Tourist demand is subject to considerable variations, a fact which aggravates the development of forecast models of sufficiently adequate accuracy. This study develops models that permit including most if not all factors of influence. To this end, due consideration was given to calendar effects...

This study uses time-series techniques and econometric approaches in order to quantify the effects that organising an EU presidency has on the tourism exports of a country. The approach to explain tourism revenues by a time-series intervention model filters out special effects (data...

This study uses time-series techniques and econometric approaches in order to quantify the effects that organising an EU presidency has on the tourism exports of a country. The approach to explain tourism revenues by a time-series intervention model filters out special effects (data...

Outlier detection in high-dimensional datasets poses new challenges that have not been investigated in the literature. In this paper, we present an integrated methodology for the identification of outliers which is suitable for datasets with higher number of variables than observations. Our...

We consider the detection of multiple outliers in Exponential and Pareto samples -- as well as general samples that have approximately Exponential or Pareto tails, thanks to Extreme Value Theory. It is shown that a simple "robust'' modification of common test statistics makes inward sequential...

We present a new procedure for detecting multiple additive outliers in GARCH(1,1) models at unknown dates. The outlier candidates are the observations with the largest standardized residual. First, a likelihood-ratio based test determines the presence and timing of an outlier. Next, a second...