ONUSDT · historical base rate

Swept the lows and reclaimed (1h) on ONUSDT

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 ONUSDT when it held

Historically, when Swept the lows and reclaimed (1h) on ONUSDT held (30 occurrences in the scanned window, 27 with a computable 24h horizon), the market reached +5% within 24h in 15 of 27 (55.6) and drew down 10%+ in 2 of 27 (7.4). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

Outcome distribution

WHAT FOLLOWED - ALL 30 MATCHES, FROM THE PER-SCAN SUMMARY

5 OF 30 (16.7%) REACHED ≥ +5% WITHIN 1H

METRIC MFE_1H · CHIPS RE-READ THE SUMMARY, NEVER RE-QUERY

🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 30 = MATCHES WITH A COMPLETE 1H HORIZON

OCCURRENCES PER DAY · UTC · SUM 30 - ALL 30, NOT THE PAGE

About 1 a day, on 17 of 31 days: spread through the record rather than one event.

FWD_RET_30M DISTRIBUTION · 30 PRESENT · 0 ABSENT

Forward 30-minute returns across 30 matches: 63% of them finished up.

Upside reached · 24hThe most price moved up within 24h of each occurrence: a high-water mark, never a close. 27 with a complete 24h.

Drawdown · 24hThe worst price moved against within 24h of each occurrence: the deepest point, never the close. 27 with a complete 24h.

Versus baseline

Historically, when any eligible ONUSDT minute in the window (baseline) held (39,721 occurrences in the scanned window, 37,906 with a computable 24h horizon), the market reached +5% within 24h in 25,173 of 37,906 (66.4) and drew down 10%+ in 9,463 of 37,906 (25.0). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

The full record

The same setup counted over every recorded day on ONUSDT (2026-05-15 to 2026-08-01), growing daily.

Historically, when Swept the lows and reclaimed (1h) on ONUSDT over the full record held (57 occurrences in the scanned window, 53 with a computable 24h horizon), the market reached +5% within 24h in 25 of 53 (47.2) and drew down 10%+ in 5 of 53 (9.4). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

WHAT FOLLOWED - ALL 57 MATCHES, FROM THE PER-SCAN SUMMARY

5 OF 56 (8.9%) REACHED ≥ +5% WITHIN 1H

METRIC MFE_1H · CHIPS RE-READ THE SUMMARY, NEVER RE-QUERY

🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 56 = MATCHES WITH A COMPLETE 1H HORIZON (1 ABSENT: TOO CLOSE TO THE RECORD EDGE FOR 1H - NEVER TRUNCATED, NEVER AN IMPLIED ZERO)

OCCURRENCES PER DAY · UTC · SUM 57 - ALL 57, NOT THE PAGE

About 0.7 a day, on 35 of 79 days: spread through the record rather than one event.

FWD_RET_30M DISTRIBUTION · 55 PRESENT · 2 ABSENT

Forward 30-minute returns across 55 matches: 71% of them finished up.

Reproducibility key (q#03f5f672)

grammar: research_query.v2
normalization: archive_normalization.v1
feature library: feature_defs.v1
dataset revision: ce3b6253b51706f7a4c0e4a553e0dd67fcf76395dd1a8717eccda70dad520d60
query hash: 03f5f6721c643b35a1041099f35780c17d1e5b7901e7b39da0eed2c73030d4a4
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.

Re-run this over the API or MCP

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",
        "onusdt"
      ],
      [
        "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","onusdt"],["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 ONUSDT right now: the ONUSDT research page