A Comparison of Conditional and Unconditional VaR Models

Krzysztof Echaust , Małgorzata Just

Abstract

: This paper presents the empirical research on comparison of two different approaches for Value at Risk (VaR) measurement. The research objective is to compare the accuracy of out-of-sample VaR forecasts between conditional and unconditional models. We examine four unconditional models: Gaussian, alpha-stable, Normal Inverse Gaussian (NIG) and Generalized Pareto (GP) distributions and four conditional models: Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model with Gaussian and Student’s t innovations, Exponentially Weighted Moving Average (EWMA) and conditional Extreme Value Theory (GARCH-EVT) approach. Calculations are performed on the basis of 5 world indices, 4 exchange rates and 4 commodity futures and the results are presented for left and right distribution tails. Backtesting methods indicate the GARCH-EVT as the model that outperforms all others.
Author Krzysztof Echaust (WIiGE / KBO)
Krzysztof Echaust,,
- Department of Operations Research
, Małgorzata Just - Uniwersytet Przyrodniczy w Poznaniu, MNiSW [80]
Małgorzata Just,,
-
Pages124-135
Publication size in sheets0.55
Book Jedlička Pavel, Firlej Krzysztof, Marešová Petra, Soukal Ivan (eds.): Hradec Economic Days : Double-blind Peer Reviewed Proceedings of the International Scientific Conference Hradec Economic Days 2020, Hradec Economic Days, vol. 10, 2020, University of Hradec Králové, ISBN 9788074357763, 906 p.
Keywords in PolishVaR; rozkład stabilny; NIG; GPD; EVT; GARCH; EWMA; GARCH-EVT
Keywords in EnglishVaR; stable distribution; NIG; GPD; EVT; GARCH; EWMA; GARCH-EVT
DOIDOI:10.36689/uhk/hed/2020-01-014
URL http://hdl.handle.net/20.500.12603/215
Languageen angielski
Score (nominal)5
Score sourcepublisherList
ScoreMinisterial score = 5.0, 15-05-2020, ChapterFromConference
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