Backtesting Trading Strategies

A proper backtesting framework that handles the tedious parts: fetching historical data, running eight common strategies (SMA, RSI, MACD, Bollinger bands, etc.), and calculating the metrics you actually care about like Sharpe ratio, max drawdown, and win rate. The parameter optimization via grid search is genuinely useful for finding which moving average periods or RSI thresholds work best. Everything outputs to reports with equity curves, trade logs, and performance summaries. Built on yfinance and pandas, so it's straightforward Python without exotic dependencies. The honest limitation is that backtesting always looks better than live trading, but at least this gives you a systematic way to eliminate bad ideas before risking capital. Good for both crypto and traditional assets if you want to validate a signal or compare different approaches.

Install to Claude Code

npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill backtesting-trading-strategies --agent claude-code