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Signature-based validation of real-world economic scenarios

Published online by Cambridge University Press:  04 April 2024

Hervé Andrès Open the ORCID record for Hervé Andrès [Opens in a new window] ,
Alexandre Boumezoued  and
Benjamin Jourdain
Hervé Andrès*
Affiliation:
Milliman R&D, Paris, France CERMICS, Ecole des Ponts, INRIA, Marne-la-Vallée, France
Alexandre Boumezoued
Affiliation:
Milliman R&D, Paris, France
Benjamin Jourdain
Affiliation:
CERMICS, Ecole des Ponts, INRIA, Marne-la-Vallée, France
*
Corresponding author: Hervé Andrès; Email: herve.andres@milliman.com
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Abstract

Motivated by insurance applications, we propose a new approach for the validation of real-world economic scenarios. This approach is based on the statistical test developed by Chevyrev and Oberhauser ((2022) Journal of Machine Learning Research, 23(176), 1–42.) and relies on the notions of signature and maximum mean distance. This test allows to check whether two samples of stochastic processes paths come from the same distribution. Our contribution is to apply this test to a variety of stochastic processes exhibiting different pathwise properties (Hölder regularity, autocorrelation, and regime switches) and which are relevant for the modelling of stock prices and stock volatility as well as of inflation in view of actuarial applications.

Keywords

Real-world economic scenarioseconomic scenarios validationinsurancesignaturemaximum mean distance

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Type
Research Article
Information
ASTIN Bulletin: The Journal of the IAA , Volume 54 , Issue 2 , May 2024 , pp. 410 - 440
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of The International Actuarial Association

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