GIGGLEUSDT · recorded history

Swept the lows and reclaimed (1h) on GIGGLEUSDT

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

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Its recorded moves
GIGGLEUSDT 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?

This condition showed no clear difference for either move.

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: 38.7% · 12 of 31 minutes
Other minutes: 34.5% · 13,136 of 38,025 minutes

Price touched −10% or lower

When this held: 12.9% · 4 of 31 minutes
Other minutes: 9.9% · 3,759 of 38,025 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

Rates use the 31 of 34 matches with a full 24 hours after them. The 3 newer ones are left out, not counted as zero.

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 1.1 a day, on 19 of 31 days: spread through the record rather than one event.

Over the full record

Every recorded day on GIGGLEUSDT, 2026-05-15 to 2026-08-08: reached +5% in 23 of 73 (31.5%); fell to −10% in 4 of 73 (5.5%), within 24 hours.

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	33	33	31
Too recent	1	1	3
+1% or more	14 (42.4%)	22 (66.7%)	26 (83.9%)
+2% or more	6 (18.2%)	13 (39.4%)	23 (74.2%)
+5% or more	0 (0.0%)	4 (12.1%)	12 (38.7%)
+10% or more	0 (0.0%)	0 (0.0%)	5 (16.1%)
+15% or more	0 (0.0%)	0 (0.0%)	2 (6.5%)
+20% or more	0 (0.0%)	0 (0.0%)	1 (3.2%)
−1% or lower	10 (30.3%)	18 (54.5%)	25 (80.6%)
−2% or lower	6 (18.2%)	10 (30.3%)	23 (74.2%)
−5% or lower	1 (3.0%)	3 (9.1%)	7 (22.6%)
−10% or lower	0 (0.0%)	1 (3.0%)	4 (12.9%)
−15% or lower	0 (0.0%)	0 (0.0%)	2 (6.5%)

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

Full record: 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	75	75	73
Too recent	1	1	3
+1% or more	26 (34.7%)	52 (69.3%)	64 (87.7%)
+2% or more	10 (13.3%)	25 (33.3%)	49 (67.1%)
+5% or more	0 (0.0%)	5 (6.7%)	23 (31.5%)
+10% or more	0 (0.0%)	0 (0.0%)	7 (9.6%)
+15% or more	0 (0.0%)	0 (0.0%)	3 (4.1%)
+20% or more	0 (0.0%)	0 (0.0%)	1 (1.4%)
−1% or lower	19 (25.3%)	36 (48.0%)	57 (78.1%)
−2% or lower	7 (9.3%)	18 (24.0%)	48 (65.8%)
−5% or lower	1 (1.3%)	3 (4.0%)	13 (17.8%)
−10% or lower	0 (0.0%)	1 (1.3%)	4 (5.5%)
−15% or lower	0 (0.0%)	0 (0.0%)	2 (2.7%)

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. 31 with a complete 24 hours.

Drawdown · 24hThe worst price moved against within 24 hours of each match: the deepest point, never the close. 31 with a complete 24 hours.

Price 30 minutes laterForward 30-minute returns across 33 matches: close to an even split, which is what a coin flip looks like. 1 too recent.

How to read a distribution

Matches per UTC day

9 Jul0 matches
10 Jul1 match
11 Jul1 match
12 Jul2 matches
13 Jul1 match
14 Jul0 matches
15 Jul2 matches
16 Jul1 match
17 Jul1 match
18 Jul0 matches
19 Jul2 matches
20 Jul0 matches
21 Jul0 matches
22 Jul1 match
23 Jul2 matches
24 Jul0 matches
25 Jul2 matches
26 Jul0 matches
27 Jul1 match
28 Jul2 matches
29 Jul4 matches
30 Jul0 matches
31 Jul0 matches
1 Aug2 matches
2 Aug0 matches
3 Aug3 matches
4 Aug3 matches
5 Aug1 match
6 Aug2 matches
7 Aug0 matches
8 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 GIGGLEUSDT, 2026-07-09 00:00 to 2026-08-08 00:00 UTC.

What are MFE and MAE?

Reproducibility key (q#b90710d8)

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: 28acee8d0f123e535c8ba6325acd308c76bd0d511704f22e105e4b7842b6cb92
query hash: b90710d8aadeadc822265758448bcec11f31df48669252861d49bd9ca08b8a2c
scanned window: 2026-07-09T00:00:00.000Z to 2026-08-08T00:00:00.000Z (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",
        "giggleusdt"
      ],
      [
        "times.anchor_time",
        "between",
        [
          "2026-07-09T00:00:00.000Z",
          "2026-08-08T00:00:00.000Z"
        ]
      ]
    ]
  },
  "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","giggleusdt"],["times.anchor_time","between",["2026-07-09T00:00:00.000Z","2026-08-08T00:00:00.000Z"]]]},"sort":["times.anchor_time","desc"],"page":{"limit":50,"cursor":null}}'

Swept the lows and reclaimed (1h) on GIGGLEUSDT

Read it in context

Read GIGGLEUSDT itself

Its recorded moves

Test it on GIGGLEUSDT, then plan it

What happened in the next 24 hours?

Price touched +5% or higher

Price touched −10% or lower

Over the full record