The aim of the paper is the analysis of the sequential characteristics of the Athens Stock Exchange general index (ASE) using the time series metho-dology based on artificial intelligent techniques. The applied models include the Feed Forward Neural Network trained with the efficient Levenberg -...

This paper presents a comparison of various forecasting approaches, using time series analysis, on mean hourly wind speed data. In addition to the traditional linear (ARMA) models and the commonly used feed forward and recurrent neural networks, other approaches are also examined including the...

This paper presents a novel method for the forecasting of mean hourly wind speed data using time series analysis. The initial point for this approach is mainly the fact that none of the forecasting approaches for hourly data, that can be found in the literature, based on time series analysis or...

Under its Kyoto and EU obligations, Greece has committed to a greenhouse gas (GHG) emissions increase of at most 25% compared to 1990 levels, to be achieved during the period 2008-2012. Although this restriction was initially regarded as being realistic, information derived from GHG emissions...

The recent trend in estimating Value-at-Risk for modern and increasingly complex portfolios is the introduction of conditional models accounting for the heteroscedasticity of market risk factors. In this work, the introduction of complex methodologies is justified in relation to the dynamical...

This paper studies calendar effects in the emerging Athens Stock Exchange. Rather than examining only basket indices, we analyse calendar effects for each of the constituent stocks of the Athens Stock Exchange General Index for the period from October 1986 to April 1997. In accordance with...