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Star VaRs: Finding the Optimal Value-at-Risk Approach for the Banking Industry
Company: School of Economics and Management, Lund University
Company Url: Click here to open
Year Of Publication: 2009
Month Of Publication: May
Pages: 67
Download Count: 21
View Count: 1381
Comment Num: 0
Language: English
Source: thesis
Who Can Read: Free
Date: 7-10-2011
Publisher: Administrator
Summary
This paper explores the concept of Value-at-Risk (VaR) through a comparative study of nonparametric and parametric models in order to find the best risk model for banks’ trading portfolios. The models are estimated and tested on the S&P500 and a hypothetical bank trading portfolio. The evaluation of the models follows the Christoffersen framework of testing for correct conditional coverage together with assessment of model performance according to the regulatory requirements of the Basel Accord. The general finding is that models with leptokurtic features and time-varying volatility perform the best, while na?ve models assuming normality and/or without volatility dynamics in general display poor performance. The GARCH(1,1)-t model by far outperforms its competitors as it can correctly account for both correct unconditional coverage and volatility clustering. The implications of market risk regulation are explored and it is argued that the current regulatory environment might provide incentives for low-quality risk management practices with significant room for regulatory improvements.
Author(s)
Billinger, Olle Sign in to follow this author
Eriksson, Björn Sign in to follow this author
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