Advanced Variance Reduction Techniques in Monte Carlo Option Pricing: Antithetic, Control, and Hybrid Optimal Methods

This preprint presents a comprehensive comparison of variance reduction techniques in Monte Carlo simulation for European call option pricing under the Black-Scholes model. Standard Monte Carlo is benchmarked against antithetic variates, control variate (β = 1), and a hybrid optimal method combining antithetic paths with covariance-based control correction. Numerical results demonstrate that the hybrid approach achieves near-exact pricing with 10–50× reduced variance, even at low path counts. The practical implications for production quantitative trading systems are discussed, emphasizing computational efficiency in high-frequency and exotic option pricing.