< All conditionsLive condition · historical base rate

Order book heavily ask-sided

The order book has averaged at least half of its depth on the ask side over the sampling window.

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 Order book heavily ask-sided held (418,788 occurrences in the scanned window, 383,760 with a computable 24h horizon), the market reached +5% within 24h in 88,688 of 383,760 (23.1) and drew down 10%+ in 21,270 of 383,760 (5.5). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

Outcome distribution

WHAT FOLLOWED - ALL 418,788 MATCHES, FROM THE PER-SCAN SUMMARY

4,791 OF 397,667 (1.2%) REACHED ≥ +5% WITHIN 1H

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

🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 397,667 = MATCHES WITH A COMPLETE 1H HORIZON (21,121 ABSENT: TOO CLOSE TO THE RECORD EDGE FOR 1H - NEVER TRUNCATED, NEVER AN IMPLIED ZERO)

OCCURRENCES PER DAY · UTC · SUM 418788 - ALL 418,788, NOT THE PAGE

About 13,509 a day, on 30 of 31 days: spread through the record rather than one event.

FWD_RET_30M DISTRIBUTION · 377,896 PRESENT · 40,892 ABSENT

Forward 30-minute returns across 377,896 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 (20,559,339 occurrences in the scanned window, 18,231,915 with a computable 24h horizon), the market reached +5% within 24h in 4,217,185 of 18,231,915 (23.1) and drew down 10%+ in 992,191 of 18,231,915 (5.4). 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:

Reproducibility key (q#0a0bc471)

grammar: research_query.v2
normalization: archive_normalization.v1
feature library: feature_defs.v1
dataset revision: 52a43a418a97fbe3a324f7c372fa4d53967163acaa0ed33c56b78ddd897331a4
query hash: 0a0bc4716daa8c73463e2d3c8256c4d4f8cdca11f04e1d969836adbb9cf8e764
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.book_imbalance",
        "lte",
        -0.5
      ],
      [
        "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.book_imbalance","lte",-0.5],["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.