Volatility Analysis
Historical Standard Deviation
| Period | Value |
| 1 Week | 0.69 |
| 20 Days | 1.43 |
| 1 Month | 1.54 |
| 3 Months | 2.19 |
| 100 Days | 2.70 |
| 6 Months | 2.66 |
| Year-to-date | 6.27 |
| 1 Year | 12.64 |
| 3 Years | 16.65 |
| 5 Years | 64.54 |
Historical Volatility
Historical Volatility Returns (%) By Years/Months
| Year | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | Min | Max | avg |
| 2026 | 26.91 | 35.41 | 1.74 | -8.11 | -15.70 | -3.54 | -28.12 | 49.34 | -28.12 | 49.34 | 7.24 | ||||
| 2025 | -16.95 | 58.08 | -3.92 | -44.48 | -44.48 | 58.08 | -1.82 | ||||||||
| Summary | |||||||||||||||
| Avg Returns (%) | 26.91 | 35.41 | 1.74 | -8.11 | -15.70 | -3.54 | -28.12 | 49.34 | -16.95 | 58.08 | -3.92 | -44.48 | -44.48 | 58.08 | 4.22 |
| Max Pos Return (%) | 26.91 | 35.41 | 1.74 | -8.11 | -15.70 | -3.54 | -28.12 | 49.34 | -16.95 | 58.08 | -3.92 | -44.48 | -44.48 | 58.08 | 4.22 |
| Max Neg Return (%) | 26.91 | 35.41 | 1.74 | -8.11 | -15.70 | -3.54 | -28.12 | 49.34 | -16.95 | 58.08 | -3.92 | -44.48 | -44.48 | 58.08 | 4.22 |
| Pos Occurances (%) | 100 | 100 | 100 | 0 | 0 | 0 | 0 | 100 | 0 | 100 | 0 | 0 | 0 | 100 | 42 |
| Neg Occurance (%) | 0 | 0 | 0 | 100 | 100 | 100 | 100 | 0 | 100 | 0 | 100 | 100 | 0 | 100 | 58 |
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
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Your own documents
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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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