< One-sided tape: sellersWLDUSDT · historical base rate

One-sided tape: sellers on WLDUSDT

Taker buy ratio over the last 15 minutes has run at 0.38 or less: a persistently seller-heavy tape.

What has happened on WLDUSDT when it held

Historically, when One-sided tape: sellers on WLDUSDT held (366 occurrences in the scanned window, 353 with a computable 24h horizon), the market reached +5% within 24h in 91 of 353 (25.8) and drew down 10%+ in 16 of 353 (4.5). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

Outcome distribution

WHAT FOLLOWED - ALL 366 MATCHES, FROM THE PER-SCAN SUMMARY

0 OF 365 (0.0%) REACHED ≥ +5% WITHIN 1H

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

🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 365 = 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 366 - ALL 366, NOT THE PAGE

About 12 a day, on 29 of 31 days: spread through the record rather than one event.

FWD_RET_30M DISTRIBUTION · 365 PRESENT · 1 ABSENT

Forward 30-minute returns across 365 matches: close to an even split, which is what a coin flip looks like.

Versus baseline

Historically, when any eligible WLDUSDT minute in the window (baseline) held (36,490 occurrences in the scanned window, 35,239 with a computable 24h horizon), the market reached +5% within 24h in 9,481 of 35,239 (26.9) and drew down 10%+ in 1,545 of 35,239 (4.4). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

The full record

The same setup counted over every recorded day on WLDUSDT (2026-05-15 to 2026-07-31), growing daily.

Historically, when One-sided tape: sellers on WLDUSDT over the full record held (750 occurrences in the scanned window, 737 with a computable 24h horizon), the market reached +5% within 24h in 266 of 737 (36.1) and drew down 10%+ in 62 of 737 (8.4). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

WHAT FOLLOWED - ALL 750 MATCHES, FROM THE PER-SCAN SUMMARY

10 OF 749 (1.3%) REACHED ≥ +5% WITHIN 1H

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

🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 749 = 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 750 - ALL 750, NOT THE PAGE

About 9.6 a day, on 76 of 78 days: spread through the record rather than one event.

FWD_RET_30M DISTRIBUTION · 749 PRESENT · 1 ABSENT

Forward 30-minute returns across 749 matches: close to an even split, which is what a coin flip looks like.

Reproducibility key (q#ff15d20a)

grammar: research_query.v2
normalization: archive_normalization.v1
feature library: feature_defs.v1
dataset revision: 52a43a418a97fbe3a324f7c372fa4d53967163acaa0ed33c56b78ddd897331a4
query hash: ff15d20a3e083885bf57b10e695c3ff8a2c222efd6fab2a05d9c26689a5624c8
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.taker_buy_ratio_15m",
        "lte",
        0.38
      ],
      [
        "identity.symbol",
        "eq",
        "wldusdt"
      ],
      [
        "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.taker_buy_ratio_15m","lte",0.38],["identity.symbol","eq","wldusdt"],["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.

Everything measured on WLDUSDT right now: the WLDUSDT research page