Academic Journal

On the Use of Lehmann's Alternative to Capture Extreme Losses in Actuarial Science.

Bibliographic Details
Title: On the Use of Lehmann's Alternative to Capture Extreme Losses in Actuarial Science.
Authors: Gómez-Déniz, Emilio1 (AUTHOR) emilio.gomez-deniz@ulpgc.es, Calderín-Ojeda, Enrique2 (AUTHOR) enrique.calderin@unimelb.edu.au
Superior Title: Risks. Jan2024, Vol. 12 Issue 1, p6. 22p.
Subject Terms: ACTUARIAL science, CUMULATIVE distribution function, CONTINUOUS distributions
Abstract: This paper studies properties and applications related to the mixture of the class of distributions built by the Lehmann's alternative (also referred to in the statistical literature as max-stable or exponentiated distribution) of the form [ G (·) ] λ , where λ > 0 and G (·) is a continuous cumulative distribution function. This mixture can be useful in economics, financial, and actuarial fields, where extreme and long tails appear in the empirical data. The special case in which G (·) is the Stoppa cumulative distribution function, which is a good description of the random behaviour of large losses, is studied in detail. We provide properties of this mixture, mainly related to the analysis of the tail of the distribution that makes it a candidate for fitting actuarial data with extreme observations. Inference procedures are discussed and applications to three well-known datasets are shown. [ABSTRACT FROM AUTHOR]
Copyright of Risks is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Business Source Premier
Description
Description not available.