< All conditionsLive condition · historical base rate

Liquidations arriving in cascades

The cascade clustering index is above 0.6: liquidations are arriving in bursts rather than independently.

Firing now (provisional, current bucket)

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 Liquidations arriving in cascades held (604 occurrences in the scanned window, 587 with a computable 24h horizon), the market reached +5% within 24h in 280 of 587 (47.7) and drew down 10%+ in 212 of 587 (36.1). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

Outcome distribution

WHAT FOLLOWED - ALL 604 MATCHES, FROM THE PER-SCAN SUMMARY

124 OF 604 (20.5%) REACHED ≥ +5% WITHIN 1H

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

🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 604 = MATCHES WITH A COMPLETE 1H HORIZON

OCCURRENCES PER DAY · UTC · SUM 604 - ALL 604, NOT THE PAGE

About 19 a day, on 29 of 31 days: spread through the record rather than one event.

FWD_RET_30M DISTRIBUTION · 599 PRESENT · 5 ABSENT

Forward 30-minute returns across 599 matches: close to an even split, which is what a coin flip looks like.

Versus baseline

Historically, when any eligible minute in the window (baseline) held (20,407,210 occurrences in the scanned window, 18,096,944 with a computable 24h horizon), the market reached +5% within 24h in 4,001,868 of 18,096,944 (22.1) and drew down 10%+ in 836,192 of 18,096,944 (4.6). 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:

BTCUSDT ETHUSDT

Reproducibility key (q#5758c3cd)

grammar: research_query.v2
normalization: archive_normalization.v1
feature library: feature_defs.v1
dataset revision: 52a43a418a97fbe3a324f7c372fa4d53967163acaa0ed33c56b78ddd897331a4
query hash: 5758c3cdd0a37f817e75def0b7e433f7d2ba18c7784b24260f0ce4ba0ad1f86d
scanned window: 2026-07-01T00:00:00.000Z to 2026-07-31T00:00:00.000Z (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.cascade_clustering_index",
        "gte",
        0.6
      ],
      [
        "times.anchor_time",
        "between",
        [
          "2026-07-01T00:00:00.000Z",
          "2026-07-31T00:00:00.000Z"
        ]
      ]
    ]
  },
  "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.cascade_clustering_index","gte",0.6],["times.anchor_time","between",["2026-07-01T00:00:00.000Z","2026-07-31T00:00:00.000Z"]]]},"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.