{"repo":"IsaacCheng9/quant-trading-strategy-backtester","free":true,"listed":false,"github":"https://github.com/IsaacCheng9/quant-trading-strategy-backtester","clone":"git clone https://github.com/IsaacCheng9/quant-trading-strategy-backtester.git","description":"A quantitative trading strategy backtester with an interactive dashboard. Enables users to implement, test, and visualise trading strategies using historical market data, featuring customisable parameters and key performance metrics. Developed with Python and Polars.","language":"Python","stars":44,"topics":["backtester","backtesting","mean-reversion","moving-average","pairs-trading","pandas","plotly","polars","python","quant"],"license":null,"category":"trading","readme_excerpt":"Quant Trading Strategy Backtester A quantitative trading strategy backtester with an interactive dashboard. Enables users to implement, test, and visualise trading strategies using historical market data, featuring customisable parameters and key performance metrics. Developed with Python. Try the deployed app here on Streamlit Cloud! Key Features - Multiple trading strategies – Buy and Hold, Mean Reversion, Moving Average Crossover, and Pairs Trading - Walk-forward validation – parameter optimisation with expanding training windows to reduce overfitting - Exploratory current-universe selection – grid search over parameter combinations and today's largest S&P 500 constituents - Transaction costs and slippage modelling – configurable fees and slippage for realistic performance estimates - Trade ledger and cost attribution – explicit trade events, turnover, gross/net returns, and cumulative cost drag - Cointegration-gated pairs selection – Engle-Granger filtering for automatic pairs trading selection and p-value diagnostics for manual pairs - Benchmark-relative reporting – SPY-relative excess return, beta, annualised alpha, and information ratio for the displayed backtest period - Efficient data processing – vectorised computation using Polars for improved performance - Interactive web-based dashboard – Streamlit UI for strategy configuration, backtesting, and analysis - Trade and spread visualisation – equity curves with trade markers and pairs spread z-score charts with entry","default_branch":null,"files":null,"tree":[],"storefront":"/r/IsaacCheng9","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/IsaacCheng9/quant-trading-strategy-backtester/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}