Elliott Wave Github !!exclusive!! Official

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

Developers and traders utilize these repositories to move beyond manual charting. Common features include: Automated Pattern Detection

: Algorithms that identify the 5-wave impulse and 3-wave corrective structures. Fibonacci Integration : Many tools, such as the elliot-waves-auto

repository, use Fibonacci retracement and extension levels to project future price zones. Machine Learning Optimization : Projects like PyBacktesting

apply genetic algorithms to optimize wave parameters for better forecasting. Validation Rules : Tools like the ElliottWaveAnalyzer

validate identified patterns against strict sets of rules (e.g., ensuring wave 3 is not the shortest). Key Open-Source Projects

The following repositories are notable for their specific contributions to the Elliott Wave ecosystem: ElliottWaveAnalyzer

: A Python-based scanner that finds impulse and corrective movements by trying multiple combinations of price patterns. python-taew

: A package focused on technical analysis that provides wave labeling and backtracking based on established research. ElliottWaves (alessioricco)

: A script specifically for pattern discovery on financial dataframes, featuring visualization via Matplotlib. EW_Dataset elliott wave github

: An open-source dataset of impulse waves designed to train Convolutional Neural Networks (CNNs) for automatic pattern recognition. Strategy-ElliottWave

: An MQL4 strategy implementation for MetaTrader, integrating Elliott Wave indicators for automated trading. Implementation Languages

GitHub hosts these projects in several primary languages, depending on the trader's environment:

drstevendev/ElliottWaveAnalyzer: Tools to find Elliot ... - GitHub

GitHub has become a vital hub for traders and developers seeking to automate Elliott Wave Theory, a technical analysis method based on the idea that market prices move in predictable cycles or "waves" driven by investor psychology.

While the theory is famously subjective, open-source projects on GitHub are working to standardize wave counting using algorithms, machine learning, and visualization tools. Core Concepts of Elliott Wave Analysis

Before diving into GitHub repositories, it is essential to understand the basic structure being modeled: Impulse Waves (1, 3, 5): These follow the primary trend.

Corrective Waves (2, 4, A, B, C): These act as counter-trend movements.

The 5-3 Pattern: A complete cycle consists of an 8-wave pattern—five in the direction of the trend and three against it. Top Elliott Wave Projects on GitHub Elliott Wave Theory on GitHub encompasses a range

Developers have created various tools to find, validate, and trade these patterns. 1. Automated Wave Recognition & Scanners

Finding Elliott Wave patterns manually is time-consuming. Several repositories offer automated detection:

ElliottWaveAnalyzer: This Python-based tool uses an iterative scanner to find "monowaves" (the smallest elements of a trend) and validate them against 12345 impulsive movements.

ElliottWaves Python Script: A script specifically designed to find and analyze recurrent price patterns in financial dataframes.

python-taew: A library focused on automated Elliott Wave labeling to fill the gap of missing open-source labeling packages. 2. Machine Learning & Genetic Algorithms

For advanced users, some projects integrate AI to improve forecast accuracy:

EW_Dataset: An open-source dataset designed for training Convolutional Neural Networks (CNNs) to recognize impulse wave structures in financial charts.

PyBacktesting: This project models the theory and uses genetic algorithms to optimize parameters, often using the Sharpe ratio as a fitness function. 3. Strategy Development & Backtesting

These tools help turn Elliott Wave counts into actionable trading systems: Strategy based on the Elliot Wave indicator. - GitHub How to Contribute to Open Source Elliott Wave

Strategy Elliot Waves. Strategy based on the Elliot Waves indicator. Dependencies. Tag. Framework. v1.000. v2.000. v1.001. v2.001.

drstevendev/ElliottWaveAnalyzer: Tools to find Elliot ... - GitHub

How to Contribute to Open Source Elliott Wave

If you are a developer and a trader, you can add value by contributing to these projects. The community currently lacks:

  1. AI Training Data: A labeled dataset of "correct" wave counts (this is the holy grail—no public dataset exists).
  2. Real-time Alerts: Most repos output charts, not JSON alerts for trading bots.
  3. Multi-Timeframe Confirmation: Scripts that check if a Wave 3 on the 15-minute chart aligns with a Wave 3 on the 4-hour chart.

Step 2: Trend Detection

Once you have pivots, you classify the sequence (Up, Down, Up). The algorithm checks if the second "Up" leg exceeds the first "Up" leg (for an impulse).

How to Evaluate a Repository

| Criterion | What to check | |-----------|----------------| | Recent commits | Last update <1 year → maintained. | | Sample charts | Look for screenshots showing correct wave labels. | | Test coverage | At least 2-3 test files (e.g., test_impulse.py). | | Validation | Does it compare results against known historical waves (e.g., SPX 2009-2021)? |

5. Step-by-Step: Running a Python Elliott Wave Script

If you find a Python repository you want to use, here is the standard workflow:

Prerequisites: Install Python and Git on your computer.

  1. Clone the Repo: 
    git clone https://github.com/username/elliott-wave-repo.git
  2. Install Dependencies: Navigate to the folder and look for a requirements.txt file. Run: 
    pip install -r requirements.txt
    (This installs pandas, matplotlib, numpy, etc.)
  3. Prepare Data: Most scripts require a CSV file with market data (Date, Open, High, Low, Close). You can download this from Yahoo Finance or your broker.
  4. Run the Script: 
    python main.py
  5. Analyze Output: The script will likely output an image (chart) or a text file predicting the next wave count.

4. fractal-wave-algo (C++/Python bindings)

Best for: High-frequency futures trading. Elliott Wave is fractal by nature. This repo uses recursive fractal decomposition to break a daily chart down to minute-level waves. It is extremely fast but has a steep learning curve.

Top Elliott Wave Repositories on GitHub

To save you hours of sifting, here are the most active and well-documented projects as of 2025.