Meshless Galerkin methods using radial basis functions
Mathematics of Computation
Radial Basis Functions
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Radial basis functions are well-known successful tools for interpolation and quasi-interpolation of the equal distance or scattered data in high dimensions. Furthermore, their truly mesh-free nature motivated researchers to use them to deal with partial differential equations(PDEs). With more than twenty-year development, radial basis functions have become a powerful and popular method in solving ordinary and partial differential equations now. In this paper, based on the idea of quasi-interpolation and radial basis functions approximation, a fast and accurate numerical method is developed for multi-dimensions Black-Scholes equation for valuation of european options prices on three underlying assets. The advantage of this method is that it does not require solving a resultant full matrix, therefore as indicated in the the numerical computation, this method is effective for option pricing problem.