Abstract The automated Neural Network Autoregressive (NNAR) algorithm from the forecast
package in R generates sub-optimal forecasts when faced with seasonal tourism demand …

This paper considers how well the approach of combining forecasts extends to the context of
electricity prices. With the increasing popularity of regime switching and time-varying …

The electricity price forecasting (EPF) is essential for decision-making mechanisms of
market participants to survive in the deregulated and competing commercial environment …

The usefulness of a predictor evaluation framework which combines a blocked cross-
validation scheme with directional accuracy measures is investigated. The advantage of …

This article seeks to evaluate the appropriateness of a variety of existing forecasting
techniques (17 methods) at providing accurate and statistically significant forecasts for gold …

International Finance presents the corporate uses of international financial markets to upper
undergraduate and graduate students of business finance and financial economics …

We examine the unemployment hysteresis hypothesis for 31 European countries, the USA
and Japan, using alternative linear and nonlinear unit root tests, taking into account possible …

This paper is aimed at introducing the powerful, nonparametric time series analysis and
forecasting technique of Singular Spectrum Analysis (SSA) for trade forecasting via an …

In this paper, an optimized multivariate singular spectrum analysis (MSSA) approach is
proposed to find leading indicators of cross‐industry relations between 24 monthly …

This study aims to forecast the exchange rate by a combination of different models as
proposed by Poon and Granger (2003). For this purpose, we include three univariate time …