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          Welcome to Serge, CEO France
          16/01/2023
          Detra Note 2023-1 | Risk management with Local Least Squares Monte-Carlo
          14/02/2023
          L&L March 2023 Cover EN
          Lunch & Learn | Risk management with Local Least Squares Monte-Carlo
          We are happy to invite you to participate in our next Lunch & Learn. This online session will take place on Tuesday, March 28, 2022 from 12:30 to 13:30 (UTC+1). It's FREE and OPEN to everyone.

          Accreditation : 1 CPD | 6 PPC

          It will be given in English by our Scientific Director, Donatien Hainaut and our TAP Consultant, Adnane Akbaraly

          This Lunch & Learn will present our Detra Note about the same topic.

          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 on risk factors. This article proposes a novel approach for this step, based on an a-priori 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.
          I'd like to participate!
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          Related posts

          27/02/2023

          21.03.2023 | Lunch & Learn | Gestion des risques avec les moindres carrés locaux et simulations de Monte-Carlo (FR)


          Read more
          14/02/2023

          Detra Note 2023-1 | Risk management with Local Least Squares Monte-Carlo


          Read more
          16/01/2023

          Welcome to Serge, CEO France


          Read more
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