Range compression on the 15-minute candle

About 2,142 a day, on 31 of 31 days: spread through the record rather than one event.

How to read a distribution

Matches per UTC day

• 5 Sep2,222 matches
• 6 Sep2,568 matches
• 7 Sep2,533 matches
• 8 Sep2,155 matches
• 9 Sep3,045 matches
• 10 Sep1,891 matches
• 11 Sep2,738 matches
• 12 Sep1,906 matches
• 13 Sep2,564 matches
• 14 Sep1,975 matches
• 15 Sep2,703 matches
• 16 Sep2,154 matches
• 17 Sep1,863 matches
• 18 Sep2,415 matches
• 19 Sep2,375 matches
• 20 Sep2,426 matches
• 21 Sep2,225 matches
• 22 Sep2,105 matches
• 23 Sep2,025 matches
• 24 Sep1,991 matches
• 25 Sep2,102 matches
• 26 Sep2,218 matches
• 27 Sep2,500 matches
• 28 Sep1,782 matches
• 29 Sep1,906 matches
• 30 Sep1,803 matches
• 1 Oct1,752 matches
• 2 Oct2,485 matches
• 3 Oct1,689 matches
• 4 Oct2,286 matches
• 5 Oct9 matches

• 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 markets 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 22,579,909 eligible market-minutes (eligible_symbol_buckets) on 524 markets, 2026-09-05 00:00 to 2026-10-05 00:00 UTC.
• These counts pool every market, so markets that match often weigh more. Each market page compares that market with its own reference.
• Live status is not connected yet, so this page is recorded history only.

What are MFE and MAE?

{
  "schema_version": "research_query.v2",
  "normalization_version": "archive_normalization.v1",
  "feature_version": "feature_defs.v1",
  "target": "record_occurrences",
  "where": {
    "all": [
      [
        "feature.candle_compression_15m",
        "gte",
        2
      ],
      [
        "times.anchor_time",
        "between",
        [
          "2026-09-05T00:00:00.000Z",
          "2026-10-05T00:00:00.000Z"
        ]
      ]
    ]
  },
  "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.candle_compression_15m","gte",2],["times.anchor_time","between",["2026-09-05T00:00:00.000Z","2026-10-05T00:00:00.000Z"]]]},"sort":["times.anchor_time","desc"],"page":{"limit":50,"cursor":null}}'