, inflation expectations, exchange rate changes and stock market volatility among others. Hence, forecasting the price of gold is …The price of gold is influenced by a wide range of local and global factors such as commodity prices, interest rates … allows both the forecasting model and the coefficients to change over time. Based on this framework, we systematically …

reversion and assume that relative prices are unchanged. Direct forecasting or panel data techniques are better than the random …

forecasting volatility. We outline the genesis of this approach from similar models of turbulent flows in statistical physics and …

competing models. We show that the forecasting gains translate into economically and statistically significant (risk …

competing models. We show that the forecasting gains translate into economically and statistically significant (risk …

results shows the rolling ward networks exceed the recursive ward networks and feed forward networks in forecasting gold price …This paper analyzes recursive and rolling neural network models to forecast one-step-ahead sign variations in gold … sign variation. The results support the use of neural networks with a dynamic framework to forecast the gold price sign …

-of-sample forecasting environments. Furthermore, the predictive ability of our macro-financial measures frequently exceeds that of purely …