< One-sided tape: sellersDOGEUSDT · historical base rate

One-sided tape: sellers on DOGEUSDT

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

What has happened on DOGEUSDT when it held

Historically, when One-sided tape: sellers on DOGEUSDT held (371 occurrences in the scanned window, 356 with a computable 24h horizon), the market reached +5% within 24h in 20 of 356 (5.6) and drew down 10%+ in 0 of 356 (0.0). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

Outcome distribution

WHAT FOLLOWED - ALL 371 MATCHES, FROM THE PER-SCAN SUMMARY

0 OF 370 (0.0%) REACHED ≥ +5% WITHIN 1H

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

🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 370 = 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 371 - ALL 371, NOT THE PAGE

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

FWD_RET_30M DISTRIBUTION · 370 PRESENT · 1 ABSENT

Forward 30-minute returns across 370 matches: close to an even split, which is what a coin flip looks like.

Versus baseline

Historically, when any eligible DOGEUSDT minute in the window (baseline) held (36,641 occurrences in the scanned window, 35,371 with a computable 24h horizon), the market reached +5% within 24h in 2,007 of 35,371 (5.7) and drew down 10%+ in 0 of 35,371 (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 DOGEUSDT (2026-05-15 to 2026-07-31), growing daily.

Historically, when One-sided tape: sellers on DOGEUSDT over the full record held (934 occurrences in the scanned window, 919 with a computable 24h horizon), the market reached +5% within 24h in 48 of 919 (5.2) and drew down 10%+ in 3 of 919 (0.3). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

WHAT FOLLOWED - ALL 934 MATCHES, FROM THE PER-SCAN SUMMARY

0 OF 933 (0.0%) REACHED ≥ +5% WITHIN 1H

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

🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 933 = 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 934 - ALL 934, NOT THE PAGE

About 12 a day, on 76 of 78 days: spread through the record rather than one event.

FWD_RET_30M DISTRIBUTION · 933 PRESENT · 1 ABSENT

Forward 30-minute returns across 933 matches: close to an even split, which is what a coin flip looks like.

Reproducibility key (q#cd9114f4)

grammar: research_query.v2
normalization: archive_normalization.v1
feature library: feature_defs.v1
dataset revision: 52a43a418a97fbe3a324f7c372fa4d53967163acaa0ed33c56b78ddd897331a4
query hash: cd9114f44b42d77f05b9081c55f6a70f882c8ace9d47a7460d9e0ad75480c67a
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",
        "dogeusdt"
      ],
      [
        "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","dogeusdt"],["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 DOGEUSDT right now: the DOGEUSDT research page