Artikel
Estimating conditional value at risk in the Tehran stock exchange based on the extreme value theory using GARCH models
This paper attempted to calculate the market risk in the Tehran Stock Exchange by estimating the Conditional Value at Risk. Since the Conditional Value at Risk is a tail-related measure, Extreme Value Theory has been utilized to estimate the risk more accurately. Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models were used to model the volatility-clustering feature, and to estimate the parameters of the model, the Maximum Likelihood method was applied. The results of the study showed that in the estimation of model parameters, assuming T-student distribution function gave better results than the Normal distribution function. The Monte Carlo simulation method was used for backtesting the Conditional Value at Risk model, and in the end, the performance of different models, in the estimation of this measure, was compared.
- Sprache
-
Englisch
- Erschienen in
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Journal: Administrative Sciences ; ISSN: 2076-3387 ; Volume: 9 ; Year: 2019 ; Issue: 2 ; Pages: 1-17 ; Basel: MDPI
- Klassifikation
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Öffentliche Verwaltung
- Thema
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conditional value at risk
extreme value theory
GARCH models
backtesting models
maximum likelihood method
- Ereignis
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Geistige Schöpfung
- (wer)
-
Tabasi, Hamed
Yousefi, Vahidreza
Tamošaitienė, Jolanta
Ghasemi, Foroogh
- Ereignis
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Veröffentlichung
- (wer)
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MDPI
- (wo)
-
Basel
- (wann)
-
2019
- DOI
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doi:10.3390/admsci9020040
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:45 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Tabasi, Hamed
- Yousefi, Vahidreza
- Tamošaitienė, Jolanta
- Ghasemi, Foroogh
- MDPI
Entstanden
- 2019
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