Sectors Performance
Sector Price Performance Distribution
For Date: 2026-09-22
Performance Heatmap (%)
| Sector | 1 Day | 1 Week | 1 Month | 3 Months | 6 Months | YTD | 1 Year |
| Materials | 1.80 | -2.01 | -7.15 | -3.70 | 4.92 | 8.66 | 11.48 |
| Consumer Staples | 0.99 | -2.16 | -4.73 | -0.32 | 1.61 | 6.76 | 7.25 |
| Technology | 0.73 | 6.05 | 6.30 | 1.41 | 42.44 | 35.36 | 38.42 |
| Health Care | 0.70 | 0.81 | -3.21 | 12.63 | 17.26 | 9.61 | 25.29 |
| Industrials | 0.29 | 0.67 | -5.70 | -6.50 | 4.51 | 8.16 | 12.06 |
| Consumer Discretionary | 0.18 | 1.22 | -4.91 | -2.36 | 2.12 | -4.79 | -5.98 |
| Real Estate | -0.16 | -1.11 | -5.52 | -3.25 | 5.76 | 7.12 | 4.95 |
| Utilities | -0.26 | -1.60 | -4.93 | -9.08 | -8.63 | -4.58 | -2.54 |
| Energy | -0.90 | -5.26 | -1.85 | 15.54 | 5.49 | 38.71 | 45.63 |
| Communication Services | -1.08 | 0.63 | 3.01 | 7.38 | 2.07 | -1.27 | -2.36 |
| Financials | -1.93 | -1.67 | -2.75 | 4.10 | 13.85 | 2.64 | 4.78 |
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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