Elliott Wave (EW)
EW scenario generation, probability aggregation, and invalidation logic.
What It Measures
Elliott Wave models structural sequence risk by evaluating candidate wave patterns and scenario probabilities per timeframe.
Inputs
- Noise-filtered pivots from timeframe OHLC data.
- Pattern validation checks and hierarchy fit context.
- Scenario generation targets/invalidation levels.
ew_thresholds:{"1d": 0.12, "1w": 0.18, "4h": 0.05}ew_threshold_floors:{"1d": 0.05, "1w": 0.12, "4h": 0.03}ew_nesting_fit_enabled:trueew_nesting_bonus_strength:moderate
Calculation Pipeline
- Detect pivots and candidate wave structures.
- Score pattern validity and hierarchy consistency.
- Generate bull and bear scenarios with targets/invalidation.
- Normalize scenario probabilities to 100 total.
- Aggregate bull and bear probabilities from scenarios.
Formulas & Rules
bull_prob = Σ scenario.probability where scenario.type == 'bull'
bear_prob = Σ scenario.probability where scenario.type == 'bear'
direction = bullish if bull_prob > bear_prob else bearish
Constraints include:
- pattern validity checks
- pivot-anchored invalidation
- hierarchy fit (cross-timeframe consistency)Live Worked Example
| TF | Bull/Bear | Pattern | Top Scenario | Target | Invalidation |
|---|---|---|---|---|---|
| 1W | 55/45 | corrective | Bull Reversal (55%) | $159,630 | < $56,810 |
| 1D | 55/45 | corrective | Bull Reversal (55%) | $75,999 | < $61,672 |
| 4H | 55/45 | impulse | Bull Reversal (55%) | $72,858 | < $66,907 |
Failure / Fallback Behavior
- If no pivots or valid pattern exists, fallback payload returns neutral probabilities and minimal structure.
- Invalid or low-quality patterns are de-prioritized by score/hierarchy logic.
- Scenario set enforces dual-sided coverage where possible (bull + bear alternatives).
Interpretation Notes
Use EW as a path model. Highest-probability scenario is a working hypothesis until invalidation breaks.