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http://dx.doi.org/10.14403/jcms.2021.34.2.157

FORECASTING GOLD FUTURES PRICES CONSIDERING THE BENCHMARK INTEREST RATES  

Lee, Donghui (Department of Mathematics Pusan National University)
Kim, Donghyun (Department of Mathematics Pusan National University)
Yoon, Ji-Hun (Department of Mathematics Pusan National University)
Publication Information
Journal of the Chungcheong Mathematical Society / v.34, no.2, 2021 , pp. 157-168 More about this Journal
Abstract
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.
Keywords
Gold future prices; Boruta algorithm; Long short-term memory; Support vector machine; Benchmark interest rates;
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