Up/Down Trends
Streak Statistics
Streak-Length Distribution & Average Return
| Streak Length (days) | Up Streaks | Avg Up Return | Down Streaks | Avg Down Return |
| 1 | 6 | 4.62% | 10 | -3.97% |
| 2 | 6 | 5.33% | 5 | -7.74% |
| 3 | 3 | 6.24% | 2 | -13.80% |
| 4 | 0 | – | 0 | – |
| 5+ | 2 | 14.37% | 0 | – |
| Total | 17 | – | 17 | – |
Longest Streaks on Record
| Record | Days | From | First Price | Last Price | Return |
| Longest UP streak | 6 | Jun 10, 2026 | 7,730.82 | 9,063.84 | 17.24% |
| Longest DOWN streak | 3 | Jul 3, 2026 | 8,088.34 | 7,246.79 | -10.40% |
Momentum vs. Mean-Reversion
| Today \ Tomorrow | Up | Down |
| Up | 55.3% | 44.7% |
| Down | 64.0% | 36.0% |
Seasonality
By Day of Week
| Weekday | Days | Up (%) | Avg Daily Return |
| Monday | 12 | 50.0% | -0.811% |
| Tuesday | 13 | 61.5% | -1.325% |
| Wednesday | 13 | 61.5% | -0.120% |
| Thursday | 14 | 64.3% | 0.289% |
| Friday | 12 | 58.3% | 1.809% |
By Month of Year
| Month | Days | Up (%) | Avg Daily Return |
| January | 0 | – | – |
| February | 0 | – | – |
| March | 0 | – | – |
| April | 0 | – | – |
| May | 0 | – | – |
| June | 14 | 71.4% | 0.744% |
| July | 22 | 45.5% | -0.943% |
| August | 20 | 65.0% | 0.214% |
| September | 8 | 62.5% | 0.412% |
| October | 0 | – | – |
| November | 0 | – | – |
| December | 0 | – | – |
Price Chart with Up/Down Rally Indicators

Historical Up/Down Days and Returns
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.
Or start with