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.
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Notes
- 1.
According to ADF and Phillips-Perron unit root test all of the variables are stationary at level. However, because of the space constraint, results are not presented here. They can be submitted upon request.
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5.1.1 Flow Chart of the Proposed Synergistic Techno-Fundamental Model
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Gokmenoglu, K.K., Ebrahimijam, S. (2022). A Synergistic Forecasting Model for Techno-Fundamental Analysis of Gold Market Returns. In: Procházka, D. (eds) Regulation of Finance and Accounting. ACFA ACFA 2021 2020. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-99873-8_5
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