State the rule in SQL
Example: premium ≥ $100k, DTE ≤ 14, repeated prints, optional |delta| bands. all queryable on RawOptionTrades.
UOA for quant research
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 vendor score.
For quant and systematic desks that treat UOA as a feature research problem. You own labels and thresholds. OptionData provides OPRA prints, chains, and SQL over the past 15 days of trades.
Check access before integrating
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Research artifacts
- You define
- UOA rules
- 30d+
- SQL windows
- Live
- same filters on WS
From hypothesis to live UOA monitor
Codify rules, estimate false positives historically, attach chain context, then stream survivors.
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: 7-day short-dated large-premium clusters for NVDA
SELECT
symbol,
expiration_date,
strike,
put_call,
sum(toFloat64(price) * size * 100) AS premium,
max(iv) AS max_iv,
avg(abs(delta)) AS avg_abs_delta,
count() AS prints
FROM RawOptionTrades
WHERE date >= today() - 7
AND symbol = 'NVDA'
AND toFloat64(price) * size * 100 >= 100000
AND dateDiff('day', date, expiration_date) <= 14
GROUP BY symbol, expiration_date, strike, put_call
HAVING prints >= 3
ORDER BY premium DESC
LIMIT 100UOA research graph
See also the UOA product page, quant flow guide, and OI glossary.
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.