Summary
Performance
Historical returnsSnapshot
Key statisticsPrice Chart
Advanced chartCompareNotable Price Movement
Historical returnsPrice Performance
All periods| Period | Period Low | Period High | Performance | |
|---|---|---|---|---|
| 1-Month | 46.0000 +8.70% on 09/09/26 | 105.0000 -52.38% on 08/11/26 | -55.0000 (-52.38%) since 08/11/26 | |
| 3-Month | 38.0000 +31.58% on 07/08/26 | 178.0000 -71.91% on 06/18/26 | -32.0000 (-39.02%) since 06/11/26 | |
| 6-Month | 26.0000 +92.31% on 03/23/26 | 270.0000 -81.48% on 05/26/26 | -10.0000 (-16.67%) since 03/10/26 | |
| YTD | 0.0000 on 01/02/26 | 1,301.0000 -96.16% on 01/05/26 | +50.0000 (+0.00%) since 01/02/26 | |
| 52-Week | 0.0000 on 01/02/26 | 1,301.0000 -96.16% on 01/05/26 | -113.0000 (-69.33%) since 09/10/25 | |
| 5-Year | 0.0000 on 01/02/24 | 1,311.0000 -96.19% on 01/04/23 | -27.0000 (-35.06%) since 09/09/21 |
New Highs
Historical highsAsk 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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