Since Fama's Efficient Market Hypothesis (EMH), numerous authors have argued that it is impossible to constantly beat the market. The best an investor can do is buy and hold 'the market' through a market index. Taking into account the important role of market indices as benchmarks against which...

Since the early days of Dow Jones Averages indexing has raised complexity. The lack of standard theoretical framework for index building, and the heterogeneity of empirical studies regarding their statistical properties, make comparisons an issue. The scenario remains the same in...

Purpose – This study aims to apply a new forecasting approach to improve predictions in the hospitality industry. To do so, the authors developed a multivariate setting that allows the incorporation of the cross-correlations in the evolution of tourist arrivals from visitor markets to a...

This study employs different nonlinear models (smooth transition autoregressive models (STAR), artificial neural networks (ANN) and nearest neighbours (NN)) to study the predictability of one-step-ahead forecast returns for the Ibex35 stock future index at a one year forecast horizon. It is...

This study attempts to improve the forecasting accuracy of tourism demand by using the existing common trends in tourist arrivals form all visitor markets to a specific destination in a multiple-input multiple-output (MIMO) structure. While most tourism forecasting research focuses on univariate...

This study aims to analyze the effects of data pre-processing on the performance of forecasting based on neural network models. We use three different Artificial Neural Networks techniques to forecast tourist demand: a multi-layer perceptron, a radial basis function and an Elman neural network....