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Abstract
Nowadays, investing in gold as a hedge against macroeconomic factors risk has been brought into the spotlight. It is essential for investors to predict gold prices before making their hedging decisions. After a thorough study of past precursors, the machine learning method, especially the gradient boosting technique, has been proven to be a powerful method for predicting gold prices. This study tests macroeconomic factors as well as oil prices and uses them as independent variables to predict gold prices. By using advanced machine learning technique: gradient boosting, this study achieves finding the best four factors model. The research shows that oil prices, the U.S. dollar index, interest rate, and GDP growth are significant factors in predicting gold prices. Among all the significant factors, oil price is the most important one. The explicit reasons of this result is because that transportation cost and operation cost of gold mining is largely influenced by oil price. This study lays the foundations for investors to make insightful decisions.
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