options-strategy

You can backtest multi-leg options strategies by simulating portfolio performance over historical underlying price data using the Black-Scholes model. This engine calculates theoretical pricing, Greeks, and PnL metrics for complex strategies like iron condors, butterflies, and straddles.

Yes, you can calculate options Greeks without live market data by synthesizing prices and Greeks like Delta, Gamma, Theta, and Vega using historical volatility. The Black-Scholes engine provides a synthetic backtesting environment for theoretical pricing.

Yes, you need a configured signal engine to run options backtesting simulations. The engine also requires JSON-based parameter definitions to compute Greeks and PnL metrics across various asset classes using historical underlying price data.

Simulating options portfolio performance generates comprehensive performance analytics reports including equity curves, drawdown metrics, and trade-by-trade logs. These reports help evaluate hedging, volatility trading, and spread analysis strategies.

The Black-Scholes model supports backtesting volatility trading strategies across various asset classes using historical underlying price data. It synthesizes theoretical option prices and computes Greeks for multi-leg strategies without requiring live market data.

A synthetic backtesting environment computes theoretical option prices using the Black-Scholes model and historical volatility, meaning it does not reflect real-time market liquidity or slippage. It is designed for evaluating multi-leg strategy performance rather than live execution.