FLOCKUSDT · historical base rate

Swept the lows and reclaimed (1h) on FLOCKUSDT

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 FLOCKUSDT when it held

Historically, when Swept the lows and reclaimed (1h) on FLOCKUSDT held (35 occurrences in the scanned window, 34 with a computable 24h horizon), the market reached +5% within 24h in 20 of 34 (58.8) and drew down 10%+ in 5 of 34 (14.7). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

Outcome distribution

WHAT FOLLOWED · ALL 35 MATCHES

31 of 35 (88.6%) 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?

WINDOWMOVE SIZE

🔒 Measured after every match, never by keeping winners. 35 of the matches have a complete 1 hour forward.

What are MFE and MAE?

Why 7 days can show fewer than 1 hour: a match too recent for a complete 7 days 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.

When they happened - one bar per UTC day, all 35 matches

About 1.1 a day, on 18 of 31 days: spread through the record rather than one event.

Where the next 30 minutes landed - 35 measured, 0 too recent

Forward 30-minute returns across 35 matches: 57% of them finished down.

How to read a distribution

Upside reached · 24hThe most price moved up within 24h of each occurrence: a high-water mark, never a close. 34 with a complete 24h.

Drawdown · 24hThe worst price moved against within 24h of each occurrence: the deepest point, never the close. 34 with a complete 24h.

Versus baseline

Historically, when any eligible FLOCKUSDT minute in the window (baseline) held (40,501 occurrences in the scanned window, 38,710 with a computable 24h horizon), the market reached +5% within 24h in 23,483 of 38,710 (60.7) and drew down 10%+ in 6,121 of 38,710 (15.8). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

The full record

The same setup counted over every recorded day on FLOCKUSDT (2026-08-14 to 2026-09-13), growing daily.

Historically, when Swept the lows and reclaimed (1h) on FLOCKUSDT over the full record held (35 occurrences in the scanned window, 34 with a computable 24h horizon), the market reached +5% within 24h in 20 of 34 (58.8) and drew down 10%+ in 5 of 34 (14.7). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

WHAT FOLLOWED · ALL 35 MATCHES

31 of 35 (88.6%) 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?

WINDOWMOVE SIZE

🔒 Measured after every match, never by keeping winners. 35 of the matches have a complete 1 hour forward.

What are MFE and MAE?

When they happened - one bar per UTC day, all 35 matches

About 1.1 a day, on 18 of 31 days: spread through the record rather than one event.

Where the next 30 minutes landed - 35 measured, 0 too recent

Forward 30-minute returns across 35 matches: 57% of them finished down.

How to read a distribution

Check our work: the key that re-runs this exact count (q#87a4261d)

grammar: research_query.v2
normalization: archive_normalization.v1
feature library: feature_defs.v1
dataset revision: 0848795c73770f58efd1b92d65553dd83603bcf23b7d9a5ff6b63224cb3eae10
query hash: 87a4261dc9253cc422275e92230748861093019eb1529c97aabc2e8ac407bbac
scanned window: 2026-08-14T00:00:00.000Z to 2026-09-13T00:00:00.000Z (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"
      ],
      [
        "identity.symbol",
        "eq",
        "flockusdt"
      ],
      [
        "times.anchor_time",
        "between",
        [
          "2026-08-14T00:00:00.000Z",
          "2026-09-13T00:00:00.000Z"
        ]
      ]
    ]
  },
  "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","flockusdt"],["times.anchor_time","between",["2026-08-14T00:00:00.000Z","2026-09-13T00:00:00.000Z"]]]},"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 FLOCKUSDT right now: the FLOCKUSDT research page