A novel hybrid model on the prediction of time series and its application for the gold price analysis and forecasting

Jianwei E, Jimin Ye and Haihong Jin

Physica A: Statistical Mechanics and its Applications, 2019, vol. 527, issue C

Abstract: Gold, as a dominant ingredient in financial market, has gripped a large quantities of the financiers and scholars to research the formation mechanism of its price. Academic circles spring up plenty of methods to analyze and predict the gold price, such techniques are based on linear regression (MLR), support vector machine (SVM), artificial neural network (ANN), respectively. However, the existing methods cannot track the random and nonlinear features of the gold price well. The accurate and effective estimation models are acceptable for researching the temporal sequence, at the same time, it will be a powerful tool for governments and investors to formulate strategies.

Keywords: Gold price; Independent component analysis; Gated recurrent unit neural network; Hidden states; Mode function (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:527:y:2019:i:c:s037843711930843x

DOI: 10.1016/j.physa.2019.121454

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