Summary
Performance
Historical returnsSnapshot
Key statisticsPrice Chart
Advanced chartCompareNotable Price Movement
Historical returnsPrice Performance
All periods| Period | Period Low | Period High | Performance | |
|---|---|---|---|---|
| 1-Month | 44.4685 +34.51% on 03/31/26 | 64.1734 -6.79% on 04/20/26 | +15.3471 (+34.51%) since 03/31/26 | |
| 3-Month | 37.2017 +60.79% on 03/20/26 | 64.1734 -6.79% on 04/20/26 | -1.1507 (-1.89%) since 01/29/26 | |
| 6-Month | 37.2017 +60.79% on 03/20/26 | 67.3370 -11.17% on 01/22/26 | -0.9923 (-1.63%) since 10/28/25 | |
| YTD | 37.2017 +60.79% on 03/20/26 | 67.3370 -11.17% on 01/22/26 | +5.1068 (+9.33%) since 01/02/26 | |
| 52-Week | 22.4750 +166.14% on 04/30/25 | 71.2877 -16.09% on 09/18/25 | +36.9521 (+161.62%) since 04/29/25 | |
| 5-Year | 8.7729 +581.82% on 04/08/25 | 79.9742 -25.21% on 04/27/21 | -17.9263 (-23.06%) 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.
Or start with