DASHUSDT · recorded history

One-sided tape: buyers on DASHUSDT

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

Read it in context

  1. Read DASHUSDT itself

  2. Its recorded moves

  3. Test it on DASHUSDT, then plan it

    A tested result leads to Plan a trade, which measures what trading it would have paid after costs.

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
43.2% · 118 of 273 minutes
Other minutes
46.5% · 18,118 of 38,950 minutes

Price touched −10% or lower

When this held
7.0% · 19 of 273 minutes
Other minutes
8.7% · 3,377 of 38,950 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 273 of 283 matches with a full 24 hours after them. The 10 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
Matches per UTC day, 2026-09-01 to 2026-10-01

About 9.1 a day, on 30 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.
Move1 hour4 hours24 hours72 hours7 days
Measured283281273252217
Too recent02103166
+0.1% or more250 (88.3%)262 (93.2%)263 (96.3%)249 (98.8%)216 (99.5%)
+0.2% or more227 (80.2%)253 (90.0%)258 (94.5%)248 (98.4%)216 (99.5%)
+0.5% or more172 (60.8%)225 (80.1%)245 (89.7%)241 (95.6%)215 (99.1%)
+1% or more100 (35.3%)178 (63.3%)227 (83.2%)236 (93.7%)213 (98.2%)
+2% or more32 (11.3%)111 (39.5%)196 (71.8%)214 (84.9%)206 (94.9%)
+5% or more4 (1.4%)29 (10.3%)118 (43.2%)176 (69.8%)193 (88.9%)
+10% or more2 (0.7%)7 (2.5%)65 (23.8%)133 (52.8%)170 (78.3%)
+15% or more0 (0.0%)0 (0.0%)30 (11.0%)97 (38.5%)143 (65.9%)
+20% or more0 (0.0%)0 (0.0%)15 (5.5%)57 (22.6%)103 (47.5%)
+30% or more0 (0.0%)0 (0.0%)6 (2.2%)33 (13.1%)45 (20.7%)
+50% or more0 (0.0%)0 (0.0%)0 (0.0%)29 (11.5%)39 (18.0%)
−0.1% or lower260 (91.9%)273 (97.2%)269 (98.5%)249 (98.8%)215 (99.1%)
−0.2% or lower246 (86.9%)270 (96.1%)266 (97.4%)246 (97.6%)212 (97.7%)
−0.5% or lower196 (69.3%)247 (87.9%)254 (93.0%)237 (94.0%)206 (94.9%)
−1% or lower110 (38.9%)198 (70.5%)241 (88.3%)226 (89.7%)199 (91.7%)
−2% or lower41 (14.5%)122 (43.4%)201 (73.6%)207 (82.1%)181 (83.4%)
−5% or lower1 (0.4%)10 (3.6%)100 (36.6%)152 (60.3%)145 (66.8%)
−10% or lower0 (0.0%)1 (0.4%)19 (7.0%)62 (24.6%)79 (36.4%)
−15% or lower0 (0.0%)0 (0.0%)1 (0.4%)24 (9.5%)33 (15.2%)
−20% or lower0 (0.0%)0 (0.0%)0 (0.0%)1 (0.4%)22 (10.1%)

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

Distributions and daily counts
Upside reached · 24hUpside reached (MFE, 24h)The most price moved up within 24 hours of each match: a high-water mark, never a close. 273 with a complete 24 hours.
Drawdown · 24hDrawdown (MAE, 24h)The worst price moved against within 24 hours of each match: the deepest point, never the close. 273 with a complete 24 hours.
Price 30 minutes laterForward 30-minute returnForward 30-minute returns across 283 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

  • 1 Sep9 matches
  • 2 Sep14 matches
  • 3 Sep12 matches
  • 4 Sep5 matches
  • 5 Sep2 matches
  • 6 Sep7 matches
  • 7 Sep8 matches
  • 8 Sep9 matches
  • 9 Sep7 matches
  • 10 Sep11 matches
  • 11 Sep10 matches
  • 12 Sep14 matches
  • 13 Sep12 matches
  • 14 Sep9 matches
  • 15 Sep12 matches
  • 16 Sep11 matches
  • 17 Sep8 matches
  • 18 Sep9 matches
  • 19 Sep8 matches
  • 20 Sep10 matches
  • 21 Sep11 matches
  • 22 Sep7 matches
  • 23 Sep12 matches
  • 24 Sep8 matches
  • 25 Sep8 matches
  • 26 Sep9 matches
  • 27 Sep10 matches
  • 28 Sep11 matches
  • 29 Sep10 matches
  • 30 Sep10 matches
  • 1 Oct0 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 43,201 eligible market-minutes (eligible_symbol_buckets) on DASHUSDT, 2026-09-01 00:00 to 2026-10-01 00:00 UTC.

What are MFE and MAE?

Reproducibility key (q#283bb9d6)

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
c764b05a2cce2a39e38b40d35fcb2488ecc1bfda3dfbabbbd252d4ba3f3a9680
query hash
283bb9d6d40ed3648a351e536437b24ad3398e9cca94e75e68de6ab5f444641c
scanned window
2026-09-01T00:00:00.000Z to 2026-10-01T00:00:00.000Z (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",
        "dashusdt"
      ],
      [
        "times.anchor_time",
        "between",
        [
          "2026-09-01T00:00:00.000Z",
          "2026-10-01T00:00:00.000Z"
        ]
      ]
    ]
  },
  "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","dashusdt"],["times.anchor_time","between",["2026-09-01T00:00:00.000Z","2026-10-01T00:00:00.000Z"]]]},"sort":["times.anchor_time","desc"],"page":{"limit":50,"cursor":null}}'

Past examples from the record, not a guarantee or a prediction. Nothing here is trading advice.