< One-sided tape: buyers1000BONKUSDT · historical base rate

One-sided tape: buyers on 1000BONKUSDT

Taker buy ratio over the last 15 minutes has run at 0.62 or more: a persistently buyer-heavy tape.

What has happened on 1000BONKUSDT when it held

Historically, when One-sided tape: buyers on 1000BONKUSDT held (383 occurrences in the scanned window, 367 with a computable 24h horizon), the market reached +5% within 24h in 95 of 367 (25.9) and drew down 10%+ in 29 of 367 (7.9). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

Outcome distribution

WHAT FOLLOWED - ALL 383 MATCHES, FROM THE PER-SCAN SUMMARY

2 OF 381 (0.5%) REACHED ≥ +5% WITHIN 1H

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

🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 381 = MATCHES WITH A COMPLETE 1H HORIZON (2 ABSENT: TOO CLOSE TO THE RECORD EDGE FOR 1H - NEVER TRUNCATED, NEVER AN IMPLIED ZERO)

OCCURRENCES PER DAY · UTC · SUM 383 - ALL 383, NOT THE PAGE

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

FWD_RET_30M DISTRIBUTION · 381 PRESENT · 2 ABSENT

Forward 30-minute returns across 381 matches: close to an even split, which is what a coin flip looks like.

Versus baseline

Historically, when any eligible 1000BONKUSDT minute in the window (baseline) held (36,376 occurrences in the scanned window, 35,207 with a computable 24h horizon), the market reached +5% within 24h in 9,039 of 35,207 (25.7) and drew down 10%+ in 3,314 of 35,207 (9.4). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

The full record

The same setup counted over every recorded day on 1000BONKUSDT (2026-05-15 to 2026-07-31), growing daily.

Historically, when One-sided tape: buyers on 1000BONKUSDT over the full record held (726 occurrences in the scanned window, 710 with a computable 24h horizon), the market reached +5% within 24h in 151 of 710 (21.3) and drew down 10%+ in 32 of 710 (4.5). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

WHAT FOLLOWED - ALL 726 MATCHES, FROM THE PER-SCAN SUMMARY

3 OF 724 (0.4%) REACHED ≥ +5% WITHIN 1H

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

🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 724 = MATCHES WITH A COMPLETE 1H HORIZON (2 ABSENT: TOO CLOSE TO THE RECORD EDGE FOR 1H - NEVER TRUNCATED, NEVER AN IMPLIED ZERO)

OCCURRENCES PER DAY · UTC · SUM 726 - ALL 726, NOT THE PAGE

About 9.3 a day, on 55 of 78 days: spread through the record rather than one event.

FWD_RET_30M DISTRIBUTION · 724 PRESENT · 2 ABSENT

Forward 30-minute returns across 724 matches: close to an even split, which is what a coin flip looks like.

Reproducibility key (q#ab9f3d07)

grammar: research_query.v2
normalization: archive_normalization.v1
feature library: feature_defs.v1
dataset revision: 52a43a418a97fbe3a324f7c372fa4d53967163acaa0ed33c56b78ddd897331a4
query hash: ab9f3d07b2982a1bd51eaa5cdb3d1e174e5ae2db4b2df96c55b2b139df73f229
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",
        "gte",
        0.62
      ],
      [
        "identity.symbol",
        "eq",
        "1000bonkusdt"
      ],
      [
        "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","gte",0.62],["identity.symbol","eq","1000bonkusdt"],["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 1000BONKUSDT right now: the 1000BONKUSDT research page