Economic theory predicts that, in a small open economy, the dynamics of the real price of gold should be linked to real interest rates and the rate of change of the real exchange rate. Using data for Australia, we use a real-time forecasting approach to analyze whether real interest rates and...

We use Bayesian additive regression trees (BART) to reexamine whether investments in precious metals are a hedge against exchange-rate movements. We control for the influence of stock-market fluctuations and other factors, we quantify the relative importance of several major exchange rates, and...

Economic theory predicts that, in a small open economy, the dynamics of the real price of a commodity should be linked to a large-country real interest rate and fluctuations of the real exchange rate. Using data for Australia, we test this prediction using an out-ofsample forecasting experiment....

We use a boosting approach to study the time-varying out-of-sample informational content of various financial and macroeconomic variables for forecasting the volatility of gold-price fluctuations. We use an out-of-sample R2 statistic to evaluate forecasts as a function of the shape of a...

Economic theory predicts that, in a small open economy, the dynamics of the real price of gold should be linked to real interest rates and the rate of change of the real exchange rate. Using data for Australia, we use a real-time forecasting approach to analyze whether real interest rates and...

Economic theory predicts that, in a small open economy, the dynamics of the real price of gold should be linked to real interest rates and the rate of change of the real exchange rate. Using data for Australia, we use a real-time forecasting approach to analyze whether real interest rates and...

We use multivariate random forests to compute out-of-sample forecasts of a vector of returns of four precious metal prices (gold, silver, platinum, and palladium). We compare the multivariate forecasts with univariate out-of-sample forecasts implied by random forests independently fitted to...

We use a machine-learning algorithm known as boosted regression trees (BRT) to implement an orthogonality test of the rationality of aggregate stock-market forecasts. The BRT algorithm endogenously selects the predictor variables used to proxy the information set of forecasters so as to maximize...