The method of least squares Monte-Carlo (LSMC) has become a standard in the insurance and financial sectors for computing the exposure of a company to market risk. The sensitive point of this procedure is the non-linear regression of simulated responses to risk factors. This article proposes a novel approach for this step, based on an apriori segmentation of responses. Using a K-means algorithm, we identify clusters of responses that are next locally regressed on corresponding risk factors. A global function of regression is obtained by combining local models and a logistic regression. The efficiency of the Local Least squares Monte-Carlo (LLSMC) is checked in two illustrations. The first one focuses on butterfly and bull trap options in a Heston stochastic volatility model. The second illustration analyzes the exposure to risks of a participating life insurance.
Sector: Insurance
Expertise: Assurance Vie
Authors: Adnane Akbaraly,
Donatien Hainaut
Publisher: Detralytics
Date: January 2023
Language: English
Pages: 34
Reference : Detra Note 2023-1
Adnane is part of the Talent Accelerator Program (TAP) at Detralytics. Prior to joining Detralytics, Adnane worked at CNP Assurances in retirement department and developed skills in Market Consistency Embedded Value (MCEV) assessment.
Having a strong appeal for Data Science applied to actuarial sciences, Adnane has developed technical skills during his experiences in Life and Non-Life. In addition, he had the opportunity to work on an R&D topic that was published in the ASTIN Bulletin.
Donatien Hainaut est Conseiller Scientifique chez Detralytics et Professeur à l’UCLouvain (Belgique), où il dirige le Master en Data Science à orientation statistique. Auparavant, il a occupé plusieurs postes académiques, notamment en tant que Professeur Associé à la Rennes School of Business et à l’ENSAE à Paris. Il possède également une solide expérience en entreprise, ayant travaillé comme Risk Officer, Quantitative Analyst et ALM Officer.
Actuaire qualifié et titulaire d’un doctorat en Asset and Liability Management, ses recherches actuelles portent sur les mécanismes de contagion dans les processus stochastiques ainsi que sur les applications des réseaux de neurones en assurance.
