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< One-sided tape: buyers
HEMIUSDT · recorded history

One-sided tape: buyers on HEMIUSDT

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 HEMIUSDT itself

    Inspect HEMIUSDT now or at a past minute

  2. Its recorded moves

    HEMIUSDT market events and replays

  3. Test it on HEMIUSDT, 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
56.3% · 85 of 151 minutes
Other minutes
67.2% · 26,993 of 40,149 minutes

Price touched −10% or lower

When this held
19.2% · 29 of 151 minutes
Other minutes
39.1% · 15,698 of 40,149 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 151 of 153 matches with a full 24 hours after them. The 2 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, 2026-08-10 to 2026-09-09

About 4.9 a day, on 29 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
Measured152152151145134
Too recent112819
+0.1% or more144 (94.7%)147 (96.7%)150 (99.3%)144 (99.3%)134 (100.0%)
+0.2% or more134 (88.2%)143 (94.1%)150 (99.3%)144 (99.3%)134 (100.0%)
+0.5% or more105 (69.1%)128 (84.2%)146 (96.7%)143 (98.6%)134 (100.0%)
+1% or more72 (47.4%)103 (67.8%)137 (90.7%)136 (93.8%)134 (100.0%)
+2% or more39 (25.7%)71 (46.7%)118 (78.1%)120 (82.8%)134 (100.0%)
+5% or more10 (6.6%)38 (25.0%)85 (56.3%)116 (80.0%)134 (100.0%)
+10% or more1 (0.7%)20 (13.2%)69 (45.7%)107 (73.8%)134 (100.0%)
+15% or more1 (0.7%)12 (7.9%)62 (41.1%)105 (72.4%)134 (100.0%)
+20% or more0 (0.0%)7 (4.6%)55 (36.4%)105 (72.4%)134 (100.0%)
+30% or more0 (0.0%)4 (2.6%)50 (33.1%)104 (71.7%)134 (100.0%)
+50% or more0 (0.0%)1 (0.7%)16 (10.6%)87 (60.0%)126 (94.0%)
+100% or more0 (0.0%)0 (0.0%)0 (0.0%)11 (7.6%)83 (61.9%)
+200% or more0 (0.0%)0 (0.0%)0 (0.0%)0 (0.0%)20 (14.9%)
−0.1% or lower139 (91.4%)149 (98.0%)150 (99.3%)144 (99.3%)133 (99.3%)
−0.2% or lower125 (82.2%)142 (93.4%)146 (96.7%)141 (97.2%)130 (97.0%)
−0.5% or lower101 (66.4%)129 (84.9%)137 (90.7%)132 (91.0%)122 (91.0%)
−1% or lower68 (44.7%)106 (69.7%)129 (85.4%)125 (86.2%)118 (88.1%)
−2% or lower28 (18.4%)67 (44.1%)117 (77.5%)118 (81.4%)110 (82.1%)
−5% or lower4 (2.6%)22 (14.5%)68 (45.0%)86 (59.3%)77 (57.5%)
−10% or lower1 (0.7%)5 (3.3%)29 (19.2%)45 (31.0%)38 (28.4%)
−15% or lower0 (0.0%)1 (0.7%)15 (9.9%)25 (17.2%)20 (14.9%)
−20% or lower0 (0.0%)1 (0.7%)12 (7.9%)22 (15.2%)16 (11.9%)
−30% or lower0 (0.0%)0 (0.0%)6 (4.0%)9 (6.2%)7 (5.2%)
−50% or lower0 (0.0%)0 (0.0%)0 (0.0%)1 (0.7%)2 (1.5%)

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. 151 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. 151 with a complete 24 hours.
Price 30 minutes laterForward 30-minute returnForward 30-minute returns across 152 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

  • 10 Aug12 matches
  • 11 Aug11 matches
  • 12 Aug13 matches
  • 13 Aug16 matches
  • 14 Aug15 matches
  • 15 Aug3 matches
  • 16 Aug1 match
  • 17 Aug4 matches
  • 18 Aug11 matches
  • 19 Aug2 matches
  • 20 Aug2 matches
  • 21 Aug1 match
  • 22 Aug1 match
  • 23 Aug4 matches
  • 24 Aug4 matches
  • 25 Aug3 matches
  • 26 Aug11 matches
  • 27 Aug5 matches
  • 28 Aug0 matches
  • 29 Aug4 matches
  • 30 Aug6 matches
  • 31 Aug2 matches
  • 1 Sep3 matches
  • 2 Sep5 matches
  • 3 Sep2 matches
  • 4 Sep2 matches
  • 5 Sep1 match
  • 6 Sep6 matches
  • 7 Sep1 match
  • 8 Sep2 matches
  • 9 Sep0 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 HEMIUSDT, 2026-08-10 00:00 to 2026-09-09 00:00 UTC.

What are MFE and MAE?

Reproducibility key (q#341675ea)

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
418a74e4be785450505a2b88c7da983731b66fd02c30448d58ded11053128b2a
query hash
341675ea322f98fee147781366f874504cda9e20cc77224ff5180a1c60658ba5
scanned window
2026-08-10T00:00:00.000Z to 2026-09-09T00:00:00.000Z (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",
        "hemiusdt"
      ],
      [
        "times.anchor_time",
        "between",
        [
          "2026-08-10T00:00:00.000Z",
          "2026-09-09T00:00:00.000Z"
        ]
      ]
    ]
  },
  "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","hemiusdt"],["times.anchor_time","between",["2026-08-10T00:00:00.000Z","2026-09-09T00:00:00.000Z"]]]},"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.