typical_move
Answered against 22 years of US equities and 12 years of US options data and published with the query that produced it. This result is stored as of 2026-09-27, from how-much-to-risk-per-trade.
| ticker | median_move_pct | p90_move_pct |
|---|---|---|
| NVDA | 1.85 | 5.12 |
| MSFT | 0.94 | 2.7 |
| AAPL | 0.88 | 2.77 |
| KO | 0.6 | 1.65 |
| SPY | 0.57 | 1.68 |
- Rows × columns
- 5 × 3
- Computed
- Completeness
- No missing values
- Source
- US exchange, SIP and OPRA market data
- Licence
- Strasmore terms · free, no signup
What each column holds
| Column | Type | Range | Notes |
|---|---|---|---|
ticker |
text | 5 distinct values (AAPL, KO, MSFT…) | |
median_move_pct |
number | 0.57 to 1.85 | percent |
p90_move_pct |
number | 1.65 to 5.12 | percent |
Computed from Strasmore's warehouse of US exchange, SIP and OPRA market data. Equity prices are delayed; options greeks and implied volatility are end-of-day. This result is stored, not recomputed on load — it is exactly the numbers that were returned on , and the query below is what returned them.
Run it yourself
This is the exact query behind the result above. Change a ticker, a date or a column and run it against the warehouse — no account, no key. The no-signup tier is smaller than the one this page was computed on; a query that reaches past it comes back saying which plan runs it.
SELECT
ticker,
round(quantileDeterministic(0.5)(move_pct, day_key), 2) AS median_move_pct,
round(quantileDeterministic(0.9)(move_pct, day_key), 2) AS p90_move_pct
FROM
(
SELECT
ticker,
toUInt32(date) AS day_key,
abs(100 * (toFloat64(close) / toFloat64(prev_close) - 1)) AS move_pct
FROM
(
SELECT
ticker,
date,
close,
lagInFrame(close) OVER (PARTITION BY ticker ORDER BY date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prev_close
FROM global_markets.stocks_daily_aggs
WHERE ticker IN ('AAPL', 'MSFT', 'NVDA', 'SPY', 'KO')
AND date >= '2021-09-01'
AND date < '2026-09-01'
)
WHERE toFloat64(prev_close) > 0
)
GROUP BY ticker
ORDER BY median_move_pct DESC
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