We introduce a set of improvements which allow the calculation of very tight lower bounds for Bermudan derivatives using Monte Carlo simulation. These lower bounds can be computed quickly, and with minimal hand-crafting. Our focus is on accelerating policy iteration to the point where it can be...

We investigate the pricing performance of eight trinomial trees and one binomial tree, which was found to be most effective in an earlier study, under 20 different implementation methodologies for pricing American put options. We conclude that the binomial tree, the Tian third‐order...

We study the simulation of range accrual coupons when valuing callable range accruals in the displaced-diffusion LIBOR market model (DDLMM). We introduce a number of new improvements that lead to significant efficiency improvements, and explain how to apply the adjoint-improved pathwise method...

We present a new non-nested approach for computing additive upper bounds for callable derivatives using Monte Carlo simulation. It relies on the regression of Greeks computed using adjoint methods. We also show that it is possible to early terminate paths once points of optimal exercise have...

We introduce two new methods to calculate bounds for zero-sum game options using Monte Carlo simulation. These extend and generalize upper-bound duality results to the case where both parties of a contract have Bermudan optionality. It is shown that the primal-dual simulation method can still be...

We develop new Monte Carlo techniques based on stratifying the stock's hitting-times to the barrier for the pricing and Delta calculations of discretely-monitored barrier options using the Black-Scholes model. We include a new algorithm for sampling an Inverse Gaussian random variable such that...