On the wavelet-based SWIFT method for backward stochastic differential equations

We propose a numerical algorithm for backward stochastic differential equations based on time discretization and trigonometric wavelets. This method combines the effectiveness of Fourier-based methods and the simplicity of a wavelet-based formula, resulting in an algorithm that is both accurate and easy to implement. Furthermore, we mitigate...

On the Application of Shannon Wavelet Inverse Fourier Techniques: An Extension to Asian Option Valuation and European Option Pricing under the SABR Model

This work is on the extension of the SWIFT method to option pricing problems where the sum of lognormals occurs. The SWIFT method (ShannonWavelet Inverse Fourier Technique) is extended to the valuation of geometric Asian options and arithmetic Asian options with a Lévy process as underlying price process and the valuation of European options...

A Highly Efficient Shannon Wavelet Inverse Fourier Technique for Pricing European Options

In the search for robust, accurate, and highly efficient financial option valuation techniques, we here present the SWIFT method (Shannon wavelets inverse Fourier technique), based on Shannon wavelets. SWIFT comes with control over approximation errors made by means of sharp quantitative error bounds. The nature of the local Shannon wavelets...

Numerical Pricing of Bermudan Options with Shannon Wavelet Expansions

This thesis is about pricing Bermudan options with the SWIFT method (Shannon Wavelets Inverse Fourier Technique). We reformulate the SWIFT pricing formula for European options to improve robustness, which allows us to heuristically select - and test the goodness - of all of the parameters a priori. Furthermore, we propose a simplified version of...