Index Options Strategy Backtest

I need a comprehensive back-test of my index-options trading strategy over the last five years. The entry, exit, and position-sizing rules are already defined; your role is to code them faithfully, run the historical simulation, and prepare a performance summary.

The finished report should quantify winning percentage, net profit and loss, maximum drawdown, rolling-maximum-drawdown (RMDD), CAGR, expectancy ratio, and the time spent in maximum drawdown. Clear charts—equity curve, drawdown curve, and any other visuals that highlight risk and return—will make the findings easy to digest.

Feel free to work in Python (pandas, NumPy, backtrader, Zipline), R, or another robust back-testing environment as long as the process is fully transparent and I can rerun or adapt it later.

Deliverables:
• Well-commented source code or notebook that imports reliable index-option data, executes the strategy, and outputs the metrics
• A concise PDF or Markdown report featuring all requested statistics and supporting charts
• A short walkthrough (written or call) so I can adjust parameters and replicate results

Accuracy in data handling and strict adherence to my trade logic are essential; that will be the primary acceptance criterion. Once we agree, I'll share the exact rules so you can get started right away.