What the next session did: 36 large caps bucketed by the prior day's move, Aug 2024 to Jul 2026
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 2026-08-01, from AI Daily Market Research Reports: What Breaks.
| prior_day_bucket | ticker_day_count | prior_day_move_pct | next_day_move_pct | same_direction_pct |
|---|---|---|---|---|
| fell 3% or more | 649 | -4.33 | 0.474 | 47.3 |
| fell 1% to 3% | 3219 | -1.69 | 0.046 | 49.5 |
| moved less than 1% | 10100 | 0.01 | 0.009 | 50.3 |
| rose 1% to 3% | 3430 | 1.67 | -0.039 | 50.2 |
| rose 3% or more | 602 | 4.57 | -0.102 | 49.3 |
- Rows × columns
- 5 × 5
- 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 |
|---|---|---|---|
prior_day_bucket |
text | 5 distinct values | |
ticker_day_count |
number | 602 to 10,100 | count |
prior_day_move_pct |
number | -4.33 to 4.57 | percent |
next_day_move_pct |
number | -0.102 to 0.474 | percent |
same_direction_pct |
number | 47.3 to 50.3 | 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.
WITH daily AS (
SELECT ticker,
toDate(toTimeZone(window_start, 'America/New_York')) AS d,
(argMax(close, window_start) / argMin(open, window_start) - 1) * 100 AS move_pct
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('AAPL','MSFT','NVDA','AMZN','GOOGL','META','TSLA','AVGO','JPM','XOM',
'JNJ','WMT','PG','KO','HD','CVX','MRK','PEP','COST','CSCO',
'ORCL','CRM','AMD','NFLX','DIS','BA','CAT','IBM','T','VZ',
'PFE','NKE','MCD','UNH','BAC','QCOM')
AND toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2024-08-01')
AND toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-07-31')
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
+ toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
GROUP BY ticker, d
),
paired AS (
SELECT ticker,
d,
move_pct,
leadInFrame(move_pct) OVER (PARTITION BY ticker ORDER BY d ASC
ROWS BETWEEN 1 FOLLOWING AND 1 FOLLOWING) AS next_move_pct,
row_number() OVER (PARTITION BY ticker ORDER BY d ASC) AS rn,
count() OVER (PARTITION BY ticker) AS session_total
FROM daily
),
labelled AS (
SELECT multiIf(move_pct <= -3, 'fell 3% or more',
move_pct <= -1, 'fell 1% to 3%',
move_pct < 1, 'moved less than 1%',
move_pct < 3, 'rose 1% to 3%',
'rose 3% or more') AS prior_day_bucket,
multiIf(move_pct <= -3, 1,
move_pct <= -1, 2,
move_pct < 1, 3,
move_pct < 3, 4,
5) AS bucket_rank,
move_pct,
next_move_pct
FROM paired
WHERE rn < session_total
)
SELECT prior_day_bucket,
count() AS ticker_day_count,
round(avg(move_pct), 2) AS prior_day_move_pct,
round(avg(next_move_pct), 3) AS next_day_move_pct,
round(100 * countIf((move_pct > 0) = (next_move_pct > 0)) / count(), 1) AS same_direction_pct
FROM labelled
GROUP BY prior_day_bucket, bucket_rank
ORDER BY bucket_rank ASC
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