Parameterization based on randomized quasi-Monte Carlo methods

Authors:
Giray Ökten;Matthew Willyard
Affiliations:
Department of Mathematics, Florida State University, Tallahassee, FL 32306-4510, United States;Department of Mathematics, Florida State University, Tallahassee, FL 32306-4510, United States
Venue:
Parallel Computing
Year:
2010

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Abstract

We present a theoretical framework where any randomized quasi-Monte Carlo method can be viewed and analyzed as a parameterization method for parallel quasi-Monte Carlo. We present deterministic and stochastic error bounds when different processors of the computing environment run at different speeds. We implement two parameterization methods, both based on randomized quasi-Monte Carlo, and apply them to pricing digital options and collateralized mortgage obligations. Numerical results are used to compare the parameterization methods by their parallel performance as well as their Monte Carlo efficiency.