We study the out-of-sample predictability of the real price of crude oil using forecast combinations constructed from several individual predictors. We find that forecasts of themonthly average price of oil are more accurate than the no-change forecast at horizons ranging from 1 to 24 months...

This article defines the Autoregressive Fractional Unit Root Integrated Moving Average (ARFURIMA) model for modelling ILM time series with fractional difference value in the interval of 1൏𝑑൏2. The performance of the ARFURIMA model is examined through a Monte Carlo simulation. Also, some...

We develop methods to obtain optimal forecast under long memory in the presence of a discrete structural break based on different weighting schemes for the observations. We observe significant changes in the forecasts when long-range dependence is taken into account. Using Monte Carlo...

This paper investigated the relationship between cryptocurrencies and emerging stock market indices using fractional integration and co-integration technique. Particularly, fractional integration is applied to examine stochastic properties of individual assets and fractional cointegration to...

Background: Decision makers use the process of determining the best course of action by processing, analysing & interpreting the data to gain insights, known as Business Intelligence. Some decision support systems use sales figures to predict future expansion, but few consider the effect of...