Sectors Performance
Sector Price Performance Distribution
For Date: 2026-09-28
Performance Heatmap (%)
| Sector | 1 Day | 1 Week | 1 Month | 3 Months | 6 Months | YTD | 1 Year |
| Health Care | 0.33 | 0.81 | 0.06 | 6.54 | 19.61 | 11.07 | 27.63 |
| Consumer Staples | 0.27 | -0.54 | -3.71 | -2.48 | 1.18 | 7.23 | 7.53 |
| Energy | 0.10 | 0.52 | -0.93 | 15.90 | 0.94 | 37.91 | 40.59 |
| Real Estate | -0.51 | -2.71 | -7.04 | -7.95 | 3.74 | 4.00 | 1.17 |
| Utilities | -0.66 | -3.16 | -8.14 | -14.71 | -13.98 | -7.89 | -7.93 |
| Materials | -0.66 | -2.10 | -6.98 | -2.35 | 1.14 | 8.13 | 12.43 |
| Technology | -0.89 | -0.89 | 4.76 | 4.92 | 52.75 | 35.14 | 39.33 |
| Industrials | -0.97 | -0.88 | -4.72 | -7.65 | 8.03 | 7.39 | 11.24 |
| Financials | -1.19 | -1.11 | -6.73 | 0.87 | 12.45 | -0.50 | 1.33 |
| Consumer Discretionary | -1.41 | -2.96 | -7.00 | -6.93 | 3.37 | -7.53 | -8.91 |
| Communication Services | -1.58 | -2.07 | -1.60 | 3.06 | 3.25 | -4.34 | -5.37 |
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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