Relevance Vector Machines for Index Direction Predictions: An Application on Borsa Istanbul

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Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi
Volume:19 Issue:2
Relevance Vector Machines for Index Direction Predictions: An Application on Borsa Istanbul

Relevance Vector Machines for Index Direction Predictions: An Application on Borsa Istanbul

Pages : 594-610

View : 67 | Download : 122

Publication Date : 2024-08-01

Article Type : Research Paper

Abstract :This study investigates index prediction performance of Relevance Vector Machines (RVM) and frequently applied Ridge Regression and Support Vector Machines (SVM). Daily prices of BIST Banks and BIST Financials indices of Borsa Istanbul are used to obtain one-day-ahead predictions of the algorithms. According to estimated performance measures, RVM yielded mostly the best metrics in both periods of BIST Banks. While SVM obtained the best performance metrics on BIST Financials index, metrics of RVM were not far from the best. Overall, the results indicate the applicability of RVM in predicting index directions and has a potential to be a good rival of SVM.
Keywords : Endeks Tahmini, Destek Vektör Makineleri, Ridge Regresyonu, İlgililik Vektör Makineleri

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