Abstract
A quasi-stylized fact in the literature is that gold is a safe haven for investors when there is turbulence in the financial markets. Although investing in gold is not new, the relevant literature fails to reach a consensus regarding the forces that drive gold prices or a universally accepted forecasting model that can be used in the evaluation of asset allocation in gold portfolios. In this paper, we depart from the typical econometric approaches in the field and re-evaluate gold forecasting using a hybrid method. The proposed model is based on short- and long-run decomposition of input variables using the Ensemble Empirical Mode Decomposition algorithm and forecasting each component separately based on the Support Vector Regression method. Compared to previous methods in the field, our empirical findings suggest that the proposed method significantly increases the economic returns of a trading strategy based on the forecasts of the proposed scheme.
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