📈 Advanced Stock Analysis Suite (yfinance)

A professional-grade Python suite for automated technical analysis of Indian stocks. This tool consolidates multiple high-performance analysis modules into a single, user-friendly execution flow with intelligent caching and centralized configuration.

🚀 Key Features

1. 🔍 LTP Near Gaps

Detects significant price gaps (bullish and bearish) and identifies stocks currently trading near these unfilled gap zones—prime areas for potential support or resistance.

2. 🧱 Fractal Support & Resistance

Uses vectorized fractal detection to identify statistically significant price levels. It calculates level strength based on historical touches and proximity.

3. 🕯️ Candle & Gap Analysis

Provides a statistical breakdown of recent price action:

• Green/Red/Doji distribution.
• Open = High / Open = Low detection.
• Sustained gap performance.

4. 🧬 Fibonacci Retracement Levels

Automates the plotting of Fibonacci levels from recent swing highs and lows, highlighting stocks trading near key levels like the 50% or 61.8% "Golden Ratio."

5. 📉 Chart Pattern Detection

Vectorized detection of major classical patterns:

• Reversals: Double Top/Bottom, Head & Shoulders (Regular/Inverse).
• Continuation: Falling/Rising Wedges, Ascending/Descending/Symmetrical Triangles.
• Trend Channels: Ascending and Descending channels.

📦 Project Structure

stock_analysis/
├── run_analysis.py           # 🚀 Main entry point & CONFIG HUB
├── stock_analysis/       # Core package logic
│   ├── stock_data_manager.py  # Cache & fetching
│   ├── chart_patterns.py      # Pattern logic
│   ├── ... (other modules)
├── data_cache/               # Local .pkl data storage
├── outputs/                  # Results, CSVs, and Charts
└── pyproject.toml            # Build configuration

🛠️ Installation

1. Clone or download this repository.
2. Install dependencies:

   pip install -r requirements.txt
   

🚦 Quick Start

1. Configure your Scan

Open run_analysis.py at the root. You can easily modify:

• Ticker Groups: NSE indices, NIFTY 500, Custom lists.
• Periods: Change scan duration (e.g., 1y, 2y).
• Tolerances: Fine-tune how "near" a level a stock must be.

2. Run the Analysis

python run_analysis.py

💾 Intelligent Caching

This suite features a smart slicing cache. If you've fetched 1 year of data, running a 1-month candle analysis will be instantaneous, as it slices the existing local data rather than re-downloading.

📊 Outputs

Results are neatly organized in the outputs/ folder:

• Gaps Result: Detailed CSV of unfilled gaps.
• Support_Resistance: High-resolution charts with plotted levels.
• Fibonacci: CSV and charts showing retracement proximity.
• Chart_Patterns: Identified breakout/reversal opportunities.
• Candle_Analysis: Summary reports of price action statistics.

⚖️ Disclaimer

This project is for educational and research purposes only. It does not constitute financial advice. Always verify technical signals with your own due diligence before making trading decisions.