Swept the lows and reclaimed (1h) on AKEUSDT
The last completed one-hour candle swept prior lows and closed back above them: the "bullish" sweep and reclaim formation on the hourly.
What has happened on AKEUSDT when it held
Historically, when Swept the lows and reclaimed (1h) on AKEUSDT held (30 occurrences in the scanned window, 30 with a computable 24h horizon), the market reached +5% within 24h in 23 of 30 (76.7) and drew down 10%+ in 14 of 30 (46.7). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.
Outcome distribution
6 OF 30 (20.0%) REACHED ≥ +5% WITHIN 1H
🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 30 = MATCHES WITH A COMPLETE 1H HORIZON
About 1 a day, on 15 of 31 days: spread through the record rather than one event.
Forward 30-minute returns across 30 matches: close to an even split, which is what a coin flip looks like.
Versus baseline
Historically, when any eligible AKEUSDT minute in the window (baseline) held (39,301 occurrences in the scanned window, 37,762 with a computable 24h horizon), the market reached +5% within 24h in 28,182 of 37,762 (74.6) and drew down 10%+ in 15,578 of 37,762 (41.3). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.
The full record
The same setup counted over every recorded day on AKEUSDT (2026-05-15 to 2026-08-01), growing daily.
Historically, when Swept the lows and reclaimed (1h) on AKEUSDT over the full record held (85 occurrences in the scanned window, 85 with a computable 24h horizon), the market reached +5% within 24h in 50 of 85 (58.8) and drew down 10%+ in 19 of 85 (22.4). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.
7 OF 85 (8.2%) REACHED ≥ +5% WITHIN 1H
🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 85 = MATCHES WITH A COMPLETE 1H HORIZON
About 1.1 a day, on 42 of 79 days: spread through the record rather than one event.
Forward 30-minute returns across 83 matches: close to an even split, which is what a coin flip looks like.
- grammar
- research_query.v2
- normalization
- archive_normalization.v1
- feature library
- feature_defs.v1
- dataset revision
- ce3b6253b51706f7a4c0e4a553e0dd67fcf76395dd1a8717eccda70dad520d60
- query hash
- dc3e68da0c8139d6a527e38e0c076b567555508c3a469dbc920a77928653f07f
- scanned window
- 2026-07-02T00:00:00.000Z to 2026-08-01T00:00:00.000Z (UTC)
Same key, same bytes. This receipt reruns; it does not retell. When the record grows, the dataset revision changes and says so.
This is the exact research_query.v2 definition behind the receipt. Send it to the key-authed research API (or the MCP research tool) and diff 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"
],
[
"identity.symbol",
"eq",
"akeusdt"
],
[
"times.anchor_time",
"between",
[
"2026-07-02T00:00:00.000Z",
"2026-08-01T00:00:00.000Z"
]
]
]
},
"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"],["identity.symbol","eq","akeusdt"],["times.anchor_time","between",["2026-07-02T00:00:00.000Z","2026-08-01T00:00:00.000Z"]]]},"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.
Everything measured on AKEUSDT right now: the AKEUSDT research page