Options
Trade Ideas
Chain as of 4 Sep 2026 · 3,213 of 3,730 symbols currentEvery option structure worth a look across the liquid universe, in one ranked list. Edge is what the position costs against what it is worth priced at the stock’s own realised volatility — positive means the market is paying you more than the recent past says it should. Win rate is measured from a decade of the underlying’s actual moves, not from a bell curve, and carries the number of observations behind it.
Prices are what you would pay, not mid. Every leg is bought at the ask and sold at the bid, because a structure priced at the midpoint looks better than anything you can actually trade. Legs quoting a spread wider than a third of their own mid are dropped for the same reason — a wide market manufactures edge that is not there. Theoretical is Black-Scholes at the stock’s realised volatility, blended across a month and a year and capped at 1.8× the market’s own implied vol: a realised estimate further from the market than that is a regime change rather than a mispricing, and without the cap one earnings gap put a 1,186% edge at the top of this board. Win rate settles each structure at expiry against a decade of the underlying’s own overlapping windows, re-centred so the average outcome is today’s price — option prices assume no drift, and a stock that has risen a hundredfold must not be allowed to assume it happens again. Model POP is the lognormal probability the same tools usually quote, kept for comparison. Every leg sits between 10 and 90 delta: further out than that, option value is so vol-sensitive that any model and the market disagree violently, and the disagreement is not a trade. None of this is advice, and none of it accounts for commissions, assignment or what the position does before expiry.
Ask the market a question. Get a calculated answer.
The AI is not a chatbot bolted onto a document store. It calls the same analytics engine that powers every screen on this platform — so what comes back is a number it computed from raw history, with the command that produced it.
86,000+ instruments
Global equities, ETFs, funds, options, FX, commodities, crypto, economics, filings, transcripts and news — one normalised symbol universe with adjusted history.
A real analytics engine
Screening, backtesting, technicals, options analytics, correlations, seasonality and factor models — computed on demand from raw prices, never a stale cache.
It shows its working
Answers arrive with the charts, tables and tool calls behind them, so you can check the number instead of trusting a paraphrase.
Your own documents
Upload filings, decks and research. Ask across them and the answer cites the page it came from.
Agents and workflows
Multi-step research that runs the platform's tools for you — screen, pull the history, compute, compare, then write it up.
MCP, CLI and API
The same command catalogue from Claude, your own agent, a shell or your pipeline. The answer on screen is the answer your job gets at 4am.
You ask
“How does NVDA usually trade through earnings?”
It calls
→ ka.options_expected_move(NVDA)
It answers
NVDA has averaged a 9.2% absolute move on the day after earnings and closed higher 67% of the time. Two in three reactions land between −4.2% and +16.3% — the distribution is skewed right, not symmetric.
Every figure computed live from our own history — not scraped, not summarised.
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