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A computationally efficient numerical approach for multi-asset option pricing
13
Citations
25
References
2018
Year
Numerical AnalysisMathematical ProgrammingOption PricingDense Linear SystemsEngineeringAsset PricingComputational FinanceMethod Of Fundamental SolutionPde-constrained OptimizationNumerical ComputationDerivative PricingBusinessMulti-asset Option PricingSpatial DerivativesFinancial EngineeringRadial Basis FunctionApproximation TheoryNumerical Method For Partial Differential Equation
Numerical solution of the multi-dimensional partial differential equations arising in the modelling of option pricing is a challenging problem. Mesh-free methods using global radial basis functions (RBFs) have been successfully applied to several types of such problems. However, due to the dense linear systems that need to be solved, the computational cost grows rapidly with dimension. In this paper, we propose a numerical scheme to solve the Black–Scholes equation for valuation of options prices on several underlying assets. We use the derivatives of linear combinations of multiquadric RBFs to approximate the spatial derivatives and a straightforward finite difference to approximate the time derivative. The advantages of the scheme are that it does not require solving a full matrix at each time step and the algorithm is easy to implement. The accuracy of our scheme is demonstrated on a test problem.
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