Sectors Performance
Sector Price Performance Distribution
For Date: 2026-09-10
Performance Heatmap (%)
| Sector | 1 Day | 1 Week | 1 Month | 3 Months | 6 Months | YTD | 1 Year |
| Communication Services | 0.50 | -1.41 | -0.89 | -0.32 | -5.18 | -4.65 | -2.81 |
| Consumer Staples | 0.07 | -2.90 | -2.24 | -0.56 | -2.18 | 8.24 | 5.73 |
| Financials | -0.31 | -1.04 | -1.30 | 9.14 | 14.35 | 4.77 | 8.64 |
| Energy | -0.46 | 0.32 | 8.52 | 14.62 | 17.55 | 45.04 | 53.78 |
| Health Care | -0.52 | -3.68 | -1.10 | 8.25 | 8.91 | 8.04 | 22.29 |
| Consumer Discretionary | -0.53 | -2.09 | -6.02 | -2.75 | -1.46 | -4.60 | -3.83 |
| Utilities | -0.75 | 0.63 | -0.44 | -1.74 | -7.12 | 0.77 | 6.10 |
| Industrials | -0.78 | -0.57 | -6.94 | -1.93 | 1.02 | 9.31 | 15.80 |
| Real Estate | -0.90 | -0.73 | -2.23 | -2.62 | 2.58 | 9.18 | 7.24 |
| Materials | -1.28 | -2.95 | -3.37 | 1.60 | 3.63 | 12.33 | 15.59 |
| Technology | -1.36 | 2.33 | 0.83 | 4.05 | 34.75 | 30.51 | 42.35 |
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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