UNIUSDT · historical base rate

Swept the lows and reclaimed (1h) on UNIUSDT

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 UNIUSDT when it held

Historically, when Swept the lows and reclaimed (1h) on UNIUSDT held (35 occurrences in the scanned window, 35 with a computable 24h horizon), the market reached +5% within 24h in 9 of 35 (25.7) and drew down 10%+ in 0 of 35 (0.0). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

Outcome distribution

WHAT FOLLOWED - ALL 35 MATCHES, FROM THE PER-SCAN SUMMARY

0 OF 35 (0.0%) REACHED ≥ +5% WITHIN 1H

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

🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 35 = MATCHES WITH A COMPLETE 1H HORIZON

OCCURRENCES PER DAY · UTC · SUM 35 - ALL 35, NOT THE PAGE

About 1.1 a day, on 21 of 31 days: spread through the record rather than one event.

FWD_RET_30M DISTRIBUTION · 35 PRESENT · 0 ABSENT

Forward 30-minute returns across 35 matches: close to an even split, which is what a coin flip looks like.

Upside reached · 24hThe most price moved up within 24h of each occurrence: a high-water mark, never a close. 35 with a complete 24h.

Drawdown · 24hThe worst price moved against within 24h of each occurrence: the deepest point, never the close. 35 with a complete 24h.

Versus baseline

Historically, when any eligible UNIUSDT minute in the window (baseline) held (39,121 occurrences in the scanned window, 37,628 with a computable 24h horizon), the market reached +5% within 24h in 11,121 of 37,628 (29.6) and drew down 10%+ in 0 of 37,628 (0.0). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

The full record

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

Historically, when Swept the lows and reclaimed (1h) on UNIUSDT over the full record held (73 occurrences in the scanned window, 73 with a computable 24h horizon), the market reached +5% within 24h in 15 of 73 (20.5) and drew down 10%+ in 0 of 73 (0.0). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

WHAT FOLLOWED - ALL 73 MATCHES, FROM THE PER-SCAN SUMMARY

0 OF 73 (0.0%) REACHED ≥ +5% WITHIN 1H

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

🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 73 = MATCHES WITH A COMPLETE 1H HORIZON

OCCURRENCES PER DAY · UTC · SUM 73 - ALL 73, NOT THE PAGE

About 0.9 a day, on 41 of 79 days: spread through the record rather than one event.

FWD_RET_30M DISTRIBUTION · 73 PRESENT · 0 ABSENT

Forward 30-minute returns across 73 matches: close to an even split, which is what a coin flip looks like.

Reproducibility key (q#c399ebbd)

grammar: research_query.v2
normalization: archive_normalization.v1
feature library: feature_defs.v1
dataset revision: ce3b6253b51706f7a4c0e4a553e0dd67fcf76395dd1a8717eccda70dad520d60
query hash: c399ebbdd2b4a677170b76ce28c0b6bb133d8875db400470fecd8ff5d9b50010
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",
        "uniusdt"
      ],
      [
        "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","uniusdt"],["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 UNIUSDT right now: the UNIUSDT research page