Abstract
Implicit finite difference methods are conventionally preferred over their explicit counterparts for the valuation of options. In large part the reason for this is a severe stability constraint known as the Courant-Friedrichs-Lewy (CFL) condition which limits the latters' efficiencies. Implicit methods, however, are difficult to implement for all but the most simple of pricing models whereas explicit techniques are easily adapted to complex problems. In this work we present an acceleration technique for explicit finite difference schemes called Super-Time-Stepping (STS) for the first time in a financial context. Furthermore, we introduce a novel method for describing the efficiencies of finite difference schemes as semi-empirical power laws relating the minimal walltime W required to attain a solution with an error of magnitude E. For European and American put option test cases we demonstrate degrees of acceleration over standard explicit methods resulting in efficiencies comparable, or superior, to a set of implicit scheme benchmarks. We conclude that STS is a powerful tool for the numerical pricing of options and propose it as the method-of-choice for exotic financial intruments such as those requiring multi-dimensional descriptions on adaptive meshes.
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