How to Deal with Small Data Sets in Machine Learning: An Analysis on the CAT Bond Market

28 Pages Posted: 26 Feb 2020

See all articles by Tobias Götze

Tobias Götze

Technische Universität Braunschweig - Institute of Finance

Marc Gürtler

University of Braunschweig - Institute of Technology, Department of Finance

Eileen Witowski

Technische Universität Braunschweig - Institute of Finance

Date Written: January 30, 2020

Abstract

This study compares state-of-the-art regression-based models to machine learning methods in terms of forecasting performance in asset pricing on a small data set. The performance comparison is conducted on the market for CAT bonds, where we use a large sample of CAT bond issues to forecast risk premia. First, we evaluate the performance of regression models based on the literature. We then test whether the accuracy of those models can be improved through different variable selection algorithms or penalization methods. Afterwards, we use the machine learning methods random forest and neural networks to forecast CAT bond premia. We obtain three main results. First, the application of selection and penalization methods to linear regression models yields only minor differences in forecasting performance. Second, random forest outperforms regression models in terms of forecasting performance. Third, machine learning methods perform quite well on a relatively small data set.

Keywords: CAT bonds, meachine learning, regression, risk premium

JEL Classification: C45, C58, G12, G17, G22

Suggested Citation

Götze, Tobias and Gürtler, Marc and Witowski, Eileen, How to Deal with Small Data Sets in Machine Learning: An Analysis on the CAT Bond Market (January 30, 2020). Available at SSRN: https://ssrn.com/abstract=3528082 or http://dx.doi.org/10.2139/ssrn.3528082

Tobias Götze

Technische Universität Braunschweig - Institute of Finance ( email )

Abt-Jerusalem-Str. 7
Braunschweig, 38106
Germany
00495313912893 (Phone)
00495313912899 (Fax)

Marc Gürtler

University of Braunschweig - Institute of Technology, Department of Finance ( email )

Abt-Jerusalem-Str. 7
Braunschweig, 38106
Germany

Eileen Witowski (Contact Author)

Technische Universität Braunschweig - Institute of Finance ( email )

Abt-Jerusalem-Str. 7
Braunschweig, 38106
Germany

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