sis 23(5):

Research Article

Gold Returns Prediction

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  • @ARTICLE{10.4108/eetsis.3323,
        author={Ahmet Yavuz and S\'{y}leyman Eken},
        title={Gold Returns Prediction},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={10},
        number={5},
        publisher={EAI},
        journal_a={SIS},
        year={2023},
        month={7},
        keywords={gold returns, Machine learning, sentiment analysis, text analysis, Deep learning},
        doi={10.4108/eetsis.3323}
    }
    
  • Ahmet Yavuz
    Süleyman Eken
    Year: 2023
    Gold Returns Prediction
    SIS
    EAI
    DOI: 10.4108/eetsis.3323
Ahmet Yavuz1, Süleyman Eken1,*
  • 1: University of Kocaeli
*Contact email: suleyman.eken@kocaeli.edu.tr

Abstract

INTRODUCTION: Major events such as economic crises, inflation, geopolitical tensions, and interest rates can have a significant impact on the price and returns of gold. OBJECTIVES: In this work, we focus on gold return prediction in five major events that occurred in Turkey. METHODS: We work on two data, one of which is text-based and the other is financial data. In the financial part, many algorithms are tested and it is found that Extra Trees Regressor gives the best results in most metrics. In text-based part, we first create a new dataset and then implement sentiment analysis and topic modelling. RESULTS: Working on data with two different modes (numeric and text) offers different perspectives. CONCLUSION: The use of sentiment analysis alone to forecast gold returns is not advised, it should be noted. To produce a more precise and trustworthy estimate of gold returns, additional fundamental and technical elements including interest rates, inflation, geopolitical concerns, and supply and demand should also be taken into account.