Abstract
AbstractIn the present chapter, we develop efficient pricing algorithms for multivariate problems, such as the pricing of multi-asset options and the pricing of options in stochastic volatility models, which exploit a third feature of the wavelet basis, namely that wavelets constitute a hierarchic basis of the univariate finite element space. This allows constructing the so-called sparse tensor product subspaces for the numerical solution of d-dimensional pricing problems with complexity essentially equal to that of one-dimensional problems.KeywordsSparse GridStochastic Volatility ModelScholes ModelTensor Product SpaceFull GridThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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