Applications of Kernel Methods in Financial Risk Management

Andreas Mitschele (), Stephan Chalup, Frank Schlottmann and Detlef Seese
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Andreas Mitschele: Institute AIFB University of Karlsruhe (TH), Germany
Stephan Chalup: University of Newcastle, Australia
Frank Schlottmann: GILLARDON AG financial software, Bretten, Germany
Detlef Seese: Institute AIFB University of Karlsruhe (TH), Germany

No 317, Computing in Economics and Finance 2006 from Society for Computational Economics

Abstract: Since their introduction Kernel Methods have proven their superior performance in many different application areas. Recently these algorithms have also been employed for different tasks in the area of finance. In this contribution we present an introduction to the methodology and give an overview of successful applications in finance. Subsequently two promising areas for the use of these advanced statistical learning methods are introduced, namely integrated risk management and parameter estimation in the Basel II capital accord context. Integrated risk management is concerned with the simultaneous consideration of the major sources of risk and return for today’s financial institutions. While risk measurement is typically still performed using isolated and substantially different quantitative models per risk category, we describe a novel approach based on Support Vector Machines (SVMs). Through training the SVM learns the implicit relation between different risk types. The Loss Given Default (LGD) represents a parameter to be estimated by banks when using internal rating based approaches within their Basel II implementation. Real-world applications indicate that linear relations between the input values may fail to describe the parameter output. We have used SVMs with varying kernels and obtained rather reliable estimates for the LGD compared to standard methods

Keywords: financial risk management; Basel II; parameter estimation; kernel methods; support vector machines (search for similar items in EconPapers)
JEL-codes: C45 G18 G21 (search for similar items in EconPapers)
Date: 2006-07-04
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Persistent link: https://EconPapers.repec.org/RePEc:sce:scecfa:317

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