The University of Waterloo quantitative analysis stocks club backtesting framework repository.
Project description
backtesting-framework
The University of Waterloo Quantitative Analysis Stocks Club Backtesting Framework
Welcome to the University of Waterloo Quantitative Analysis Stocks Club Backtesting Framework repository. This framework is designed to help you test and analyze various stock trading strategies using historical data.
Features
- Historical Data Analysis: Import and analyze historical stock data to backtest trading strategies.
- Strategy Implementation: Implement and test custom trading strategies.
- Performance Metrics: Evaluate the performance of your strategies with various metrics.
- Visualization: Visualize the results of your backtests with charts and graphs.
Getting Started
Prerequisites
- Python 3.x
- Required Python libraries (listed in
requirements.txt)
Installation
- Clone the repository:
git clone https://github.com/yourusername/backtesting-framework.git
- Navigate to the project directory:
cd backtesting-framework
- Install the required dependencies:
pip install -r requirements.txt
Usage
- Prepare your historical data in the required format.
- The current application runs on data in csv format and uses streamlit.
- Run the application:
streamlit run main.py
- CSV File Access:
- Due to file size constraints, the CSV file 'hackathon_sample_v2.csv' used for backtesting is stored externally
- You can download it from [https://drive.google.com/file/d/1H3ktLEsd3Bg9A9Rx5P45OdnYMEdkX29s/view?usp=sharing] and place it in the
data/directory.
Happy backtesting!
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