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Dergiler / Öneri Dergisi / 2026 / Cilt: 21 Sayı: 66

Rassal Orman Sınıflandırıcısı Yöntemi ile Borsa İstanbul’da Fiyat Köpüğünün Belirleyicilerinin Tahmin Edilmesi

Estimating the Determinants of Price Bubbles in Borsa Istanbul Using the Random Forest Classifier Method

Yunus Emre Turan(SAKARYA UNIVERSITY)0000-0002-4439-596X
Erdinç Altay(ISTANBUL UNIVERSITY)0000-0002-4461-3891
Sayfa
507–530
Yayın Tarihi
2026-07-28
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Elde edilen bulgular, %1 anlamlılık düzeyinde sıfır hipotezinin reddedildiğini ve 2020:05–2021:01 döneminde fiyat köpüğünün oluştuğunu göstermektedir.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Bu makale, Borsa İstanbul’da hisse senedi fiyatlarının temel değerlerinden saparak fiyat köpüğü oluşturup oluşturmadığını ve bu köpüklerin oluşumuna etki eden faktörleri 2010:01–2023:11 dönemi verileriyle analiz etmeyi amaçlamaktadır.
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Temel Bulgular & Veri:Literatürde, finansal piyasalarda meydana gelen fiyat köpüklerinin reel ekonomi üzerinde ciddi etkiler yarattığı ve geçmişte yaşanan birçok piyasa çöküşünde belirleyici bir rol oynadığı ifade edilmektedir.
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Sonuç & Katkı:Elde edilen bulgular, %1 anlamlılık düzeyinde sıfır hipotezinin reddedildiğini ve 2020:05–2021:01 döneminde fiyat köpüğünün oluştuğunu göstermektedir.
🔬Tür:Literatür & Derleme Çalışması
📍Kapsam:2010 Verileri
⚙️Değişkenler:Fiyat köpüğü · GSADF testi · Rassal Orman

Özet

Bu makale, Borsa İstanbul’da hisse senedi fiyatlarının temel değerlerinden saparak fiyat köpüğü oluşturup oluşturmadığını ve bu köpüklerin oluşumuna etki eden faktörleri 2010:01–2023:11 dönemi verileriyle analiz etmeyi amaçlamaktadır. Literatürde, finansal piyasalarda meydana gelen fiyat köpüklerinin reel ekonomi üzerinde ciddi etkiler yarattığı ve geçmişte yaşanan birçok piyasa çöküşünde belirleyici bir rol oynadığı ifade edilmektedir. Bu doğrultuda çalışmada, iki aşamalı bir araştırma deseni benimsenmiştir. İlk aşamada, genişletilmiş supremum augmented Dickey-Fuller (GSADF) testi kullanılarak Borsa İstanbul’da fiyat köpüğü olup olmadığı ampirik olarak test edilmiştir. Elde edilen bulgular, %1 anlamlılık düzeyinde sıfır hipotezinin reddedildiğini ve 2020:05–2021:01 döneminde fiyat köpüğünün oluştuğunu göstermektedir. İkinci aşamada ise, literatürde fiyat köpüğü üzerinde etkili olduğu belirtilen çeşitli ekonomik değişkenlerin köpük oluşumuyla ilişkisi, makine öğrenmesi tabanlı rassal orman (random forest) yöntemiyle analiz edilmiştir. Model sonuçlarına göre, fiyat köpüğü olasılığı üzerinde en belirleyici dört değişken sırasıyla emtia endeksi, finansal inovasyon, yabancı yatırımcı oranı ve güven endeksi olarak belirlenmiştir. Bu değişkenlerin köpük olasılığına etkileri, kısmî bağımlılık grafikleri ile görselleştirilmiştir. Çalışmanın bulguları, Türkiye sermaye piyasalarında fiyat köpüklerinin dönemsel olarak ortaya çıktığını ve bu olgunun hem küresel ekonomik göstergelerden hem de yatırımcı davranışlarını etkileyen unsurlardan etkilendiğini göstermektedir.

Abstract

This study aims to analyze whether stock prices in Borsa Istanbul deviate from their fundamental values to generate price bubbles, and to examine the factors influencing the formation of such bubbles using data from the period 2010:01–2023:11. The literature emphasizes that price bubbles emerging in financial markets have substantial effects on the real economy and have played a decisive role in many past stock market crashes. In line with this, a two-stage research design has been adopted. In the first stage, the generalized supremum augmented Dickey-Fuller (GSADF) test is employed to empirically investigate the existence of price bubbles in Borsa Istanbul. The findings indicate that the null hypothesis is rejected at the 1% significance level and that a price bubble occurred during the period 2020:05–2021:01. In the second stage, the relationship between various economic variables—identified in the literature as factors influencing bubble formation—and the occurrence of bubbles is analyzed using the machine learning–based random forest method. According to the model results, the four most influential variables on bubble probability are, respectively, the commodity index, financial innovation, foreign investor share, and the confidence index. The effects of these variables on bubble probability are illustrated through partial dependence plots. The findings of the study demonstrate that price bubbles emerge periodically in Turkish capital markets and that this phenomenon is shaped both by global economic indicators and by factors affecting investor behavior.

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Bu Makaleye Atıf Yap

Turan, Y. E., Altay, E. (2026). Rassal Orman Sınıflandırıcısı Yöntemi ile Borsa İstanbul’da Fiyat Köpüğünün Belirleyicilerinin Tahmin Edilmesi. Öneri Dergisi, Cilt: 21 Sayı: 66, 507–530. https://doi.org/10.14783/maruoneri.1771525

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