Abstract
Gold has multiple attributes and its price is affected by various factors in the market. This paper studies the dynamic relationship between the gold price returns and its affecting factors. Then we use the STL-ETS, neural network and Bayesian structural time series model to predict the gold price returns, and compare their performance with the benchmark models. The results show that the shocks of crude oil returns and VIX have the positive effect on gold price returns, the shocks of the US dollar index have the negative effect on gold price returns. And the fluctuation of gold price returns mainly depends on crude oil price returns shocks. STL-ETS model can accurately fit the fluctuation trend of the gold price returns and improve prediction accuracy.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
