WLFIUSDT · recorded history

Swept the lows and reclaimed (1h) on WLFIUSDT

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

Read it in context

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Its recorded moves
WLFIUSDT market events and replays
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A tested result leads to Plan a trade, which measures what trading it would have paid after costs.
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What happened in the next 24 hours?

Reaching +5% was less common than without it; falling to −10% was about as common as without it.

Other minutes are the same markets and dates without this condition. Each percentage is the share of measured minutes that reached that move from the starting price.

Price touched +5% or higher

When this held: 2.7% · 1 of 37 minutes
Other minutes: 15.2% · 5,712 of 37,615 minutes

Price touched −10% or lower

When this held: 5.4% · 2 of 37 minutes
Other minutes: 7.2% · 2,701 of 37,615 minutes

Price can touch both levels within the same 24 hours.

This counts how often price touched a level, not what trading it would have paid.

Sample and counting

All 37 matches have a full 24 hours after them.

Every condition is measured over the same 24 hours, whatever the length of its own reading. Other windows and move sizes shows shorter and longer windows.

When it happened

About 1.2 a day, on 21 of 31 days: spread through the record rather than one event.

Other windows and move sizes

Matches that reached each move within each window. Counts first; the measured row is what each rate is over.
Move	1 hour	4 hours	24 hours
Measured	37	37	37
Too recent	0	0	0
+1% or more	3 (8.1%)	8 (21.6%)	25 (67.6%)
+2% or more	1 (2.7%)	1 (2.7%)	12 (32.4%)
+5% or more	0 (0.0%)	0 (0.0%)	1 (2.7%)
+10% or more	0 (0.0%)	0 (0.0%)	0 (0.0%)
−1% or lower	4 (10.8%)	10 (27.0%)	28 (75.7%)
−2% or lower	2 (5.4%)	2 (5.4%)	11 (29.7%)
−5% or lower	1 (2.7%)	1 (2.7%)	2 (5.4%)
−10% or lower	1 (2.7%)	1 (2.7%)	2 (5.4%)
−15% or lower	1 (2.7%)	1 (2.7%)	2 (5.4%)
−20% or lower	1 (2.7%)	1 (2.7%)	2 (5.4%)

Each window counts only matches old enough for it, so a longer window can show fewer.

Distributions and daily counts

Upside reached · 24hThe most price moved up within 24 hours of each match: a high-water mark, never a close. 37 with a complete 24 hours.

Drawdown · 24hThe worst price moved against within 24 hours of each match: the deepest point, never the close. 37 with a complete 24 hours.

Price 30 minutes laterForward 30-minute returns across 37 matches: close to an even split, which is what a coin flip looks like. 0 too recent.

How to read a distribution

Matches per UTC day

25 Jul3 matches
26 Jul1 match
27 Jul1 match
28 Jul0 matches
29 Jul3 matches
30 Jul2 matches
31 Jul2 matches
1 Aug1 match
2 Aug1 match
3 Aug3 matches
4 Aug2 matches
5 Aug1 match
6 Aug3 matches
7 Aug2 matches
8 Aug1 match
9 Aug0 matches
10 Aug0 matches
11 Aug2 matches
12 Aug1 match
13 Aug3 matches
14 Aug0 matches
15 Aug0 matches
16 Aug0 matches
17 Aug1 match
18 Aug2 matches
19 Aug1 match
20 Aug1 match
21 Aug0 matches
22 Aug0 matches
23 Aug0 matches
24 Aug0 matches

How this is counted

Each rate counts only matches with the full window after them.
A minute where a reading was missing is left out and reported, not read as zero.
The condition picks the setup, never the outcome: a definition that filters on what followed is rejected (OUTCOME_IN_PREDICATE). Every match is measured, winners and losers alike.
"Other minutes" is every other eligible minute in the same market and window. It is a reference, not a control group.
"Reached +5%" uses the highest price inside the window (maximum favourable excursion, MFE); "fell to −10%" uses the lowest (maximum adverse excursion, MAE). Neither is the close.
Checked 41,761 eligible market-minutes (eligible_symbol_buckets) on WLFIUSDT, 2026-07-25 00:00 to 2026-08-24 00:00 UTC.

What are MFE and MAE?

Reproducibility key (q#09b10362)

The key that re-runs this exact count. Same key, same bytes; when the record grows, the dataset revision changes.

grammar: research_query.v2
normalization: archive_normalization.v1
feature library: feature_defs.v1
dataset revision: c9e0579296efd94a7ed22f263b9b7549097c44019cff4da395a5cf6ac557aceb
query hash: 09b10362db5768b8460bcc4f7b2c75f5c4f37b1629d1beb9a91ec6dfc69a944d
scanned window: 2026-07-25T00:00:00.000Z to 2026-08-24T00:00:00.000Z (UTC)

Re-run over the API

The exact search definition behind this count. 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",
        "wlfiusdt"
      ],
      [
        "times.anchor_time",
        "between",
        [
          "2026-07-25T00:00:00.000Z",
          "2026-08-24T00:00:00.000Z"
        ]
      ]
    ]
  },
  "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","wlfiusdt"],["times.anchor_time","between",["2026-07-25T00:00:00.000Z","2026-08-24T00:00:00.000Z"]]]},"sort":["times.anchor_time","desc"],"page":{"limit":50,"cursor":null}}'

Swept the lows and reclaimed (1h) on WLFIUSDT

Read it in context

Read WLFIUSDT itself

Its recorded moves

Test it on WLFIUSDT, then plan it

What happened in the next 24 hours?

Price touched +5% or higher

Price touched −10% or lower