Fast remote but not extreme quantiles with multiple factors. Applications to Solvency II and Enterprise Risk Management
For operational purposes, in Enterprise Risk Management or in insurance for example, it may be important to estimate remote (but not extreme) quantiles of some function ƒ of some random vector. The call to ƒ may be time- and resource-consuming so that one aims at reducing as much as possible the number of calls to ƒ. In this paper, we propose some ways to address this problem of general interest. We then numerically analyze the performance of the method on insurance and Enterprise Risk Management real-world case studies.
|Date of creation:||2011|
|Date of revision:|
|Publication status:||Published in European Actuarial Journal, 2011, 1 (1), pp.131-157|
|Note:||View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-00517766v2|
|Contact details of provider:|| Web page: https://hal.archives-ouvertes.fr/|
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- Laurent Devineau & Stéphane Loisel, 2009. "Risk aggregation in Solvency II: How to converge the approaches of the internal models and those of the standard formula?," Post-Print hal-00403662, HAL.
- Michael B. Gordy & Sandeep Juneja, 2008.
"Nested simulation in portfolio risk measurement,"
Finance and Economics Discussion Series
2008-21, Board of Governors of the Federal Reserve System (U.S.).
- Laurent Devineau & Stéphane Loisel, 2009. "Construction d'un algorithme d'accélération de la méthode des «simulations dans les simulations» pour le calcul du capital économique Solvabilité II," Post-Print hal-00365363, HAL.
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