Summary
Performance
Historical returnsSnapshot
Key statisticsPrice Chart
Advanced chartCompareNotable Price Movement
Historical returnsPrice Performance
All periods| Period | Period Low | Period High | Performance | |
|---|---|---|---|---|
| 1-Month | 62,631.18 +27.42% on 08/16/26 | 81,479.50 -2.05% on 08/28/26 | +16,788.74 (+26.64%) since 08/15/26 | |
| 3-Month | 61,250.00 +30.30% on 07/06/26 | 81,479.50 -2.05% on 08/28/26 | +16,721.04 (+26.50%) since 07/04/26 | |
| 6-Month | 57,717.55 +38.27% on 07/01/26 | 82,814.23 -3.63% on 05/06/26 | +1,125.18 (+1.43%) since 05/02/26 | |
| YTD | 57,717.55 +38.27% on 07/01/26 | 97,963.62 -18.53% on 01/14/26 | -8,930.85 (-10.06%) since 01/01/26 | |
| 52-Week | 57,717.55 +38.27% on 07/01/26 | 97,963.62 -18.53% on 01/14/26 | -8,000.51 (-9.11%) since 12/27/25 | |
| 5-Year | 24,750.00 +222.45% on 06/15/23 | 126,296.00 -36.81% on 10/06/25 | +52,319.31 (+190.33%) since 03/25/23 |
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