Li, Longqing (2017): A Comparative Study of GARCH and EVT Model in Modeling ValueatRisk. Published in: Journal of Applied Business and Economics , Vol. 19, No. 7 : pp. 2748.

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Abstract
The paper addresses an inefficiency of the traditional approach in modeling the tail risk, particularly the 1day ahead forecast of ValueatRisk (VaR), using Extreme Value Theory (EVT) and GARCH model. Specifically, I apply both models onto major countries stock markets daily loss, including U.S., U.K., China and Hong Kong between 2006 and 2015, and compare the relative forecasting performance. The paper differs from other studies in two important ways. First, it incorporates an asymmetric shock of volatility in the financial time series. Second, it applies a skewed fattailed return distribution using the Generalized Error Distribution (GED). The backtesting result shows that, on one hand, the conditional EVT performs equally well relative to GARCH model under the Generalized Error Distribution. On the other hand, the Exponential GARCH based model is the best performing one in ValueatRisk forecasting, because it not only correctly identifies the future extreme loss, but more importantly, its occurrence is independent.
Item Type:  MPRA Paper 

Original Title:  A Comparative Study of GARCH and EVT Model in Modeling ValueatRisk 
Language:  English 
Keywords:  ValueatRisk,Extreme Value Theory, Backtesting, Risk Forecasting 
Subjects:  C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C53  Forecasting and Prediction Methods ; Simulation Methods C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C58  Financial Econometrics G  Financial Economics > G3  Corporate Finance and Governance > G32  Financing Policy ; Financial Risk and Risk Management ; Capital and Ownership Structure ; Value of Firms ; Goodwill 
Item ID:  85645 
Depositing User:  Longqing Li 
Date Deposited:  02 Apr 2018 23:08 
Last Modified:  30 Sep 2019 10:14 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/85645 