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Candlestick Scanner Ranking and Deduplication

Install and import#

bash
npm install fintech-algorithms
ts
import { rankAndDeduplicate } from "fintech-algorithms/price-action-and-candlesticks/candlestick-scanning-and-context/candlestick-scanner-ranking-and-deduplication";

Signature#

rankAndDeduplicate(data)

calculate a traceable composite rank, keep deterministic order, and deduplicate only within an explicit identity key and bar window.

Parameters#

NameTypeNotes
data{ recency_half_life_bars: number; dedup_window_bars: number; occurrences: { occurrence_id: string; instrument_id: string; interval: string; pattern_id: string; direction: string; end_index: number; confidence: number; age_bars: number; liquidity_score: number; priority_score: number }[] }Topic input record; the required fields are fixed by this topic data-contract.

Returns#

{ state, ranked_count, suppressed_count, ranked, suppressed }

One ready ranking record containing stable ranks and component traces for kept occurrences plus reason-coded duplicates and both counts.

Complexity: time O(n log n) worst case; see README for topic-specific n, space O(n).

Worked example#

verified This is the worked example published in the article, replayed by the test suite on every run. The output cannot drift.

Input#

data
{
  "recency_half_life_bars": 5,
  "dedup_window_bars": 2,
  "occurrences": [
    {
      "occurrence_id": "A",
      "instrument_id": "SYNTH:AAA",
      "interval": "5m",
      "pattern_id": "D06-F03-A01",
      "direction": "bullish",
      "end_index": 10,
      "confidence": 90,
      "age_bars": 1,
      "liquidity_score": 0.8,
      "priority_score": 0.8
    },
    {
      "occurrence_id": "B",
      "instrument_id": "SYNTH:AAA",
      "interval": "5m",
      "pattern_id": "D06-F03-A01",
      "direction": "bullish",
      "end_index": 11,
      "confidence": 85,
      "age_bars": 0,
      "liquidity_score": 0.9,
      "priority_score": 0.9
    },
    {
      "occurrence_id": "C",
      "instrument_id": "SYNTH:BBB",
      "interval": "5m",
      "pattern_id": "D06-F02-A06",
      "direction": "bullish",
      "end_index": 11,
      "confidence": 70,
      "age_bars": 2,
      "liquidity_score": 1,
      "priority_score": 0.5
    }
  ]
}

Call#

rankAndDeduplicate(data)

Returns#

object with 3 fields: state, ranked_count, suppressed_count

{
  "state": "ready",
  "ranked_count": 2,
  "suppressed_count": 1
}

Diagrams#

Candlestick Scanner Ranking and Deduplication — decision

Calculation flow#

Decision flow 
flowchart LR
    A["Validated point-in-time input"] --> B["Normalize rank components"]
    B --> C["Apply declared weights"]
    C --> D{"Boundary satisfied?"}
    D -->|"Yes"| E["Reason-coded ready output"]
    D -->|"No"| F["Explicit rejected or unavailable state"]

How it works#

This page states the contract — how to call it correctly. The article explains the concept: why it works, and where it breaks.

Read the article →

References#

The rest of the Candlestick Scanning and Context family#