The paper presents examples of application of error correction models (ECM) in forecasting daily changes of market volatility recorded on currency options markets in Poland, Hungary and South Africa. The models are based on the observed correlation between daily changes of spot rates and daily...

This study analyses point forecasts of exact scoreline outcomes for football matches in the English Premier League. These forecasts were made for distinct competitions and originally judged differently. We compare these with implied probability forecasts using bookmaker odds and a crowd of...

In this paper, we examine the usefulness of Google Trends data in predicting monthly tourist arrivals and overnight stays in Prague during the period between January 2010 and December 2016. We offer two contributions. First, we analyze whether Google Trends provides significant forecasting...

In this study, we treat the seasonal variation in monthly time series in the context of the Western-European tourism demand for Tunisia, by presenting different techniques of detection of seasonality and the parametric and non-parametric approaches of seasonal adjustment. Then, we compare the...

The paper makes an attempt to provide estimation of foreign tourism demand by 2014, by investigating the case of Macedonia. The author applies the Box-Jenkins methodology and tests several alternative specifications in the modeling of original time series. Upon the outcomes of standard...

This paper improves short-term forecasting models of monthly tourism arrivals by estimating and evaluating a time-series model with exogenous regressors (ARIMA-X) using a case of Aruba, a small open tourism-dependent economy. Given importance of the US market for Aruba, it investigates...

This paper aims to compare the performance of different Artificial Neural Networks techniques for tourist demand forecasting. We test the forecasting accuracy of three different types of architectures: a multi-layer perceptron, a radial basis function and an Elman network. We also evaluate the...

It has been established in the economics literature that competitive outcomes can be well predicted by the aggregate salaries of the contesting participants. In this paper we use this idea to construct a forecast test to evaluate a novel, and hitherto unevaluated source of wage data. If the...

The present study investigates the performance of the k nearest neighbor (kNN) forecasts in the context of European tourism demand. The forecasting performance of neural networks is examined across different parameterizations of the kNN model. The selection of the most appropriate kNN...