Layered: UOA × quant

Unusual Options Activity for Quant Research

Define unusual-activity rules as testable SQL, measure hit rates over weeks of prints, then deploy thresholds to the real-time WebSocket without a black-box vendor score.

Who this is for: quant and systematic desks that treat UOA as a feature research problem — not a retail heatmap. You own labels and thresholds; OptionData provides OPRA prints, chains, and 2.8B+ historical rows.

From hypothesis to live UOA monitor

Codify rules, estimate false positives historically, attach chain context, then stream survivors.

State the rule in SQL

Example: premium ≥ $100k, DTE ≤ 14, repeated prints, optional |delta| bands — all queryable on RawOptionTrades.

Measure base rates

Count how often the rule fires per symbol/day over multi-week windows before wiring alerts.

Join chain context

Pull IV, OI, and bid/ask around event times so labels include liquidity and surface state.

Deploy to WebSocket filters

Translate surviving thresholds into server-side stream filters and online scorers.

What “unusual” can mean in research

  • Large premium vs recent symbol baseline
  • Short-dated clustering into a single expiry
  • Size relative to open interest (via chain join)
  • Repeated same-strike prints within a time window
  • AGGREGATED sweep-like consolidations
  • Custom desk labels — never forced by OptionData
Example: 30-day short-dated large-premium clusters
SELECT
  symbol,
  expiration,
  strike,
  side,
  sum(size * price * 100) AS premium,
  max(implied_volatility) AS max_iv,
  avg(abs(delta)) AS avg_abs_delta,
  count() AS prints
FROM RawOptionTrades
WHERE date BETWEEN today() - 30 AND today()
  AND premium >= 100000
  AND days_to_expiration <= 14
GROUP BY symbol, expiration, strike, side
HAVING prints >= 3
ORDER BY premium DESC
LIMIT 100;

UOA research graph

Connect UOA product, quant flow, and glossary IV/OI pages.

UOA for quant FAQ

Does OptionData sell a proprietary UOA score?

No. It provides the data plane (stream, SQL, chains). Detection logic and labels are defined by your research.

Can I backtest UOA rules?

Yes. Historical SQL over stored option trades supports multi-day and multi-week rule evaluation with premium, Greeks, IV, and contract fields.

How do I avoid overfitting alert rules?

Hold out calendar weeks, track alert frequency per symbol, and require stability across AGGREGATED vs RAW if both modes matter to production.

Where do I start if I am new to UOA?

Start with the unusual options activity API overview, then return here for the research loop and SQL examples.