DEXEUSDT · historical base rate

One-sided tape: sellers on DEXEUSDT

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

What has happened on DEXEUSDT when it held

Historically, when One-sided tape: sellers on DEXEUSDT held (113 occurrences in the scanned window, 109 with a computable 24h horizon), the market reached +5% within 24h in 70 of 109 (64.2) and drew down 10%+ in 18 of 109 (16.5). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

Outcome distribution

WHAT FOLLOWED - ALL 113 MATCHES, FROM THE PER-SCAN SUMMARY

5 OF 113 (4.4%) REACHED ≥ +5% WITHIN 1H

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

🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 113 = MATCHES WITH A COMPLETE 1H HORIZON

OCCURRENCES PER DAY · UTC · SUM 113 - ALL 113, NOT THE PAGE

About 3.6 a day, on 22 of 31 days: spread through the record rather than one event.

FWD_RET_30M DISTRIBUTION · 113 PRESENT · 0 ABSENT

Forward 30-minute returns across 113 matches: close to an even split, which is what a coin flip looks like.

Upside reached · 24hThe most price moved up within 24h of each occurrence: a high-water mark, never a close. 109 with a complete 24h.

Drawdown · 24hThe worst price moved against within 24h of each occurrence: the deepest point, never the close. 109 with a complete 24h.

Versus baseline

Historically, when any eligible DEXEUSDT minute in the window (baseline) held (40,681 occurrences in the scanned window, 39,258 with a computable 24h horizon), the market reached +5% within 24h in 25,033 of 39,258 (63.8) and drew down 10%+ in 17,657 of 39,258 (45.0). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

The full record

The same setup counted over every recorded day on DEXEUSDT (2026-05-15 to 2026-08-01), growing daily.

Historically, when One-sided tape: sellers on DEXEUSDT over the full record held (367 occurrences in the scanned window, 363 with a computable 24h horizon), the market reached +5% within 24h in 182 of 363 (50.1) and drew down 10%+ in 77 of 363 (21.2). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

WHAT FOLLOWED - ALL 367 MATCHES, FROM THE PER-SCAN SUMMARY

12 OF 367 (3.3%) REACHED ≥ +5% WITHIN 1H

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

🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 367 = MATCHES WITH A COMPLETE 1H HORIZON

OCCURRENCES PER DAY · UTC · SUM 367 - ALL 367, NOT THE PAGE

About 4.6 a day, on 48 of 79 days: spread through the record rather than one event.

FWD_RET_30M DISTRIBUTION · 365 PRESENT · 2 ABSENT

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

Reproducibility key (q#a66a0e60)

grammar: research_query.v2
normalization: archive_normalization.v1
feature library: feature_defs.v1
dataset revision: ce3b6253b51706f7a4c0e4a553e0dd67fcf76395dd1a8717eccda70dad520d60
query hash: a66a0e60de3d143a6d633be686ebeb802167078172b3da59133dbacb569382bf
scanned window: 2026-07-02T00:00:00.000Z to 2026-08-01T00:00:00.000Z (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",
        "dexeusdt"
      ],
      [
        "times.anchor_time",
        "between",
        [
          "2026-07-02T00:00:00.000Z",
          "2026-08-01T00:00:00.000Z"
        ]
      ]
    ]
  },
  "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","dexeusdt"],["times.anchor_time","between",["2026-07-02T00:00:00.000Z","2026-08-01T00:00:00.000Z"]]]},"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 DEXEUSDT right now: the DEXEUSDT research page