FORECASTING GOLD FUTURES PRICES CONSIDERING THE BENCHMARK INTEREST RATES

This study uses the benchmark interest rate of the Federal Open Market Committee (FOMC) to predict gold futures prices. For the predictions, we used the support vector machine (SVM) (a machine-learning model) and the long short-term memory (LSTM) deep-learning model. We found that the LSTM method is more accurate than the SVM method. Moreover, we applied the Boruta algorithm to demonstrate that the FOMC benchmark interest rates correlate with gold futures.

1. Introduction

2. Preliminaries on Machine Learning and Deep Learning

3. Materials and Methods

4. Results

5. Conclusion and Future work

References

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