Variance-reduction technique in Monte Carlo: for every simulated path using boldsymbolZ, also evaluate the path using -boldsymbolZ, then average. Variance of the estimator becomes Var[(f(Z) + f(-Z))/2] = tfrac12(Var,f + Cov(f(Z), f(-Z))); variance falls relative to plain MC whenever f is monotone in Z (negative covariance). Effective for vanilla European options; ineffective when payoff symmetry breaks (e.g. one-touch barriers).