Machine Learning Techniques for Mortality Modeling

16 Pages Posted: 23 Feb 2017

See all articles by Philippe Deprez

Philippe Deprez

ETH Zurich - Department of Mathematics

Pavel V. Shevchenko

Macquarie University; Macquarie University, Macquarie Business School

Mario V. Wuthrich

RiskLab, ETH Zurich

Date Written: February 20, 2017

Abstract

Various stochastic models have been proposed to estimate mortality rates. In this paper we illustrate how machine learning techniques allow us to analyze the quality of such mortality models. In addition, we present how these techniques can be used for differentiating the different causes of death in mortality modeling.

Keywords: mortality modeling, cause-of-death mortality, machine learning, boosting, regression

JEL Classification: G22, G28, C13, C14

Suggested Citation

Deprez, Philippe and Shevchenko, Pavel V. and Wuthrich, Mario V., Machine Learning Techniques for Mortality Modeling (February 20, 2017). Available at SSRN: https://ssrn.com/abstract=2921841 or http://dx.doi.org/10.2139/ssrn.2921841

Philippe Deprez

ETH Zurich - Department of Mathematics ( email )

Raemistrasse 101
Zurich, 8092
Switzerland

Pavel V. Shevchenko

Macquarie University ( email )

North Ryde
Sydney, New South Wales 2109
Australia

HOME PAGE: http://www.businessandeconomics.mq.edu.au/contact_the_faculty/all_fbe_staff/pavel_shevchenko

Macquarie University, Macquarie Business School ( email )

New South Wales 2109
Australia

Mario V. Wuthrich (Contact Author)

RiskLab, ETH Zurich ( email )

Department of Mathematics
Ramistrasse 101
Zurich, 8092
Switzerland

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