options-strategy

You can backtest multi-leg options strategies using synthetic data by simulating portfolio performance against historical underlying price data, calculating theoretical pricing and Greeks without requiring a live market data feed.

The Black-Scholes model calculates theoretical option values and Greeks including Delta, Gamma, Theta, and Vega by utilizing historical volatility to evaluate risk exposure and time decay impact during backtesting simulations.

Yes, you can simulate complex multi-leg structures like Iron Condors, Butterflies, and Calendar Spreads for crypto pairs such as BTC-USDT by running backtests with a structured configuration file.

Yes, running an options backtesting simulation requires a custom signal engine implementation to generate trading instructions, alongside a structured configuration file to define the multi-leg portfolio strategy parameters.

The best way to evaluate volatility and hedging strategies is by simulating multi-leg option portfolio structures against historical underlying price data to analyze theoretical pricing and portfolio performance metrics.

Using historical volatility for options pricing in backtesting means the simulation relies on synthetic data and theoretical Black-Scholes values rather than real-time market dynamics, which may not capture live execution slippage.