When pricing Bermudan derivatives by regression-based methods, foresight bias will appear in lower bounds when using a single simulation to estimate the exercise strategy and to compute lower bounds. In this paper, we propose a new method to remove this kind of bias without introducing an...

We introduce a new simulation algorithm for computing the Hessians of Bermudan swaptions and cancellable swaps, the resulting pathwise estimates are unbiased and accurate. Given the exercise strategy, the pathwise angularities are removed by a sequence of measure changes. The change of measure...

We present a new class of upper bounds for the Monte Carlo pricing of Bermudan derivatives. This class contains both the additive and multiplicative upper bounds as special cases. We also see that the hypothesis that the pay-off is positive for the multiplicative upper bound is unnecessary. The...