Estimating Conditional Value at Risk in the Tehran Stock Exchange Based on the Extreme Value Theory Using GARCH Models

Hamed Tabasi, Vahidreza Yousefi, Jolanta Tamošaitienė and Foroogh Ghasemi
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Hamed Tabasi: Finance Department, University of Tehran, Tehran 1417614418, Iran
Vahidreza Yousefi: Construction and Project Management, University of Tehran, Tehran 1417614418, Iran
Jolanta Tamošaitienė: Institute of Sustainable Construction, Faculty of Civil Engineering, Vilnius Gediminas Technical University, Sauletekio Ave. 11, Vilnius LT-10223, Lithuania
Foroogh Ghasemi: Project and Construction Management, University of Art, Tehran 1136813518, Iran

Administrative Sciences, 2019, vol. 9, issue 2, 1-17

Abstract: 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.

Keywords: conditional value at risk; extreme value theory; GARCH models; backtesting models; maximum likelihood method (search for similar items in EconPapers)
JEL-codes: L M M0 M1 M10 M11 M12 M14 M15 M16 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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