Sectors Performance
Sector Price Performance Distribution
For Date: 2026-09-18
Performance Heatmap (%)
| Sector | 1 Day | 1 Week | 1 Month | 3 Months | 6 Months | YTD | 1 Year |
| Technology | 0.82 | 2.89 | 2.14 | -0.84 | 37.77 | 31.71 | 38.05 |
| Industrials | 0.44 | -0.11 | -7.53 | -5.94 | 3.30 | 8.01 | 12.56 |
| Financials | -0.04 | -2.05 | -3.42 | 4.65 | 15.06 | 2.57 | 4.80 |
| Health Care | -0.25 | 0.38 | -0.79 | 13.21 | 15.41 | 9.21 | 24.62 |
| Energy | -0.26 | -0.34 | 0.99 | 20.45 | 11.57 | 42.82 | 47.81 |
| Consumer Discretionary | -0.32 | -1.61 | -4.58 | -5.05 | 0.82 | -5.81 | -6.94 |
| Consumer Staples | -0.83 | -1.92 | -3.25 | 0.08 | 1.46 | 7.91 | 6.98 |
| Real Estate | -0.95 | -1.37 | -4.71 | -2.18 | 2.78 | 6.97 | 4.62 |
| Communication Services | -1.37 | -3.70 | 0.30 | 1.50 | -1.95 | -4.66 | -5.65 |
| Utilities | -1.42 | -1.72 | -6.63 | -7.60 | -10.87 | -3.54 | 0.07 |
| Materials | -1.42 | -0.99 | -3.46 | -3.16 | 3.95 | 9.27 | 12.01 |
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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