List of Articles Generalized Extreme Value Distribution

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  1 - Estimation value at risk (VAR) and conditional value at risk (CoVaR) at Tehran Stock Exchange by approach to using Fréchet distribution (FD)
  Azadeh Meharani Ali Najafi moghadam Ali baghani
  Risk estimation cannot deliver appropriate reliable predictions by focusing on one or two models and considering the irrelevant factors. This study aims to estimate the value at risk (VAR) and the conditional value at risk (CoVaR) in the Tehran Stock Exchange using Fr&e More

  Risk estimation cannot deliver appropriate reliable predictions by focusing on one or two models and considering the irrelevant factors. This study aims to estimate the value at risk (VAR) and the conditional value at risk (CoVaR) in the Tehran Stock Exchange using Fréchet distribution (FD). In doing so, generalized extreme value (GEV) is used with the help of Friche distribution approach. In this study, the return of 21-day and 63-day data of the time series of the total index, free-float-stock index, and index of 50 active companies of Tehran Stock Exchange during 01/01/2012 to 12/29/1398 have been used. The obtained results through the estimation of three parameters of GEV, including location, scale, and shape, have shown that the parameter of distribution shape within all 21 and 63-day periods of each indicator is positive, and the distribution for indexes studied follows FD as the second type of generalized distribution of GEV. By using the same pattern, the measurement of CoVaR and VaR has presented that it is possible to estimate CoVar and VaR through the use of FD and CoVaR is higher than VaR within the whole range of alpha. Manuscript profile
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  2 - Estimating Extreme downside risk premium using Extreme Value Theory Approach
  Maryam Davallou Mahdiyeh Dashti
  Recent year’s financial crisis gives rise to pay attention to extreme losses. Investors suffer from extreme losses and since unusaull outcomes probability is not far, investors concern about extreme tail of return distribution. This paper is aimed to examin extrem More

  Recent year’s financial crisis gives rise to pay attention to extreme losses. Investors suffer from extreme losses and since unusaull outcomes probability is not far, investors concern about extreme tail of return distribution. This paper is aimed to examin extreme downside risk (EDR) that is calculated by extreme value theory (EVT) which is designed to explain uncommon events. For this purpose, a sample composed of 243 listed firms in Tehran Stock Exchange is examined for 1384 to 1394. Portfolio study approach and Fama- McBeth (1973) regression are used to EDR pricing test. The results confirm EDR pricing and statistical significancy of extreme downside risk in TSE. This research shows that potential loss from extreme downside returns, EDR, is captured by asset pricing as a risk factor. Also, the effects of other risk measures including volatility, valu at risk and right tail mesure are stronger than EDR and if their effectes is controlled, EDR risk premium is no longer statistically significant.  Manuscript profile