Parallel computing of a quasi-Monte Carlo algorithm for valuing derivatives
Parallel Computing - Special issue on parallel computing in economics, finance and decision-making
Performance Evaluation of a Multithreaded Fast Fourier Transform Algorithm for Derivative Pricing
The Journal of Supercomputing
Architecture independent parallel binomial tree option price valuations
Parallel Computing
A penalty method for American options with jump diffusion processes
Numerische Mathematik
Numerical valuation of options with jumps in the underlying
Applied Numerical Mathematics
A Finite Difference Scheme for Option Pricing in Jump Diffusion and Exponential Lévy Models
SIAM Journal on Numerical Analysis
Parallel computing in Asian option pricing
Parallel Computing
A Fast and Accurate FFT-Based Method for Pricing Early-Exercise Options under Lévy Processes
SIAM Journal on Scientific Computing
Option pricing with regime switching Lévy processes using Fourier space time stepping
FEA '07 Proceedings of the Fourth IASTED International Conference on Financial Engineering and Applications
Recent progress and challenges in exploiting graphics processors in computational fluid dynamics
The Journal of Supercomputing
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With the evolution of graphics processing units (GPUs) into powerful and cost-efficient computing architectures, their range of application has expanded tremendously, especially in the area of computational finance. Current research in the area, however, is limited both in terms of the type of options priced and the complexity of stock price models. This paper presents algorithms, based on the Fourier space time-stepping (FST) method, for pricing single- and multi-asset European and American options with stock prices following exponential Levy processes on a GPU. Furthermore, the single-asset pricing algorithm is parallelized to attain greater efficiency.