Assessing the probability of rare and extreme events is an important issue in the risk management of financial portfolios. Extreme value theory provides the solid fundamentals needed for the statistical modeling of such events and the computation of extreme risk measures. The focus of this paper is on the use of extreme value theory to compute value at risk. The performance of the extreme value theory in value-at-risk calculations is compared to the performances of conventional methodologies (historical simulation and variance–covariance with normal distribution) in Tehran Stock Exchange. In the case studied, we found that for the right tail, which is heavier than the left tail, the EVT based VaR is the best method in all confidence levels, but for the left tail it is the most accurate at the highest quintile.
Eslami Bidgoli,S , zamani,S and kazemi,M . (2013). Measuring Value at Risk of Tehran Stock Exchange Index: Using Extreme Value Theory. Quarterly Journal of Securities Exchange, 6(21), 115-136.
MLA
Eslami Bidgoli,S , , zamani,S , and kazemi,M . "Measuring Value at Risk of Tehran Stock Exchange Index: Using Extreme Value Theory", Quarterly Journal of Securities Exchange, 6, 21, 2013, 115-136.
HARVARD
Eslami Bidgoli S, zamani S, kazemi M. (2013). 'Measuring Value at Risk of Tehran Stock Exchange Index: Using Extreme Value Theory', Quarterly Journal of Securities Exchange, 6(21), pp. 115-136.
CHICAGO
S Eslami Bidgoli, S zamani and M kazemi, "Measuring Value at Risk of Tehran Stock Exchange Index: Using Extreme Value Theory," Quarterly Journal of Securities Exchange, 6 21 (2013): 115-136,
VANCOUVER
Eslami Bidgoli S, zamani S, kazemi M. Measuring Value at Risk of Tehran Stock Exchange Index: Using Extreme Value Theory. Quarterly Journal of Securities Exchange. 2013;6(21):115-136 (In Persian).
