Variance reduction for diffusions

Practical Variance Reduction via Regression for Simulating Diffusions

The well-known variance reduction methods—the method of importance sampling and the method of control variates—can be exploited if an approximation of the required solution is known. Here we employ conditional probabilistic representations of solutions together with the regression method to obtain sufficiently inexpensive (although rather rough) estimates of the solution and its derivatives by ...

Approximating Martingales for Variance Reduction

\Knowledge of either analytical or numerical approximations should enable more eecient simulation estima-tors to be constructed." This principle seems intuitively plausible and certainly attractive, yet no completely satisfactory general methodology has been developed to exploit it. We present a new approach for Markov processes that relies on the construction of a martingale that is strongly c...

Variance Reduction for Russian-roulette

Variance Reduction via Lattice

This is a review article on lattice methods for multiple integration over the unit hypercube, with a variance-reduction viewpoint. It also contains some new results and ideas. The aim is to examine the basic principles supporting these methods and how they can be used eeectively for the simulation models that are typically encountered in the area of Management Science. These models can usually ...

Variance Reduction Techniques in . . .