Developing a Gold Price Predictive Analysis using Grey Wolf Optimizer - Nurul Asyikin, Zainal; Zuriani, Mustaffa (IEEE, 2016)

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As the value of gold cannot be blindly rejected, forecasting the future prices of gold has long been an intriguing topic and is extensively studied by researchers from different fields including economics, statistics, and computer science. The motivation for these studies is naturally to predict the future prices so that gold can be bought and sold at profitable positions and reduce the risk of investment. However, there are still a lot of untackled questions and room for improvements in these forecasting techniques. This is because there are no optimal models for all forecasting problems. Different question needs a different answer; therefore, more experiments and modeling need to be done in order for researcher to enhance their findings. The target of this paper is to present a gold forecasting techniques using one of the optimization algorithm called Grey Wolf Optimizer (GWO).