Bollinger Forest

A Python implementation of the "Enhanced Bollinger Band Stock Quantitative Trading Strategy Based on Random Forest".

Structure

• src/bollinger_forest: Source code.
• data/: Local cache for stock data (CSV).
• evaluation/: Output plots and summary CSVs.

Installation

1. Clone the repository.
2. Install in editable mode:

pip install -e .

Usage

Run the command line tool:

bollinger-forest --tickers 2888.HK 0005.HK 0939.HK --start 2011-01-01 --end 2021-12-31

Arguments

• --tickers: List of Yahoo Finance tickers (default: 2888.HK 0005.HK).
• --start: Start date for data (YYYY-MM-DD).
• --end: End date for data.
• --split: Date to split Training and Testing data (default: 2019-01-01).

Methodology

1. Classical Strategy: Buys when price < Lower Band, Sells when price > Upper Band.
2. Enhanced Strategy:
   • Uses Random Forest to predict the 3-day Weighted Moving Average (WMA) change.
   • Uses Predicted WMA to trigger Bollinger Band signals.
   • Uses ATR (Average True Range) for Stop Loss logic.

4. How to Run

1. Create the folder structure as shown above.
2. Paste the code into the respective files.
3. Open your terminal in the root folder.
4. Install: pip install -e .
5. Run: bollinger-forest --tickers 2888.HK 0005.HK