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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Hamed Tabasi & Vahidreza Yousefi & Jolanta Tamošaitienė & Foroogh Ghasemi, 2019. "Estimating Conditional Value at Risk in the Tehran Stock Exchange Based on the Extreme Value Theory Using GARCH Models," Administrative Sciences, MDPI, vol. 9(2), pages 1-17, May.
    • Handle: RePEc:gam:jadmsc:v:9:y:2019:i:2:p:40-:d:234128
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    References listed on IDEAS

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    2. Cristi Spulbar & Ramona Birau & Iqbal Thonse Hawaldar & Jatin Trivedi & Anca Ioana Iacob (Troto), 2023. "Measuring Asymmetric Volatility Of Uk, France, And German Stock Markets," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 1, pages 134-146, February.

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