BacktestR - Trading Strategy Backtesting System

This project aims to build "BacktestR," a trading strategy backtesting system using React JavaScript library. BacktestR will allow users/traders to develop, backtest, and evaluate trading strategies using historical market data. By providing an intuitive and feature-rich platform, students can gain insights into the performance and profitability of their strategies before deploying them in live trading.

Requirements:

1- Strategy Development: Implement an interface where users/traders can define and customize trading strategies using indicators, signals, and predefined rules. Allow users/traders to adjust parameters and fine-tune their strategies.

2- Historical Market Data Integration: Integrate with external APIs or data providers to retrieve accurate and reliable historical market data for various assets and time frames.

3- Backtesting Engine: Develop a robust backtesting engine that accurately simulates trades based on historical market data and defined strategies. Track trades, calculate profits/losses, and consider factors like slippage and transaction costs.

4- Performance Evaluation: Provide comprehensive performance evaluation metrics, including profitability measures, risk-adjusted returns, and drawdown analysis. Visualize performance results and generate reports for strategy comparison and analysis.

5- Interactive Visualization: Incorporate interactive charts and graphs to visualize historical market data, strategy performance, and key indicators. Enable users/traders to analyze and interpret the data effectively.

6- User-Friendly Interface: Design an intuitive and responsive user interface that enables students to easily define, test, and evaluate their strategies. Ensure smooth navigation and a seamless user experience throughout the backtesting process.

7- GitLab Development and Documentation: Develop the project using GitLab for version control and collaboration. Ensure well-documented code, including detailed comments and instructions for running and deploying the platform.

Client


Contact: Mehdi Ravanbakhsh
Phone: 0426 797 142
Email[email protected]
Preferred contact: Email
Location: UWA School of Computer Science

IP Exploitation Model


The IP exploitation model requested by the Client is: IP to be assigned to the project proposer(s)



Department of Computer Science & Software Engineering
The University of Western Australia
Last modified: 17 July 2023
Modified By: Michael Wise
UWA