A Synergistic Forecasting Model for Techno-Fundamental Analysis of Gold Market Returns

Korhan K. Gokmenoglu () and Saeed Ebrahimijam ()
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Korhan K. Gokmenoglu: Ankara HBV University
Saeed Ebrahimijam: Eastern Mediterranean University

Chapter Chapter 5 in Regulation of Finance and Accounting, 2022, pp 61-72 from Springer

Abstract: Abstract This study presents a novel approach to financial market forecasting based on a synergistic forecasting model, a type of techno-fundamental analysis that combines technical analysis indicators with fundamental variables using the Kalman filter to improve the accuracy of predictions. We used this model to forecast daily market price returns on gold. The obtained results show that our synergistic model can significantly deduct the root-mean-square error (RMSE) of the predictions compared to a sole technical and/or fundamental analysis. Also, 67% of the time, the model significantly and correctly predicted directional changes in prices one day ahead of time, outperforming the benchmark models.

Keywords: Gold price; Synergistic forecasting; EGARCH; Support vector regression; Technical analysis indicator (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-030-99873-8_5

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DOI: 10.1007/978-3-030-99873-8_5

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