Extreme Value Theory (EVT) methods are used to investigate the asymptotic distribution of the lower tail for daily returns in the Athens Stock Exchange (ASE) over the period 1986 to 2001. Overall, the Generalised Logistic (GL) distribution is found to provide adequate descriptions of the...

Extreme Value Theory methods are used to investigate the distribution of the extreme minima in the German stock market over the period 1973 to 2001. Innovative aspects of this paper include (i) a wide set of distributions considered, (ii) L-moment diagrams employed to identify the most...

With the objective of investigating the hydrological homogeneity of India's hydrometeorological subzone 3-a and identification of a suitable frequency distribution for it, a regional flood frequency analysis has been carried out using the index flood procedure and the L-moments. Based on...

In this study, a regional flood frequency analysis has been carried out, using the index flood L-moments approach. Annual maximum stream flood data observed at 14 gauged sites on the Nile River tributaries (Blue Nile, White Nile, and Atbara River) are investigated. The aim of the study is to...

During the past decades, seasonal autoregressive integrated moving average (SARIMA) had become one of a prevalent linear models in time series and forecasting. Empirical research advocated that forecasting with non-linear models can be an encouraging alternative to traditional linear models....

During the past decades, seasonal autoregressive integrated moving average (SARIMA) had become one of a prevalent linear models in time series and forecasting. Empirical research advocated that forecasting with non-linear models can be an encouraging alternative to traditional linear models....

This paper seeks to characterise the distribution of extreme returns for a UK share index over the years 1975 to 2000. In particular, the suitability of the following distributions is investigated: Gumbel, Frechet, Weibull, Generalised Extreme Value, Generalised Pareto, Log-Normal and...