Elliott Wave Github !full! Link

Searching for "Elliott Wave" on GitHub provides access to various open-source implementations for automated pattern recognition, backtesting, and quantitative analysis. These repositories generally fall into three categories: automated labeling scripts, machine learning-driven models, and educational datasets. Automated Recognition & Labeling

Elliott Wave Theory on GitHub encompasses a range of open-source tools designed to automate wave counting, visualize patterns, and backtest trading strategies based on financial market cycles. Core Functionality of GitHub Repositories elliott wave github

ElliottWaves Python Script: A script specifically designed to find and analyze recurrent price patterns in financial dataframes. Searching for "Elliott Wave" on GitHub provides access

Strategy-ElliottWave (EA31337): A dedicated repository containing trading strategies specifically based on the Elliott Wave indicator. Datasets & Educational Resources Stars : ~60 Author : fractalcap Features :

✅ Multi‑Timeframe Fractal Analysis – From 1‑minute to weekly bars, via configurable zigzag thresholds.

elliottwave (Python Package): Several developers have created lightweight libraries that allow you to pass a Pandas DataFrame and receive a list of potential wave counts.

5. FractalWave (Rust + Python bindings)

• Stars: ~60
• Author: fractalcap
• Features:
  • Detect pivots using prominence.
  • Generate simple 5-wave candidate.
  • Check rule: wave3 length > wave1 and wave3 != shortest.
  • Compute fib extension for wave 3 target.
  • Rule-based deterministic scanner: encode classical EWT rules to accept/reject candidate counts; easiest to implement and explain but brittle.
  • Heuristic scoring: score candidate counts on rule satisfaction, fib alignment, and momentum indicators; keep top-N counts for downstream use.
  • Machine learning aid: use clustering or sequence models to learn common pivot patterns; treat ML as a helper for pivot proposal, not a replacement for EWT rules.
  • Hybrid: deterministic constraints + scoring + ML pivot suggestions.