Forecasting excess returns of the gold market: Can we learn from stock market predictions?

As some recent studies have shown empirically, future gold price fluctuations are especially difficult to forecast. Against this background, this study evaluates the forecasting power of three approaches that have been applied successfully in a stock market prediction context: 1) technical indicators, 2) diffusion indices, and 3) economically motivated restrictions in predictive regressions. The results are evaluated using statistical and economic evaluation criteria over the entire data sample, as well as separately for expansive and recessive business cycles. We observe that none of the three prediction techniques leads to better forecasts of gold excess returns. The forecast power of fundamental predictor variables is not only highly regime-dependent, but also dependent on the selected economic evaluation criterion. Future gold forecast studies should address these issues.