Reduction of Computing Time for Numerical Pricing of European Multi-dimensional Options based on the COS Method

Numerical integration methods such as the Fourier-based COS method can be used for effciently and accurately pricing financial products. The COS method can be applied to options on one underlying stock as well as on multiple underlying stocks. However, this method suffers from an exponential increase in computational complexity as the dimensions increase. In this thesis we research how to reduce the computational time, especially for multi-dimensional options. Firstly, we discuss the COS method. Secondly, we program this method in three different languages, namely MATLAB, C and CUDA. Thirdly, we perform numerical tests: MATLAB- and C-code on a CPU and CUDA-code on a GPU. Lastly, we compare some options for the different computing times of these codes.Computational FinanceNumerical AnalysisElectrical Engineering, Mathematics and Computer Scienc