LITUSDT · recorded history

One-sided tape: buyers on LITUSDT

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 LITUSDT itself
Inspect LITUSDT now or at a past minute
Test it on LITUSDT, 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?

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: 49.4% · 127 of 257 minutes
Other minutes: 50.9% · 19,873 of 39,071 minutes

Price touched −10% or lower

When this held: 9.3% · 24 of 257 minutes
Other minutes: 9.3% · 3,649 of 39,071 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 257 of 261 matches with a full 24 hours after them. The 4 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 8.4 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.
Move	1 hour	4 hours	24 hours	72 hours	7 days
Measured	261	259	257	238	200
Too recent	0	2	4	23	61
+0.1% or more	236 (90.4%)	247 (95.4%)	251 (97.7%)	235 (98.7%)	200 (100.0%)
+0.2% or more	220 (84.3%)	239 (92.3%)	250 (97.3%)	235 (98.7%)	200 (100.0%)
+0.5% or more	172 (65.9%)	215 (83.0%)	239 (93.0%)	231 (97.1%)	199 (99.5%)
+1% or more	122 (46.7%)	183 (70.7%)	226 (87.9%)	222 (93.3%)	198 (99.0%)
+2% or more	40 (15.3%)	123 (47.5%)	199 (77.4%)	208 (87.4%)	197 (98.5%)
+5% or more	3 (1.1%)	23 (8.9%)	127 (49.4%)	180 (75.6%)	192 (96.0%)
+10% or more	0 (0.0%)	3 (1.2%)	64 (24.9%)	128 (53.8%)	174 (87.0%)
+15% or more	0 (0.0%)	0 (0.0%)	18 (7.0%)	70 (29.4%)	127 (63.5%)
+20% or more	0 (0.0%)	0 (0.0%)	0 (0.0%)	40 (16.8%)	68 (34.0%)
+30% or more	0 (0.0%)	0 (0.0%)	0 (0.0%)	10 (4.2%)	29 (14.5%)
−0.1% or lower	247 (94.6%)	254 (98.1%)	255 (99.2%)	237 (99.6%)	199 (99.5%)
−0.2% or lower	230 (88.1%)	245 (94.6%)	251 (97.7%)	235 (98.7%)	197 (98.5%)
−0.5% or lower	180 (69.0%)	226 (87.3%)	245 (95.3%)	232 (97.5%)	194 (97.0%)
−1% or lower	110 (42.1%)	182 (70.3%)	234 (91.1%)	228 (95.8%)	193 (96.5%)
−2% or lower	35 (13.4%)	118 (45.6%)	201 (78.2%)	208 (87.4%)	174 (87.0%)
−5% or lower	0 (0.0%)	14 (5.4%)	112 (43.6%)	158 (66.4%)	140 (70.0%)
−10% or lower	0 (0.0%)	1 (0.4%)	24 (9.3%)	73 (30.7%)	78 (39.0%)
−15% or lower	0 (0.0%)	1 (0.4%)	11 (4.3%)	17 (7.1%)	19 (9.5%)
−20% or lower	0 (0.0%)	1 (0.4%)	1 (0.4%)	11 (4.6%)	10 (5.0%)
−30% or lower	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	4 (2.0%)

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. 257 with a complete 24 hours.

Drawdown · 24hThe worst price moved against within 24 hours of each match: the deepest point, never the close. 257 with a complete 24 hours.

Price 30 minutes laterForward 30-minute returns across 261 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 Sep14 matches
2 Sep8 matches
3 Sep8 matches
4 Sep1 match
5 Sep7 matches
6 Sep7 matches
7 Sep9 matches
8 Sep6 matches
9 Sep9 matches
10 Sep8 matches
11 Sep11 matches
12 Sep12 matches
13 Sep11 matches
14 Sep8 matches
15 Sep8 matches
16 Sep9 matches
17 Sep11 matches
18 Sep8 matches
19 Sep8 matches
20 Sep11 matches
21 Sep9 matches
22 Sep11 matches
23 Sep6 matches
24 Sep6 matches
25 Sep10 matches
26 Sep11 matches
27 Sep11 matches
28 Sep9 matches
29 Sep10 matches
30 Sep4 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 LITUSDT, 2026-09-01 00:00 to 2026-10-01 00:00 UTC.

What are MFE and MAE?

Reproducibility key (q#9c6570c8)

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: 9c6570c896b027739daa69bdbf28c31b1aae6085ef10821ff2dc1c48fc46b7b3
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",
        "litusdt"
      ],
      [
        "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","litusdt"],["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}}'

One-sided tape: buyers on LITUSDT

Read it in context

Read LITUSDT itself

Test it on LITUSDT, then plan it

What happened in the next 24 hours?

Price touched +5% or higher

Price touched −10% or lower