Kernel Methods in Finance

Abstract

The first part of the present chapter provides some theoretical background and explains in the next section the general idea of kernel machines and kernelisation. Then the three fundamental machine learning paradigms dimensionality reduction, regression, and classification as well as associated questions of kernel and parameter selection are addressed. The chapter's second part gives a survey of typical questions and tasks arising in finance applications and how kernel methods have been applied to solve them. Finally follows a brief overview of relevant software toolboxes.