Abstract
We describe an adaptive algorithm to compute piecewise sparse polynomial approximations and the integral of a multivariate function over hyper-rectangular regions in medium dimensions. The key ingredient is a quasi-Monte Carlo quadrature rule which can handle the numerical integration of both very regular and less regular functions. Numerical tests are performed on functions taken from Genz package in dimensions up to 5 and on basket options pricing.
Keywords.: Adaptive numerical integration; piecewise polynomial approximations; basket option pricing
Received: 2010-02-05
Revised: 2010-09-21
Published Online: 2010-10-20
Published in Print: 2010-December
© de Gruyter 2010
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Keywords for this article
Adaptive numerical integration;
piecewise polynomial approximations;
basket option pricing
Articles in the same Issue
- Editiorial
- Random packing of hyperspheres and Marsaglia's parking lot test
- Diffusion in a nonhomogeneous medium: quasi-random walk on a lattice
- Improved Halton sequences and discrepancy bounds
- Generalizing Sudoku to three dimensions
- Adaptive integration and approximation over hyper-rectangular regions with applications to basket option pricing
- Exact simulation of Bessel diffusions
- A good permutation for one-dimensional diaphony
- Error bounds for computing the expectation by Markov chain Monte Carlo
- Stochastic iterative projection methods for large linear systems
- Increasing the number of inner replications of multifactor portfolio credit risk simulation in the t-copula model
- A genetic algorithm approach to estimate lower bounds of the star discrepancy
- Random and deterministic fragmentation models
- MCMC imputation in autologistic model