8B+ rows at time of writing. queryable via ClickHouse SQL over REST.

Are Greeks model-based?

Greeks and IV are analytics estimates under model assumptions. Use them as features, not as guaranteed P&L.