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

Administrative Sciences

Vahidreza Yousefi¹  Hamed Tabasi²  Jolanta Tamošaitienė³  Foroogh Ghasemi⁴ 

[1] Construction and Project Management, University of Tehran, Tehran 1417614418, Iran;Department of Chemical Engineering, University of Tehran, Tehran 1417614418, Iran;Institute of Sustainable Construction, Faculty of Civil Engineering, Vilnius Gediminas Technical University, Sauletekio Ave. 11, Vilnius LT-10223, Lithuania;Project and Construction Management, University of Art, Tehran 1136813518, Iran;

关键词: conditional value at risk;    extreme value theory;    GARCH models;    backtesting models;    maximum likelihood method;   

DOI  :  10.3390/admsci9020040

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown