On the conditional value at risk based on the laplace distribution with application in GARCH model

Document Type

Article

Publication Date

8-1-2022

Abstract

In this article, the Laplace distribution is employed in lieu of the well-known normal distribution for finding better scalar values of risk. Explicit formulas for value-at-risk (VaR) and conditional value-at-risk (CVaR) are studied and used to manage the risk involved in a stock movement by using the GARCH model. Numerical simulations are given for a variety of stocks in equity markets to uphold the findings.

Keywords

Risk measure, Stock market, Laplace distribution, Non-normality, Fat-tail

Funders

Ministry of Education,Deanship of Scientific Research (DSR), King Abdulaziz University (KAU), Jeddah, Saudi Arabia [IFPDP-253-22]

Publication Title

Mathematics

Volume

10

Issue

16

Publisher

MDPI

Publisher Location

ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND

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