GWEIUSDT · recorded history

One-sided tape: buyers on GWEIUSDT

Taker buy ratio over the last 15 minutes has run at 0.62 or more: a persistently buyer-heavy tape.

Read it in context

Read GWEIUSDT itself
Inspect GWEIUSDT now or at a past minute
Its recorded moves
GWEIUSDT market events and replays
Test it on GWEIUSDT, then plan it
A tested result leads to Plan a trade, which measures what trading it would have paid after costs.
Edit this test in Workbench

What happened in the next 24 hours?

Reaching +5% was about as common as without it; falling to −10% was less common than 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: 56.7% · 152 of 268 minutes
Other minutes: 55.4% · 20,602 of 37,181 minutes

Price touched −10% or lower

When this held: 32.5% · 87 of 268 minutes
Other minutes: 44.7% · 16,616 of 37,181 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 268 of 280 matches with a full 24 hours after them. The 12 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 9 a day, on 27 of 31 days: spread through the record rather than one event.

Over the full record

Every recorded day on GWEIUSDT, 2026-05-15 to 2026-08-14: reached +5% in 405 of 646 (62.7%); fell to −10% in 210 of 646 (32.5%), 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	280	280	268
Too recent	0	0	12
+1% or more	172 (61.4%)	230 (82.1%)	244 (91.0%)
+2% or more	93 (33.2%)	173 (61.8%)	217 (81.0%)
+5% or more	15 (5.4%)	65 (23.2%)	152 (56.7%)
+10% or more	0 (0.0%)	7 (2.5%)	70 (26.1%)
+15% or more	0 (0.0%)	2 (0.7%)	43 (16.0%)
+20% or more	0 (0.0%)	2 (0.7%)	31 (11.6%)
−1% or lower	161 (57.5%)	216 (77.1%)	241 (89.9%)
−2% or lower	73 (26.1%)	159 (56.8%)	213 (79.5%)
−5% or lower	4 (1.4%)	48 (17.1%)	157 (58.6%)
−10% or lower	1 (0.4%)	3 (1.1%)	87 (32.5%)
−15% or lower	0 (0.0%)	0 (0.0%)	46 (17.2%)
−20% or lower	0 (0.0%)	0 (0.0%)	10 (3.7%)

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	658	658	646
Too recent	2	2	14
+1% or more	379 (57.6%)	523 (79.5%)	594 (92.0%)
+2% or more	193 (29.3%)	377 (57.3%)	538 (83.3%)
+5% or more	36 (5.5%)	154 (23.4%)	405 (62.7%)
+10% or more	3 (0.5%)	40 (6.1%)	215 (33.3%)
+15% or more	1 (0.2%)	18 (2.7%)	159 (24.6%)
+20% or more	1 (0.2%)	9 (1.4%)	116 (18.0%)
−1% or lower	371 (56.4%)	517 (78.6%)	589 (91.2%)
−2% or lower	166 (25.2%)	366 (55.6%)	514 (79.6%)
−5% or lower	17 (2.6%)	122 (18.5%)	368 (57.0%)
−10% or lower	2 (0.3%)	18 (2.7%)	210 (32.5%)
−15% or lower	0 (0.0%)	4 (0.6%)	123 (19.0%)
−20% or lower	0 (0.0%)	3 (0.5%)	55 (8.5%)

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. 268 with a complete 24 hours.

Drawdown · 24hThe worst price moved against within 24 hours of each match: the deepest point, never the close. 268 with a complete 24 hours.

Price 30 minutes laterForward 30-minute returns across 280 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

15 Jul7 matches
16 Jul10 matches
17 Jul12 matches
18 Jul13 matches
19 Jul17 matches
20 Jul16 matches
21 Jul15 matches
22 Jul9 matches
23 Jul13 matches
24 Jul10 matches
25 Jul5 matches
26 Jul10 matches
27 Jul9 matches
28 Jul12 matches
29 Jul7 matches
30 Jul10 matches
31 Jul14 matches
1 Aug9 matches
2 Aug10 matches
3 Aug12 matches
4 Aug12 matches
5 Aug13 matches
6 Aug9 matches
7 Aug0 matches
8 Aug0 matches
9 Aug2 matches
10 Aug3 matches
11 Aug9 matches
12 Aug12 matches
13 Aug0 matches
14 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 GWEIUSDT, 2026-07-15 00:00 to 2026-08-14 00:00 UTC.

What are MFE and MAE?

Reproducibility key (q#261ccea3)

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: 3f9230e34c0a14e16a7bb3035842c9f073de8c4cb679de6f70e64bbb2153d03a
query hash: 261ccea302edb30f11f4c07fd66dc7f1e3ac2e197c01d4a9ae3a018677fa748a
scanned window: 2026-07-15T00:00:00.000Z to 2026-08-14T00:00:00.000Z (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.taker_buy_ratio_15m",
        "gte",
        0.62
      ],
      [
        "identity.symbol",
        "eq",
        "gweiusdt"
      ],
      [
        "times.anchor_time",
        "between",
        [
          "2026-07-15T00:00:00.000Z",
          "2026-08-14T00:00:00.000Z"
        ]
      ]
    ]
  },
  "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","gte",0.62],["identity.symbol","eq","gweiusdt"],["times.anchor_time","between",["2026-07-15T00:00:00.000Z","2026-08-14T00:00:00.000Z"]]]},"sort":["times.anchor_time","desc"],"page":{"limit":50,"cursor":null}}'

One-sided tape: buyers on GWEIUSDT

Read it in context

Read GWEIUSDT itself

Its recorded moves

Test it on GWEIUSDT, then plan it

What happened in the next 24 hours?

Price touched +5% or higher

Price touched −10% or lower

Over the full record