ZAMAUSDT · historical base rate

Swept the lows and reclaimed (1h) on ZAMAUSDT

The last completed one-hour candle swept prior lows and closed back above them: the "bullish" sweep and reclaim formation on the hourly.

What has happened on ZAMAUSDT when it held

Historically, when Swept the lows and reclaimed (1h) on ZAMAUSDT held (30 occurrences in the scanned window, 28 with a computable 24h horizon), the market reached +5% within 24h in 10 of 28 (35.7) and drew down 10%+ in 2 of 28 (7.1). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

Outcome distribution

WHAT FOLLOWED · ALL 30 MATCHES

13 of 29 (44.8%) reached +1% or more within 1 hour · smallest move size with matches, picked for you

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

WINDOWMOVE SIZE

🔒 Measured after every match, never by keeping winners. 29 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 30 matches

About 1 a day, on 17 of 31 days: spread through the record rather than one event.

Where the next 30 minutes landed - 28 measured, 2 too recent

Forward 30-minute returns across 28 matches: 68% 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. 28 with a complete 24h.

Drawdown · 24hThe worst price moved against within 24h of each occurrence: the deepest point, never the close. 28 with a complete 24h.

Versus baseline

Historically, when any eligible ZAMAUSDT minute in the window (baseline) held (39,721 occurrences in the scanned window, 37,885 with a computable 24h horizon), the market reached +5% within 24h in 16,947 of 37,885 (44.7) and drew down 10%+ in 2,376 of 37,885 (6.3). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

The full record

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

Historically, when Swept the lows and reclaimed (1h) on ZAMAUSDT over the full record held (59 occurrences in the scanned window, 56 with a computable 24h horizon), the market reached +5% within 24h in 21 of 56 (37.5) and drew down 10%+ in 2 of 56 (3.6). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

WHAT FOLLOWED · ALL 59 MATCHES

21 of 57 (36.8%) reached +1% or more within 1 hour · smallest move size with matches, picked for you

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

WINDOWMOVE SIZE

🔒 Measured after every match, never by keeping winners. 57 of the matches have a complete 1 hour forward; the other 2 are too recent to know.

What are MFE and MAE?

When they happened - one bar per UTC day, all 59 matches

About 0.7 a day, on 34 of 79 days: spread through the record rather than one event.

Where the next 30 minutes landed - 56 measured, 3 too recent

Forward 30-minute returns across 56 matches: 63% of them finished up.

How to read a distribution

Check our work: the key that re-runs this exact count (q#e20e05ae)

grammar: research_query.v2
normalization: archive_normalization.v1
feature library: feature_defs.v1
dataset revision: ce3b6253b51706f7a4c0e4a553e0dd67fcf76395dd1a8717eccda70dad520d60
query hash: e20e05aee296eab59b4a190da6915b48ab26bbdec8592cf10fa8a2d370542c49
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 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.candle_sweep_reclaim_1h",
        "eq",
        "bullish"
      ],
      [
        "identity.symbol",
        "eq",
        "zamausdt"
      ],
      [
        "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.candle_sweep_reclaim_1h","eq","bullish"],["identity.symbol","eq","zamausdt"],["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 ZAMAUSDT right now: the ZAMAUSDT research page