YEN | Unified Stock Analysis Workflow Manager

A comprehensive Python-based stock analysis suite that combines Volume Spread Analysis (VSA), volume anomaly detection, AI-powered reporting, and stock screening into unified workflows. YEN eliminates the complexity of managing individual analysis scripts by providing predefined workflows that chain together multiple analysis tools.

Features

Core Workflows

• VSA Analysis Pipeline: Complete Volume Spread Analysis with data export, cleaning, and visualization
• Volume Anomaly Detection: Statistical analysis to identify unusual volume patterns
• AI-Powered Analysis: Generate comprehensive analysis reports using OpenAI's GPT models
• Stock Screening: Filter stocks by institutional ownership, volatility, and volume criteria
• Batch Processing: Process multiple tickers through any workflow
• Daily Market Roundup: Real-time price/volume movement tracking with Kabu

Analysis Tools

• Volume Spread Analysis (VSA): Detect high-probability trading signals based on volume-price relationships
• Statistical Anomaly Detection: Z-score based volume anomaly identification
• Technical Data Export: Multi-timeframe OHLCV data extraction from Yahoo Finance
• Data Cleaning & Preprocessing: Automated CSV cleaning and formatting
• Interactive Visualizations: Plot generation for signals and anomalies

Project Structure

yen/
├── yen.py                     # Main workflow manager
├── core/                       # Core analysis scripts
│   ├── data_exporter.py       # OHLCV data fetching from Yahoo Finance
│   ├── clean_csv_data.py      # CSV data cleaning and preprocessing
│   ├── vsa.py                 # Volume Spread Analysis engine
│   ├── detect_volume_anomalies.py  # Statistical volume anomaly detection
│   ├── report_generator.py    # AI-powered analysis report generation
│   ├── stock_scanner.py       # Stock screening by fundamental criteria
│   ├── prompt_generator.py    # VPA analysis prompt generation
│   ├── prompt_generator_v2.py # Multi-ticker prompt generation
│   ├── txt_to_csv.py         # Data format conversion utility
│   ├── kabu.py               # Daily price/volume movement tracker
│   ├── kabu_visualizer.py    # PNG visualization generator
│   └── kabu_visualizer_html.py # HTML report generator
├── data_exports/             # Exported CSV data storage
├── vsa_outputs/             # VSA analysis results
└── requirements.txt         # Python dependencies

Installation

1. Clone the Repository

   git clone https://www.github.com/YedTheEmo/yen.git
   cd yen

2. Create Virtual Environment

   python -m venv venv
   source venv/bin/activate  # Linux/Mac
   # or
   venv\Scripts\activate     # Windows

3. Install Dependencies

   pip install -r requirements.txt

4. Configure OpenAI API (Optional) For AI-powered analysis, create config.json:

   {
       "openai_api_key": "your-openai-api-key-here"
   }

Usage Examples

VSA Analysis Pipeline

Complete Volume Spread Analysis with visualization:

python yen.py vsa-analysis AAPL 2024-01-01 2024-12-31 --plot --threshold 1.0

Volume Anomaly Detection

Detect unusual volume patterns:

python yen.py volume-anomalies TSLA 2024-01-01 2024-12-31 --threshold 2.0

AI-Powered Analysis Report

Generate comprehensive AI analysis:

python yen.py ai-analysis NVDA 2024-01-01 2024-12-31 --intervals 1wk 1d 1h

Complete Analysis Suite

Run all analyses in sequence:

python yen.py full-analysis MSFT 2024-01-01 2024-12-31

Stock Screening

Filter stocks by criteria:

python yen.py stock-screening 10.0 0.3 1000000 --output-file filtered_stocks.txt

Batch Processing

Process multiple tickers from file:

python yen.py batch-analysis tickers.txt 2024-01-01 2024-12-31 vsa --plot

Daily Market Roundup (Kabu)

Generate daily price/volume summary:

python kabu/kabu.py --tickers tickers.txt
python kabu/kabu_visualizer_html.py --report daily_report.json --output daily_report.html

🔧 Individual Script Usage

Data Export

python yen/data_exporter.py AAPL 2024-01-01 2024-12-31 --intervals 1d 1h

VSA Analysis

python yen/vsa.py -f data.csv -t 1.0 0.5 -p -d 5

Volume Anomaly Detection

python yen/detect_volume_anomalies.py input.csv output.csv --threshold 2.0

Stock Screening

python yen/stock_scanner.py 10.0 0.3 1000000 --ticker-file sp500.txt --resume

Workflow Details

VSA Analysis Pipeline

1. Data Export: Fetch OHLCV data from Yahoo Finance
2. Data Cleaning: Remove headers and handle missing data
3. VSA Analysis: Apply Volume Spread Analysis algorithms
4. Visualization: Generate signal plots and charts

Volume Anomaly Detection

1. Data Export & Cleaning: Prepare clean OHLCV dataset
2. Statistical Analysis: Calculate volume z-scores
3. Anomaly Identification: Flag volumes exceeding threshold
4. Report Generation: Export anomaly summary to CSV

AI Analysis Workflow

1. Data Collection: Multi-timeframe data aggregation
2. Prompt Generation: Create structured analysis prompts
3. AI Processing: Send to OpenAI API for analysis
4. Report Formatting: Generate HTML/Markdown reports

Requirements

• Python 3.7+
• pandas
• numpy
• yfinance
• matplotlib
• requests
• openai (for AI analysis)

Use Cases

• Day Trading: VSA signal detection for intraday opportunities
• Swing Trading: Multi-timeframe analysis for position entries
• Risk Management: Volume anomaly alerts for unusual market activity
• Portfolio Screening: Filter stocks by fundamental and technical criteria
• Market Research: AI-powered analysis of market trends and patterns
• Daily Monitoring: Automated daily market roundup and alerts

Important Notes

• API Limits: OpenAI API usage incurs costs based on token consumption
• Data Sources: Uses Yahoo Finance via yfinance library
• File Management: Temporary files are automatically cleaned up
• Error Handling: Graceful failure recovery with detailed error messages
• Resume Support: Stock screening supports resume functionality for large datasets

Troubleshooting

Argument Order Issues

Always place optional arguments after positional arguments:

# Correct
python yen.py vsa-analysis AAPL 2024-01-01 2024-12-31 --intervals 1d

# Incorrect
python yen.py vsa-analysis --intervals 1d AAPL 2024-01-01 2024-12-31

Missing Config File

If report_generator.py fails, ensure config.json exists with your OpenAI API key.

Data Export Issues

Check internet connectivity and verify ticker symbols are valid.

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YEN - Your comprehensive toolkit for professional stock market analysis and trading signal generation.