Swept the lows and reclaimed (1h)
The last completed one-hour candle swept prior lows and closed back above them: the "bullish" sweep and reclaim formation on the hourly.
The live read is not yet enabled. This surface reports the historical base rates below; the firing-now list turns on when the live evaluator is connected.
What has happened when it held
Historically, when Swept the lows and reclaimed (1h) held (25,613 occurrences in the scanned window, 23,216 with a computable 24h horizon), the market reached +5% within 24h in 6,221 of 23,216 (26.8) and drew down 10%+ in 1,143 of 23,216 (4.9). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.
Outcome distribution
20,226 of 23,486 (86.1%) reached +0% or more within 1 hour · smallest move size with matches, picked for you
Pick a window and a move size: how often did a move at least that big follow?
🔒 Measured after every match, never by keeping winners. 23,486 of the matches have a complete 1 hour forward; the other 2,127 are too recent to know.
What are MFE and MAE?Why 72 hours can show fewer than 1 hour: a match too recent for a complete 72 hours is left out of that count entirely, even if it already reached the level within 1 hour. The two counts cover different sets of matches.
About 826 a day, on 31 of 31 days: spread through the record rather than one event.
Forward 30-minute returns across 22,243 matches: close to an even split, which is what a coin flip looks like.
How to read a distributionVersus baseline
Historically, when any eligible minute in the window (baseline) held (28,596,473 occurrences in the scanned window, 24,970,956 with a computable 24h horizon), the market reached +5% within 24h in 7,302,353 of 24,970,956 (29.2) and drew down 10%+ in 1,554,591 of 24,970,956 (6.2). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.
By market
Markets where this condition occurred often enough in the window to carry its own statistically meaningful receipt:
Check our work: the key that re-runs this exact count (q#ee5ea2d7)
- grammar
- research_query.v2
- normalization
- archive_normalization.v1
- feature library
- feature_defs.v1
- dataset revision
- 8904ef0442c6f623ec772df2b59d7baf1e49aaa808b5b11ac31546605549e3bb
- query hash
- ee5ea2d701eed01cabb49b3a48e6de90a00c1ad0cb787401fa146326c6dad2f4
- scanned window
- 2026-08-19T00:00:00.000Z to 2026-09-18T00:00:00.000Z (UTC)
Same key, same bytes. This receipt reruns; it does not retell. When the record grows, the dataset revision changes and says so.
Re-run this yourself, over the API or from an AI agent
This is the exact search definition behind the receipt. Send it to the key-authed research API (or the MCP research tool) and compare the bytes: a cached rerun is free.
{
"schema_version": "research_query.v2",
"normalization_version": "archive_normalization.v1",
"feature_version": "feature_defs.v1",
"target": "record_occurrences",
"where": {
"all": [
[
"feature.candle_sweep_reclaim_1h",
"eq",
"bullish"
],
[
"times.anchor_time",
"between",
[
"2026-08-19T00:00:00.000Z",
"2026-09-18T00:00:00.000Z"
]
]
]
},
"sort": [
"times.anchor_time",
"desc"
],
"page": {
"limit": 50,
"cursor": null
}
}curl -s https://app.edgedepth.com/api/v1/research/query \
-H 'authorization: Bearer $EDGEDEPTH_API_KEY' \
-H 'content-type: application/json' \
-d '{"schema_version":"research_query.v2","normalization_version":"archive_normalization.v1","feature_version":"feature_defs.v1","target":"record_occurrences","where":{"all":[["feature.candle_sweep_reclaim_1h","eq","bullish"],["times.anchor_time","between",["2026-08-19T00:00:00.000Z","2026-09-18T00:00:00.000Z"]]]},"sort":["times.anchor_time","desc"],"page":{"limit":50,"cursor":null}}'How to read this
- Counts ship with denominators: occurrences across the eligible symbol-buckets scanned. A rate is over the occurrences with a computable horizon (present), never the total.
- Absent is absent. When a feature was not warm at a minute, that bucket leaves the denominator and is reported; it is never coerced to zero.
- This selects a setup, never its outcome. The grammar forbids filtering on what followed (OUTCOME_IN_PREDICATE), so the distribution below is over every occurrence, not a survivorship-picked subset.
Occurrences are observed examples in a selected archive, not a guarantee. Outcomes are computed forward from each anchor and are descriptive, never a filter and never a prediction. Nothing here is trading advice.