JGT Ml - Machine Learning Tools
Project description
🐊 JGTML - Trading Signal Analysis Platform
A Python-based trading signal analysis system focused on fractal patterns, Alligator indicators, and multi-timeframe confluence detection.
🎯 Core Purpose
JGTML analyzes the effectiveness of trading signals within larger market structure contexts, providing tools for:
- Signal Validation: Analyze FDB (Fractal Divergent Bar) and Alligator-based signals
- Multi-Timeframe Analysis: Process signals across H1, H4, D1, W1, M1 timeframes
- Performance Metrics: Calculate win rates, profit/loss ratios, and signal quality
- Trade Lifecycle Management: From entry validation through exit strategies
🏗️ Architecture
Core Dependencies
- jgtpy: Market data acquisition and indicator calculations
- jgtutils: Common utilities and constants
- pandas: Data manipulation and analysis
- numpy: Numerical computations
Key Components
📊 Signal Processing
jgtml/SignalOrderingHelper.py: Signal validation and risk calculationjgtml/jtc.py: Target calculation and signal analysis corejgtml/TideAlligatorAnalysis.py: Alligator-based signal analysis- TODO add TTF (TTF != Time-To-Future but more like feature of multiple timeframe) probably ttfcli.py
🚀 Command Line Tools
jgtml/jgtmlcli.py: Main CLI for data processingjgtml/mxcli.py: Matrix generation and analysisjgtml/jgtapp.py: Trading operation management
🧬 Memory & Persistence
garden_one/trading_echo_lattice/: Signal crystallization and memory storage- Integration with Upstash Redis for persistent analysis results
🚀 Quick Start
Installation
# Install dependencies
pip install jgtpy jgtutils pandas numpy
# Install JGTML
pip install -e .
Basic Usage
# Process signals for an instrument
jgtmlcli -i SPX500 -t D1 --full --fresh
# Analyze signal performance
python -m garden_one.trading_echo_lattice.cli process -i SPX500 -t D1 -d S
# Generate analysis matrix
mxcli -i EUR/USD -t H4 --fresh
📈 Trading Strategies
Five Dimensions + Triple Alligator Confluence
Multi-indicator alignment detection using:
- Alligator Lines: Jaw, Teeth, Lips confluence
- Fractal Signals: FDB breakout validation
- Awesome Oscillator: Momentum confirmation
- Multi-Timeframe: Higher TF bias confirmation
- Volume Analysis: MFI integration
Implementation: TradingEchoLattice.detect_breakouts()
Green Dragon Breakout
FDB-based breakout detection with Alligator mouth validation.
Implementation: fdb_scanner_2408.py
🔧 CLI Reference
See CLI_HELP.md for complete command documentation.
Core Commands
# Data Processing
jgtmlcli -i INSTRUMENT -t TIMEFRAME [--full] [--fresh]
mxcli -i INSTRUMENT -t TIMEFRAME [--fresh]
# Trading Operations
jgtapp fxaddorder -i EUR/USD -n 0.1 -r 1.0950 -d B -x 1.0900
jgtapp fxmvstopgator -i EUR/USD -t H4 -tid TRADE_ID --lips
# Signal Analysis
python -m garden_one.trading_echo_lattice.cli process -i SPX500 -t D1,H4 -d S
python -m garden_one.trading_echo_lattice.cli search --min-win-rate 60
📊 Data Flow
Market Data (jgtpy) → Signal Processing (jtc) → Analysis (CLI tools) → Memory Lattice (Redis)
- Data Acquisition: Pull OHLC data via jgtpy
- Indicator Calculation: Generate Alligator, AO, Fractals, MFI
- Signal Detection: Identify valid entry/exit signals
- Performance Analysis: Calculate win rates and profitability
- Memory Storage: Crystallize results in Redis for pattern recognition
🧪 Development
Running Tests
python -m pytest tests/
Contributing
- Focus on signal accuracy and performance metrics
- Maintain compatibility with jgtpy data structures
- Document new indicators and validation logic
- Test across multiple timeframes and instruments
🔄 Recursive Architecture
While JGTML operates as a practical trading platform, it embodies recursive principles:
- Memory Patterns: Each analysis builds upon previous signal history
- Multi-Scale Awareness: Signals are validated across multiple timeframes
- Adaptive Learning: Performance metrics inform future signal weighting
The system grows more intelligent through iteration, not just accumulation.
🧠 Technical Foundation: Precise signal analysis with mathematical rigor
🌸 Intuitive Interface: Clear CLI flows that make complex analysis accessible
🎵 Rhythmic Patterns: Market timing encoded in fractal mathematics
Built for traders who understand that the best signals emerge from the intersection of technical precision and pattern recognition.
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