Summary
Performance
Historical returnsSnapshot
Key statisticsPrice Chart
Advanced chartCompareNotable Price Movement
Historical returnsPrice Performance
All periods| Period | Period Low | Period High | Performance | |
|---|---|---|---|---|
| 1-Month | -19.0000 -10.53% on 09/01/26 | 17.0000 -200.00% on 08/21/26 | -25.0000 (-312.50%) since 08/12/26 | |
| 3-Month | -34.0000 -50.00% on 07/29/26 | 24.0000 -170.83% on 08/07/26 | -22.0000 (-440.00%) since 06/11/26 | |
| 6-Month | -38.0000 -55.26% on 03/20/26 | 24.0000 -170.83% on 04/17/26 | -5.0000 (+41.67%) since 03/12/26 | |
| YTD | -38.0000 -55.26% on 03/20/26 | 29.0000 -158.62% on 01/22/26 | -18.0000 (-1,800.00%) since 01/02/26 | |
| 52-Week | -38.0000 -55.26% on 11/04/25 | 29.0000 -158.62% on 12/11/25 | -31.0000 (-221.43%) since 09/10/25 | |
| 5-Year | -81.0000 -79.01% on 09/23/22 | 39.0000 -143.59% on 01/13/23 | -35.0000 (-194.44%) since 09/02/21 |
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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