We present globally convergent multigrid methods for the nonsymmetric obstacle problems as arising from the discretization of Black—Scholes models of American options with local volatilities and discrete data. No tuning or regularization parameters occur. Our approach relies on symmetrization by transformation and data recovery by superconvergence.