American double Heston options skip point-by-point free-boundary solving: one training run yields boundary, value and Greeks
Pricing American options under the double Heston model is hard because the early exercise boundary is itself unknown and must be solved together with the option value. A deep learning scheme that multiplies the outputs of several sub-networks fixes that boundary first, then predicts the early exercise boundary, the value function and first- and second-order Greeks in a single training run. Under constant and stochastic interest rates, its value functions are compared numerically with asymptotic expansion and least-squares Monte Carlo results.