AN APPLICATION OF EXTREME VALUE THEORY IN MODELLING EXTREME SHARE RETURNS
Konstantinos Tolikas
Abstract
Open-access reader
Konstantinos Tolikas
Abstract
Open-access reader
Extreme value theory (EVT) methods are used to investigate the asymptotic distribution/s of the extreme minima and maxima of the Athens Stock Exchange daily returns over the period 1976-2001.Innovative aspects of this study include: (1) the generalized extreme value and generalized logistic distributions are considered, (2) Lmomentsratio diagrams are used to identify the distribution/s most likely to fit the extreme daily returns adequately, (3) the probability weighted moments method is used to estimate the parameters of the distribution/s, and (4) the Anderson-Darling goodness of fit test is employed to test the adequacy of fit.The generalized logistic distribution is found to provide adequate descriptions of the behavior of both the extreme minima and maxima over the period studied; however, the asymptotic distributions of extremes appear to become less fat tailed over time implying that the probability of a large daily return occurring is decreasing.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Extreme value theory (EVT) methods are used to investigate the asymptotic distribution/s of the extreme minima and maxima of the Athens Stock Exchange daily returns over the period 1976-2001.Innovative aspects of this study include: (1) the generalized extreme value and generalized logistic distributions are considered, (2) Lmomentsratio diagrams are used to identify the distribution/s most likely to fit the extreme daily returns adequately, (3) the probability weighted moments method is used to estimate the parameters of the distribution/s, and (4) the Anderson-Darling goodness of fit test is employed to test the adequacy of fit.The generalized logistic distribution is found to provide adequate descriptions of the behavior of both the extreme minima and maxima over the period studied; however, the asymptotic distributions of extremes appear to become less fat tailed over time implying that the probability of a large daily return occurring is decreasing.
Key concepts: Extreme value theory, Value (mathematics), Econometrics, Mathematics, Computer science, Statistics