Sectors Performance
Sector Price Performance Distribution
For Date: 2026-10-01
Performance Heatmap (%)
| Sector | 1 Day | 1 Week | 1 Month | 3 Months | 6 Months | YTD | 1 Year |
| Energy | 1.95 | 1.06 | -3.20 | 18.73 | 7.09 | 39.24 | 43.48 |
| Technology | 1.05 | 0.78 | 7.72 | 6.57 | 46.80 | 37.42 | 39.55 |
| Industrials | 0.99 | -1.05 | -2.37 | -8.03 | 2.81 | 7.30 | 10.60 |
| Utilities | 0.61 | 0.43 | -6.77 | -11.37 | -13.40 | -6.88 | -7.98 |
| Financials | 0.11 | -2.52 | -6.54 | -2.41 | 8.53 | -1.84 | 1.35 |
| Consumer Discretionary | -0.03 | -1.58 | -5.04 | -7.86 | -0.70 | -7.69 | -9.21 |
| Materials | -0.33 | -2.53 | -6.78 | -4.86 | -3.44 | 6.10 | 10.95 |
| Consumer Staples | -0.34 | -2.11 | -5.77 | -3.57 | -0.70 | 4.69 | 4.79 |
| Real Estate | -0.56 | -2.12 | -7.63 | -7.92 | 0.20 | 2.31 | -0.85 |
| Communication Services | -0.93 | -2.67 | -0.85 | 0.18 | -0.92 | -5.41 | -4.95 |
| Health Care | -1.32 | -2.64 | -3.19 | 4.17 | 13.00 | 7.79 | 17.32 |
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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