I have a rule-based forex strategy that now needs a rigorous retrospective check in Python. Your task is to take clean historical price data on the major pairs—think EUR/USD, GBP/USD, USD/JPY and the rest of the standard majors—code the logic exactly as provided, and return a clear statistical picture of how the system would have performed. Please structure the script so I can easily swap parameters, load new CSVs, and rerun the test without rewriting functions. The report you generate should cover core metrics such as CAGR, max drawdown, Sharpe and win-rate, plus an equity-curve plot. If you use common libraries like pandas, NumPy, TA-Lib or backtrader, keep the environment requirements in a simple requirements.txt. Deliverables • Well-commented Python source code • Read-me or quick-start notes for reproduction • Performance report (PDF or notebook) with the metrics and visuals outlined above I’ll supply the strategy rules and any additional constraints as soon as we start.