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An extreme value theory under exponential normalization: A study based on CAC 40 index
Abstract
Extensive research has focused on estimating return levels in extreme value theory (EVT) using exponential normalization. In this work, we introduce a theoretical framework based on the Von Mises function to estimate return levels under nonlinear normalization. To assess the reliability of return level estimation for the generalized extreme value (GEV) distribution under exponential normalization, we implement an algorithm and conduct an empirical study using data from the CAC 40 stock index.
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