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

Yıl 2024, , 594 - 610, 01.08.2024

Cemile Özgür

https://doi.org/10.17153/oguiibf.1400125

Öz

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.

Anahtar Kelimeler

Index Prediction, Support Vector Machines, Ridge Regression, Relevance Vector Machines

Endeks Yönü Tahmininde İlgililik Vektör Makineleri: Borsa İstanbul Üzerine Bir Uygulama

Öz

Bu çalışma, İlgililik Vektör Makineleri (İVM) ile sıklıkla uygulanan Destek Vektör Makineleri (DVM) ve Ridge Regresyonunun endeks tahmin performansını araştırmaktadır. Algoritmaların bir gün sonrası tahminlerinin elde edilmesi amacıyla Borsa İstanbul’un BIST Banka ve BIST Mali endekslerinin günlük fiyat serileri kullanılmıştır. Hesaplanan performans ölçütlerine göre İVM, BIST Banka’nın her iki periyodunda da çoğunlukla en iyi ölçütleri sağlamıştır. BIST Mali endeksinin en iyi performans ölçütlerini DVM elde etmişken, İVM’nin ölçütleri en iyiden çok uzakta değildir. Genel olarak sonuçlar, İVM’nin endeks yönü tahmininde uygulanabilirliğini ve DVM’nin iyi bir rakibi olma potansiyeline sahip olduğunu belirtmektedir.

Anahtar Kelimeler

Endeks Tahmini, Destek Vektör Makineleri, Ridge Regresyonu, İlgililik Vektör Makineleri

Kaynakça

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