Summary
Performance
Historical returnsSnapshot
Key statisticsPrice Chart
Advanced chartCompareNotable Price Movement
Historical returnsPrice Performance
All periods| Period | Period Low | Period High | Performance | |
|---|---|---|---|---|
| 1-Month | 665.0000 +89.62% on 08/21/26 | 1,426.0000 -11.57% on 09/01/26 | +318.0000 (+33.72%) since 08/11/26 | |
| 3-Month | 490.0000 +157.35% on 07/03/26 | 1,485.0000 -15.08% on 07/08/26 | +281.0000 (+28.67%) since 06/11/26 | |
| 6-Month | 353.0000 +257.22% on 04/08/26 | 1,808.0000 -30.25% on 03/19/26 | +712.0000 (+129.69%) since 03/10/26 | |
| YTD | 353.0000 +257.22% on 04/08/26 | 1,909.0000 -33.94% on 03/03/26 | +319.0000 (+33.86%) since 01/02/26 | |
| 52-Week | 353.0000 +257.22% on 04/08/26 | 1,909.0000 -33.94% on 03/03/26 | +146.0000 (+13.09%) since 09/10/25 | |
| 5-Year | 246.0000 +412.60% on 10/04/22 | 2,048.0000 -38.43% on 04/04/25 | +246.0000 (+24.24%) 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.
Or start with