Seasonality Analysis
Historical Prices Year-by-Year
Historical Returns (%) By Years/Months
| Year | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | Min | Max | avg |
| 2026 | 8.77 | 13.32 | -9.53 | 17.19 | 5.71 | 14.34 | -15.35 | 5.47 | -15.35 | 17.19 | 4.99 | ||||
| 2025 | -13.75 | -7.77 | 0.42 | 15.97 | 17.50 | 6.68 | -4.45 | 21.35 | 7.57 | -2.97 | 4.52 | -13.75 | 21.35 | 4.10 | |
| Summary | |||||||||||||||
| Avg Returns (%) | 8.77 | -0.22 | -8.65 | 8.81 | 10.84 | 15.92 | -4.34 | 0.51 | 21.35 | 7.57 | -2.97 | 4.52 | -8.65 | 21.35 | 5.18 |
| Max Pos Return (%) | 8.77 | 13.32 | -7.77 | 17.19 | 15.97 | 17.50 | 6.68 | 5.47 | 21.35 | 7.57 | -2.97 | 4.52 | -7.77 | 21.35 | 8.97 |
| Max Neg Return (%) | 8.77 | -13.75 | -9.53 | 0.42 | 5.71 | 14.34 | -15.35 | -4.45 | 21.35 | 7.57 | -2.97 | 4.52 | -15.35 | 21.35 | 1.39 |
| Pos Occurances (%) | 100 | 50 | 0 | 100 | 100 | 100 | 50 | 50 | 100 | 100 | 0 | 100 | 0 | 100 | 71 |
| Neg Occurance (%) | 0 | 50 | 100 | 0 | 0 | 0 | 50 | 50 | 0 | 0 | 100 | 0 | 0 | 100 | 29 |
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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