How to Build Technical Analysis and Backtesting Workflow with pandas-ta-classic, Strategy Signals, and Performance Metrics

A tutorial walks through a full pandas-ta-classic trading workflow on Apple stock data.

It shows how to download and clean OHLCV data, then calculate indicators like RSI, MACD, Bollinger Bands, EMA, and candlestick patterns.

The article combines daily and weekly signals, defines entry and exit rules, and backtests the strategy with shifted positions.

It then computes performance metrics and visualizes the equity curve to assess how the strategy performs.

Overall, it demonstrates how to turn market data into testable signals and evaluate a technical trading system end to end.