Historical Prices
Historical Stats
| Low | High | Average | |
|---|---|---|---|
| Close | 314.47 2025-03-13 | 519 days ago |
706.82 2026-02-17 | 178 days ago |
478.26 |
| Open | 329.00 2025-03-13 | 519 days ago |
700.10 2026-02-18 | 177 days ago |
478.21 |
| High | 329.00 2025-03-13 | 519 days ago |
700.10 2026-02-18 | 177 days ago |
478.21 |
| Low | 309.01 2025-03-13 | 519 days ago |
689.00 2026-02-09 | 186 days ago |
471.74 |
| Volume | 211,400 2025-12-24 | 233 days ago |
4,999,800 2024-08-30 | 714 days ago |
850,584 |
| Price Volume | 128,641,128 2025-12-24 | 233 days ago |
2,166,133,342 2025-05-30 | 441 days ago |
387,988,544 |
| Change | -88.98 2026-03-13 | 154 days ago |
67.55 2025-12-05 | 252 days ago |
0.29 |
| Change % | -14.24 2026-03-13 | 154 days ago |
13.68 2025-03-14 | 518 days ago |
0.09 |
Historical Prices
Ask 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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