GWEIUSDT · recorded history

One-sided tape: sellers on GWEIUSDT

Taker buy ratio over the last 15 minutes has run at 0.38 or less: a persistently seller-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.
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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: 54.8% · 183 of 334 minutes
Other minutes: 55.5% · 19,606 of 35,304 minutes

Price touched −10% or lower

When this held: 38.6% · 129 of 334 minutes
Other minutes: 44.4% · 15,689 of 35,304 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 334 of 348 matches with a full 24 hours after them. The 14 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 11 a day, on 28 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 456 of 778 (58.6%); fell to −10% in 299 of 778 (38.4%), 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	348	346	334
Too recent	0	2	14
+1% or more	193 (55.5%)	272 (78.6%)	300 (89.8%)
+2% or more	108 (31.0%)	220 (63.6%)	269 (80.5%)
+5% or more	14 (4.0%)	77 (22.3%)	183 (54.8%)
+10% or more	0 (0.0%)	10 (2.9%)	87 (26.0%)
+15% or more	0 (0.0%)	5 (1.4%)	54 (16.2%)
+20% or more	0 (0.0%)	2 (0.6%)	36 (10.8%)
−1% or lower	225 (64.7%)	295 (85.3%)	308 (92.2%)
−2% or lower	105 (30.2%)	217 (62.7%)	270 (80.8%)
−5% or lower	9 (2.6%)	76 (22.0%)	207 (62.0%)
−10% or lower	0 (0.0%)	4 (1.2%)	129 (38.6%)
−15% or lower	0 (0.0%)	0 (0.0%)	56 (16.8%)
−20% or lower	0 (0.0%)	0 (0.0%)	10 (3.0%)

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	792	790	778
Too recent	0	2	14
+1% or more	425 (53.7%)	618 (78.2%)	706 (90.7%)
+2% or more	232 (29.3%)	477 (60.4%)	638 (82.0%)
+5% or more	33 (4.2%)	173 (21.9%)	456 (58.6%)
+10% or more	1 (0.1%)	36 (4.6%)	234 (30.1%)
+15% or more	1 (0.1%)	14 (1.8%)	169 (21.7%)
+20% or more	1 (0.1%)	6 (0.8%)	118 (15.2%)
−1% or lower	464 (58.6%)	644 (81.5%)	725 (93.2%)
−2% or lower	224 (28.3%)	457 (57.8%)	634 (81.5%)
−5% or lower	28 (3.5%)	165 (20.9%)	475 (61.1%)
−10% or lower	2 (0.3%)	21 (2.7%)	299 (38.4%)
−15% or lower	1 (0.1%)	7 (0.9%)	163 (21.0%)
−20% or lower	0 (0.0%)	3 (0.4%)	62 (8.0%)

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. 334 with a complete 24 hours.

Drawdown · 24hThe worst price moved against within 24 hours of each match: the deepest point, never the close. 334 with a complete 24 hours.

Price 30 minutes laterForward 30-minute returns across 348 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 Jul13 matches
16 Jul16 matches
17 Jul13 matches
18 Jul16 matches
19 Jul14 matches
20 Jul14 matches
21 Jul18 matches
22 Jul14 matches
23 Jul14 matches
24 Jul10 matches
25 Jul8 matches
26 Jul13 matches
27 Jul13 matches
28 Jul11 matches
29 Jul13 matches
30 Jul12 matches
31 Jul12 matches
1 Aug13 matches
2 Aug15 matches
3 Aug13 matches
4 Aug16 matches
5 Aug14 matches
6 Aug11 matches
7 Aug0 matches
8 Aug2 matches
9 Aug9 matches
10 Aug6 matches
11 Aug11 matches
12 Aug14 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#2fecf165)

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: 2fecf1653912c1d1e60a5c3de99956613b4aede963e1e52032af25314cdffc61
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",
        "lte",
        0.38
      ],
      [
        "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","lte",0.38],["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: sellers 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