BTWUSDT · historical base rate

One-sided tape: sellers on BTWUSDT

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

What has happened on BTWUSDT when it held

Historically, when One-sided tape: sellers on BTWUSDT held (354 occurrences in the scanned window, 345 with a computable 24h horizon), the market reached +5% within 24h in 209 of 345 (60.6) and drew down 10%+ in 40 of 345 (11.6). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

Outcome distribution

WHAT FOLLOWED · ALL 354 MATCHES

19 of 354 (5.4%) reached +5% or more within 1 hour

Pick a move size and a window: how often did a move at least that big follow?

🔒 Measured after every match, never by keeping winners. 354 of the matches have a complete 1 hour forward.

What are MFE and MAE?

When they happened - one bar per UTC day, all 354 matches

About 11 a day, on 29 of 31 days: spread through the record rather than one event.

Where the next 30 minutes landed - 354 measured, 0 too recent

Forward 30-minute returns across 354 matches: 57% of them finished up.

How to read a distribution

Upside reached · 24hThe most price moved up within 24h of each occurrence: a high-water mark, never a close. 345 with a complete 24h.

Drawdown · 24hThe worst price moved against within 24h of each occurrence: the deepest point, never the close. 345 with a complete 24h.

Versus baseline

Historically, when any eligible BTWUSDT minute in the window (baseline) held (36,720 occurrences in the scanned window, 35,345 with a computable 24h horizon), the market reached +5% within 24h in 22,506 of 35,345 (63.7) and drew down 10%+ in 6,792 of 35,345 (19.2). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

The full record

The same setup counted over every recorded day on BTWUSDT (2026-05-15 to 2026-08-02), growing daily.

Historically, when One-sided tape: sellers on BTWUSDT over the full record held (497 occurrences in the scanned window, 487 with a computable 24h horizon), the market reached +5% within 24h in 314 of 487 (64.5) and drew down 10%+ in 128 of 487 (26.3). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

WHAT FOLLOWED · ALL 497 MATCHES

41 of 496 (8.3%) reached +5% or more within 1 hour

Pick a move size and a window: how often did a move at least that big follow?

🔒 Measured after every match, never by keeping winners. 496 of the matches have a complete 1 hour forward; the other 1 are too recent to know.

What are MFE and MAE?

When they happened - one bar per UTC day, all 497 matches

About 6.2 a day, on 51 of 80 days: spread through the record rather than one event.

Where the next 30 minutes landed - 496 measured, 1 too recent

Forward 30-minute returns across 496 matches: close to an even split, which is what a coin flip looks like.

How to read a distribution

Check our work: the key that re-runs this exact count (q#6ee8f472)

grammar: research_query.v2
normalization: archive_normalization.v1
feature library: feature_defs.v1
dataset revision: 4873bd76720e8980808a8dade433845b262b5755e1d0e203e9811b57c83d8078
query hash: 6ee8f472aeffd3cbb7f6e43afa97b71cea73c910b63c9289a8718d17c8dc1cb6
scanned window: 2026-07-03T00:00:00.000Z to 2026-08-02T00:00:00.000Z (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 yourself, over the API or from an AI agent

This is the exact search definition behind the receipt. Send it to the key-authed research API (or the MCP research tool) and compare 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",
        "btwusdt"
      ],
      [
        "times.anchor_time",
        "between",
        [
          "2026-07-03T00:00:00.000Z",
          "2026-08-02T00:00:00.000Z"
        ]
      ]
    ]
  },
  "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","btwusdt"],["times.anchor_time","between",["2026-07-03T00:00:00.000Z","2026-08-02T00:00:00.000Z"]]]},"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 BTWUSDT right now: the BTWUSDT research page