A Comparison of Forecasting Accuracy between Two Dynamic Conditional Correlation (DCC) Models

Öz

This study compares two commonly used DCC-family models to predict the linkage between the US equity and REIT markets within a global minimum-variance portfolio. Equity and REIT portfolios are constructed using variance-covariance matrices, which represent forward-looking covariance information. These matrices are constructed out-of-sample with ex-ante forecasting. By assessing the predictive precision of each model, the study aims to determine which one produces the lowest forecasting errors and performs better economically. According to a statistical comparison, ex-ante correlation forecasts based on the Asymmetric DCC model were more accurate than those based on the standard DCC model. An empirical comparison of the economic performance of these two models in a dynamic portfolio allocation framework reveals that, despite its complexity, the Asymmetric DCC model exhibits similar economic performance characteristics to the standard DCC model. Despite the lack of emphasis on the economic overperformance of the Asymmetric DCC model, investors who recalibrate their portfolios weekly will benefit from reduced forecast errors and the ability to create more efficient portfolios by using an asymmetric model instead of a standard model.

Anahtar Kelimeler

• Forecasting Error
• Asymmetric DCC-GARCH
• Dynamic Correlation

İki Dinamik Koşullu Korelasyon (DCC) Modeli Arasındaki Tahmin Doğruluğunun Karşılaştırılması

Öz

Bu çalışma, genel bir minimum varyans portföyü içinde ABD hisse senedi ve GYO (Gayrimenkul Yatırım Ortaklığı) piyasaları arasındaki bağlantıyı tahmin etmek için yaygın olarak kullanılan iki Dinamik Koşullu Korelasyon (DCC) modelini karşılaştırmaktadır. Hisse senedi ve GYO portföyleri, varyans-kovaryans matrisleri ile örneklem dışı olarak oluşturulmuş, ex-ante tahminle ileriye dönük kovaryans bilgisini temsil etmektedir. Çalışmanın amacı, her iki modelin tahmin hassasiyetini değerlendirip hangisinin daha düşük tahmin hataları ürettiğini ve ekonomik olarak daha iyi performans gösterdiğini belirlemektir. İstatistiksel karşılaştırmaya göre Asimetrik DCC modele dayanan ex-ante korelasyon tahminleri, standart DCC modele göre daha küçük hatalar üretmektedir. Bu iki modelin ekonomik performansı, dinamik bir portföy tahsisi çerçevesinde ampirik olarak karşılaştırıldığında, Asimetrik DCC modelinin standart DCC modeline benzer ekonomik performans özellikleri sergilediği ortaya konulmuştur. Asimetrik DCC modelinin ekonomik performansına rağmen portföylerini haftalık olarak yeniden kalibre eden yatırımcılar, daha az tahmin hatasından ve daha verimli portföyler oluşturma becerisinden faydalanabilirler.

Anahtar Kelimeler

• Tahmin Hatası
• Asimetrik DCC-GARCH
• Dinamik Korelasyon

Kaynakça

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