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A graphical model approach to simulating economic variables over long horizons

Published online by Cambridge University Press:  12 July 2019

Jaideep S. Oberoi ,
Aniketh Pittea  and
Pradip Tapadar Open the ORCID record for Pradip Tapadar [Opens in a new window]
Jaideep S. Oberoi
Affiliation:
Kent Business School, University of Kent, Canterbury CT2 7FS, UK
Aniketh Pittea
Affiliation:
School of Mathematics, Statistics and Actuarial Science, University of Kent, Canterbury CT2 7FS, UK
Pradip Tapadar*
Affiliation:
School of Mathematics, Statistics and Actuarial Science, University of Kent, Canterbury CT2 7FS, UK
*
*Corresponding author. Email: P.Tapadar@kent.ac.uk
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Abstract

We present an application of statistical graphical models to simulate economic variables for the purpose of risk calculations over long time horizons. We show that this approach is relatively easy to implement, and argue that it is appealing because of the transparent yet flexible means of achieving dimension reduction when many variables must be modelled. Using the United Kingdom data as an example, we demonstrate the development of an economic scenario generator that can be used by life insurance companies and pension funds.We compare different algorithms to select a graphical model, based on p-values, AIC, BIC and deviance. We find the economic scenario generator to yield reasonable results and relatively stable structures in our example, suggesting that it would be beneficial for actuaries to include graphical models in their toolkit.

Keywords

Graphical modelsscenario generatorsdimension reductionlong-term risk management
Type
Paper
Information
Annals of Actuarial Science , Volume 14 , Issue 1 , March 2020 , pp. 20 - 41
Copyright
© Institute and Faculty of Actuaries 2019 

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