We analyzed six stock exchange markets through the nonlinear dynamics concept. We used daily data from the Toronto Stock Exchange, NYSE, London Stock Exchange, Hong Kong Stock Market, Tokyo Stock Exchange, and the Singapore Stock Exchange. The period studied is from January 1, 1988 to June 30,...

Several recently developed chaotic forecasting methods give better results than the random walk forecasts. However they do not take into account specific regularities of stock returns reported in empirical finance literature, such as the calendar effects. In this paper, we present a method for...

A method is presented that takes into account the day-of-the-week and the turn-of-the-month effect and the holiday effect and embodies them to neural network forecasting. It adjusts the time series in order to make its dynamics less distorted. After a predicted value is calculated by the...

We propose the use of simulation in order to obtain a statistical significance measure of the least median of squares (LMS) regression coefficients. We shuffle the values of the dependent variable many times (e.g. 100), so as to preserve their distribution, and we calculate the LMS regression...

Surrogate Data Analysis (SDA) is a statistical hypothesis testing framework for the determination of weak chaos in time series dynamics. Existing SDA procedures do not account properly for the rich structures observed in stock return sequences, attributed to the presence of heteroscedasticity,...

In this work we propose the use of simulation for the solution of the Cronbach's alpha statistical significance problem. This coefficient measures the reliability of a questionnaire's answers. Many analytical tests have been developed over the years which gave birth to very complicated formulas...

Surrogate data analysis (SDA) is a statistical hypothesis testing framework for the determination of weak chaos in time series dynamics. Existing SDA procedures do not account properly for the rich structures observed in stock return sequences, attributed to the presence of heteroscedasticity,...

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...

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 -...