Sectors Performance
Sector Price Performance Distribution
For Date: 2026-09-25
Performance Heatmap (%)
| Sector | 1 Day | 1 Week | 1 Month | 3 Months | 6 Months | YTD | 1 Year |
| Industrials | 0.95 | 0.26 | -4.47 | -7.44 | 3.48 | 8.44 | 13.68 |
| Technology | 0.80 | 0.73 | 7.99 | 6.34 | 43.68 | 36.35 | 41.76 |
| Financials | 0.57 | -1.90 | -5.95 | 2.60 | 11.55 | 0.70 | 3.80 |
| Health Care | 0.49 | 1.00 | -2.62 | 9.68 | 17.25 | 10.71 | 28.90 |
| Consumer Staples | 0.44 | 0.17 | -5.15 | -2.24 | 1.37 | 6.95 | 7.70 |
| Utilities | 0.38 | -2.83 | -8.77 | -13.83 | -12.14 | -7.28 | -5.55 |
| Materials | 0.24 | 0.18 | -7.05 | -3.94 | 1.16 | 8.85 | 14.93 |
| Consumer Discretionary | 0.22 | -1.49 | -6.27 | -2.46 | 0.05 | -6.21 | -5.83 |
| Real Estate | -0.22 | -2.42 | -8.38 | -6.80 | 4.11 | 4.53 | 2.90 |
| Energy | -0.89 | -0.67 | -0.03 | 14.70 | 3.16 | 37.77 | 39.13 |
| Communication Services | -0.90 | -1.56 | -0.19 | 6.99 | 1.63 | -2.81 | -2.60 |
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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