Create a professional project listing for the following requirement: I am looking to hire an experienced Python developer with strong knowledge of NSE derivatives to build a research-grade backtesting engine for a rules-based options selling strategy hedged with futures. This project is strictly for historical backtesting and risk analysis only. No live trading or broker integration required. Scope: • Use 3–5 years of NSE F&O historical data • Reconstruct historical option chains correctly per expiry • Handle futures expiry and rollover logic • Support short futures + short put structures (possible next-month future roll) • Compute Greeks (at least delta; IV calculation if not provided) • Avoid lookahead bias • Include realistic slippage, brokerage, STT, and transaction cost modeling • Track portfolio-level P&L, drawdown, delta exposure, and capital usage • Produce performance reports (CAGR, max DD, Sharpe, Calmar, monthly returns) • Export full trade log to CSV Requirements: • Strong understanding of option chains, expiry mechanics, and delta hedging • Experience with Black-Scholes and implied volatility calculation • Prior experience building backtesting systems for derivatives • Clean, modular Python architecture with configurable parameters Add screening questions: 1. How would you reconstruct historical option chains for NSE? 2. How do you prevent lookahead bias in options backtests? 3. How would you calculate delta if IV is not available? 4. Share an example of a derivatives-related backtesting project you have built. Budget: Open to serious proposals. Timeline: 3–4 weeks.