UAIUSDT · historical base rate

Swept the lows and reclaimed (1h) on UAIUSDT

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 UAIUSDT when it held

Historically, when Swept the lows and reclaimed (1h) on UAIUSDT held (36 occurrences in the scanned window, 36 with a computable 24h horizon), the market reached +5% within 24h in 19 of 36 (52.8) and drew down 10%+ in 6 of 36 (16.7). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

Outcome distribution

WHAT FOLLOWED · ALL 36 MATCHES

2 of 36 (5.6%) 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. 36 of the matches have a complete 1 hour forward.

What are MFE and MAE?

When they happened - one bar per UTC day, all 36 matches

About 1.2 a day, on 22 of 31 days: spread through the record rather than one event.

Where the next 30 minutes landed - 36 measured, 0 too recent

Forward 30-minute returns across 36 matches: 56% 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. 36 with a complete 24h.

Drawdown · 24hThe worst price moved against within 24h of each occurrence: the deepest point, never the close. 36 with a complete 24h.

Versus baseline

Historically, when any eligible UAIUSDT minute in the window (baseline) held (39,421 occurrences in the scanned window, 37,871 with a computable 24h horizon), the market reached +5% within 24h in 18,239 of 37,871 (48.2) and drew down 10%+ in 7,769 of 37,871 (20.5). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

The full record

The same setup counted over every recorded day on UAIUSDT (2026-05-15 to 2026-08-03), growing daily.

Historically, when Swept the lows and reclaimed (1h) on UAIUSDT over the full record held (69 occurrences in the scanned window, 69 with a computable 24h horizon), the market reached +5% within 24h in 36 of 69 (52.2) and drew down 10%+ in 10 of 69 (14.5). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

WHAT FOLLOWED · ALL 69 MATCHES

4 of 69 (5.8%) 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. 69 of the matches have a complete 1 hour forward.

What are MFE and MAE?

When they happened - one bar per UTC day, all 69 matches

About 0.9 a day, on 43 of 81 days: spread through the record rather than one event.

Where the next 30 minutes landed - 68 measured, 1 too recent

Forward 30-minute returns across 68 matches: 60% of them finished up.

How to read a distribution

Check our work: the key that re-runs this exact count (q#8e85b7c2)

grammar: research_query.v2
normalization: archive_normalization.v1
feature library: feature_defs.v1
dataset revision: a52c6390738e56734585b736b0a1c739bca72cac3f87cca21db6d03ebdd35d64
query hash: 8e85b7c2719d966542ca3fec5989c065439e2111127d262b5bbe750d3ac51768
scanned window: 2026-07-04T00:00:00.000Z to 2026-08-03T00:00:00.000Z (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",
        "uaiusdt"
      ],
      [
        "times.anchor_time",
        "between",
        [
          "2026-07-04T00:00:00.000Z",
          "2026-08-03T00:00:00.000Z"
        ]
      ]
    ]
  },
  "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","uaiusdt"],["times.anchor_time","between",["2026-07-04T00:00:00.000Z","2026-08-03T00:00:00.000Z"]]]},"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 UAIUSDT right now: the UAIUSDT research page