Time-Varying Beta Estimation: A Comparison of DCC-GARCH and Rolling-Window Methods in Turkish Industry Portfolios

Öz

This study empirically compares the accuracy of two common methods for estimating time-varying betas in Turkish industry portfolios: rolling-window OLS regression and the DCC model. Using daily returns from 2004 to 2024, the methods are evaluated based on their alignment with CAPM predictions, specifically the insignificance of Jensen’s alpha and the significance of the market risk premium. Findings show that despite its complexity, the DCC model does not outperform the rolling-window approach. The rolling-window approach produces insignificant Jensen’s alpha estimates for more industries and yields slightly higher mean and t-statistics for the market risk premium. These findings challenge the view that rolling-window estimators are inefficient due to assuming beta constancy within short windows and suggest that the DCC model’s reliance on multiple constant parameters imposes a rigid structure that may hinder its adaptability to evolving market conditions. This study contributes to the literature by directly comparing these two widely used methods and highlighting the importance of carefully considering model assumptions when estimating time-varying betas.

Anahtar Kelimeler

• CAPM
• Time-varying beta
• DCC
• Rolling-window
• Jensen’s alpha
• Market risk premium

Zamanla Değişen Betanın Tahmini: Türk Sektör Portföylerinde DCC-GARCH ve Rolling-Window Yöntemlerinin Karşılaştırılması

Öz

Bu çalışma, Türk sektör portföylerinde zamanla değişen betaların tahmininde yaygın olarak kullanılan iki yöntem olan kayan pencere en küçük kareler regresyonu ile DCC modelini ampirik olarak karşılaştırmaktadır. 2004–2024 dönemine ait günlük getiriler kullanılarak, bu yöntemler CAPM öngörüleriyle özellikle Jensen alfa değerlerinin anlamsızlığı ve piyasa risk priminin anlamlılığı temelinde değerlendirilmiştir. Bulgular, karmaşıklığına rağmen DCC modelinin kayan pencere yaklaşımından daha iyi performans göstermediğini ortaya koymaktadır. Kayan pencere yaklaşımı, daha fazla sektör için istatistiksel olarak anlamsız Jensen alfa tahminleri verirken, piyasa risk primi için biraz daha yüksek ortalama ve t-istatistikleri üretmektedir. Bu bulgular, kısa pencere sürelerinde betanın sabit olduğu varsayımına dayanan kayan pencere yöntemlerinin etkin olmadığı görüşüne meydan okumakta ve DCC modelinin çok sayıda sabit parametreye dayalı yapısının, değişen piyasa koşullarına uyum sağlamasını zorlaştırabileceğini göstermektedir. Çalışma, bu iki yaygın yöntemi doğrudan karşılaştırarak ve zamanla değişen beta tahmininde model varsayımlarının dikkatli değerlendirilmesinin önemini vurgulayarak literatüre katkı sağlamaktadır.

Anahtar Kelimeler

• SVFM
• Zamanla değişen beta
• Dinamik Koşullu Korelasyon
• Kayan pencere
• Jensen alpha
• Piyasa risk primi

Kaynakça

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