Robust Estimation of Value-at-Risk through Distribution-Free and Parametric Approaches Using the Joint Severity and Frequency Model: Applications in Financial, Actuarial, and Natural Calamities Domains

Robust Estimation of Value-at-Risk through Distribution-Free and Parametric Approaches Using the Joint Severity and Frequency Model: Applications in Financial, Actuarial, and Natural Calamities Domains

Value-at-Risk (VaR) is a well-accepted risk metric in modern quantitative risk management (QRM). The classical Monte Carlo simulation (MCS) approach, denoted henceforth as the classical approach, assumes the independence of loss severity and loss frequency. In practice, this assumption does not alwa...

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Bibliographic Details
Main Authors: Sabyasachi Guharay, KC Chang, Jie Xu
Format: Article
Language:English
Published: MDPI AG 2017-07-01
Series:Risks
Subjects:
risk management
simulation
copula
loss severity modeling
Value-at-Risk
Online Access:https://www.mdpi.com/2227-9091/5/3/41

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