High-performance computing in finance: the last 10 years and the next
Parallel Computing - Special Anniversary issue
High-performance computing in finance: the last 10 years and the next
Parallel Computing - Special Anniversary issue
Performance optimization of financial option calculations
Parallel Computing - Special issue on parallel computing in economics, finance and decision-making
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
A Jump-Diffusion Model for Option Pricing
Management Science
Architecture independent parallel binomial tree option price valuations
Parallel Computing
A software architecture framework for on-line option pricing
The Journal of Supercomputing
Numerical inversion of probability generating functions
Operations Research Letters
Wavelet techniques for option pricing on advanced architectures
Euro-Par 2010 Proceedings of the 2010 conference on Parallel processing
Pricing Discretely Monitored Asian Options by Maturity Randomization
SIAM Journal on Financial Mathematics
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We price discretely monitored options when the underlying evolves according to different exponential Levy processes. By geometric randomization of the option maturity, we transform the n-steps backward recursion that arises in option pricing into an integral equation. The option price is then obtained solving n independent integral equations by a suitable quadrature method. Since the integral equations are mutually independent, we can exploit the potentiality of a grid computing architecture. The primary performance disadvantage of grids is the slow communication speeds between nodes. However, our algorithm is well-suited for grid computing since the integral equations can be solved in parallel, without the need to communicate intermediate results between processors. Moreover, numerical experiments on a cluster architecture show the good scalability properties of our algorithm.