Options
Positioning Shift
Chain as of 2 Sep 2026 · 3,144 of 3,144 symbols currentDirectional exposure added or removed overnight, from the change in open interest weighted by delta. Open interest is what somebody was willing to carry — volume counts everything opened and closed inside the session. This is not order-flow sentiment: signing a trade buy or sell needs a per-print tape with trade-time quotes, which we do not receive, and a closing-print classifier would mark almost the entire market "sold".
▲ Delta added
most contracts of delta opened▼ Delta removed
most contracts of delta closed or soldGamma concentration by strike
Δ added sums each contract’s overnight change in open interest multiplied by its delta and by 100, so it is in shares of delta. % of OI divides that by the same book measured in shares, which is how much of the existing position the day moved. Put deltas are negative, so opening puts subtracts and closing them adds — the sign is the direction of exposure, not the direction of trading. Gamma is shown gross, calls and puts separately, rather than as a single net dealer-gamma line: netting requires assuming which side of every open contract the market maker holds, and that assumption is not in our data. Where gamma is concentrated is observable and is where hedging flow gathers; who is short it is not.
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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