Summary
Performance
Historical returnsSnapshot
Key statisticsPrice Chart
Advanced chartCompareNotable Price Movement
Historical returnsPrice Performance
All periods| Period | Period Low | Period High | Performance | |
|---|---|---|---|---|
| 1-Month | -6.0000 -1,650.00% on 04/01/26 | 120.0000 -22.50% on 04/17/26 | +91.0000 (+4,550.00%) since 03/31/26 | |
| 3-Month | -178.0000 -152.25% on 03/20/26 | 260.0000 -64.23% on 02/06/26 | -25.0000 (-21.19%) since 01/29/26 | |
| 6-Month | -178.0000 -152.25% on 03/20/26 | 260.0000 -64.23% on 02/06/26 | +69.0000 (+287.50%) since 10/28/25 | |
| YTD | -178.0000 -152.25% on 03/20/26 | 260.0000 -64.23% on 02/06/26 | +65.0000 (+232.14%) since 01/02/26 | |
| 52-Week | -178.0000 -152.25% on 03/20/26 | 260.0000 -64.23% on 02/06/26 | +72.0000 (+342.86%) since 04/29/25 | |
| 5-Year | -657.0000 -114.16% on 04/08/25 | 346.0000 -73.12% on 05/07/21 | -123.0000 (-56.94%) since 04/23/21 |
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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