Summary
Performance
Historical returnsSnapshot
Key statisticsPrice Chart
Advanced chartCompareBull vs Bear
4 bullish · 2 bearish points- Holds 198.7% above its 200-day average.
- Has recovered 1,801.4% off the 52-week low of $0.01.
- Outperformed the S&P 500 by 1,796.7% over the last quarter (+1,801.4% against +4.7%).
- FY2026 earnings rose 220.5% to -$824.9K.
- Still 33.4% below its 52-week high of $0.20.
- Revenue fell 100.0% year on year in the Apr 2026 quarter.
Notable Price Movement
Historical returnsPrice Performance
All periods| Period | Period Low | Period High | Performance | |
|---|---|---|---|---|
| 1-Month | 0.13 +3.58% on 08/31/26 | 0.20 -33.42% on 08/18/26 | -0.01 (-4.93%) since 07/27/26 | |
| 3-Month | 0.01 +1,801.43% on 07/17/25 | 0.20 -33.42% on 07/01/26 | +0.13 (+1,801.43%) since 07/17/25 | |
| 6-Month | 0.01 +1,801.43% on 07/01/25 | 0.20 -33.42% on 07/01/26 | +0.07 (+127.52%) since 04/16/25 | |
| YTD | 0.13 +3.58% on 08/31/26 | 0.20 -33.42% on 07/01/26 | -0.05 (-26.04%) since 06/26/26 | |
| 52-Week | 0.01 +1,801.43% on 07/01/25 | 0.20 -33.42% on 07/01/26 | +0.12 (+977.73%) since 10/22/24 |
New Highs
Historical highsFinancial SnapshotFY 2026
Full financialsAsk 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