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- research-articleJanuary 2021
Green Simulation with Database Monte Carlo
ACM Transactions on Modeling and Computer Simulation (TOMACS), Volume 31, Issue 1Article No.: 4, Pages 1–26https://doi.org/10.1145/3429336In a setting in which experiments are performed repeatedly with the same simulation model, green simulation means reusing outputs from previous experiments to answer the question currently being asked of the model. In this article, we address the ...
- articleJune 2012
Pricing barrier and American options under the SABR model on the graphics processing unit
Concurrency and Computation: Practice & Experience (CCOMP), Volume 24, Issue 8Pages 867–879https://doi.org/10.1002/cpe.1771In this paper, we presented our study on using the graphics processing unit (GPU) to accelerate the computation in pricing financial options. We first introduced the GPU programming and the SABR stochastic volatility model. We then discussed pricing ...
- articleFebruary 2003
Time Series Simulation with Quasi Monte Carlo Methods
Computational Economics (KLU-CSEM), Volume 21, Issue 1-2Pages 23–43https://doi.org/10.1023/A:1022289509702This paper compares quasi Monte Carlo methods, in particular so-called (t, m, s)-nets, with classical Monte Carlo approaches for simulating econometric time-series models. Quasi Monte Carlo methods have found successful application in many fields, such as ...
- research-articleJanuary 2003
Randomized Polynomial Lattice Rules for Multivariate Integration and Simulation
SIAM Journal on Scientific Computing (SISC), Volume 24, Issue 5Pages 1768–1789https://doi.org/10.1137/S1064827501393782Lattice rules are among the best methods to estimate integrals in a large number of dimensions. They are part of the quasi-Monte Carlo set of tools. A theoretical framework for a class of lattice rules defined in a space of polynomials with coefficients ...
- articleDecember 1997
Exploring quasi Monte Carlo for marginal density approximation
Statistics and Computing (KLU-STCO), Volume 7, Issue 4Pages 217–228https://doi.org/10.1023/A:1018542303861We first review quasi Monte Carlo (QMC) integration for approximating integrals, which we believe is a useful tool often overlooked by statistics researchers. We then present a manually-adaptive extension of QMC for approximating marginal densities when ...