On the efficiency of the gold market: Results of a real-time forecasting approach

Using a real-time forecasting approach, we study whether publicly available information on a large set of financial and macroeconomic variables help in forecasting out-of-sample monthly excess returns on investing in gold. The real-time forecasting approach accounts for the fact that an investor must reach an investment decision in real time under uncertainty concerning the optimal forecasting model. The real-time forecasting approach also accounts for the possibility that the optimal forecasting model may change overtime. We account for transaction costs and show that using forecasts implied by the real-time forecasting approach to set up a simple trading rule does not necessarily lead to a superior performance relative to a buy-and-hold strategy, implying that the gold market is informationally efficient with respect to the predictor variables that we study in this research. (C) 2014 Elsevier Inc. All rights reserved,