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

⚠ No verified equity curve — no track-record source connected.

No score history is stored yet — only the current score is shown.

⚠ No live verification account connected — ask for proof before buying.

Alerts on changes: coming soon

Prop-firm compatibility not provided.

Data-completeness & trust index (not a profitability rating)