M-GARCH Modellerinin Karşılaştırmalı Analizi

Öz

Tek bir değişken için zamanla değişen varyans kavramını ele alan ARCH modeli, çok sayıda içeren modeller için genişletilmiştir. Bu modellerde en önemli problem, çok sayıda parametrenin tahmin ediliyor olmasıdır. Bu çalışma Diagonal VEC, Sabit Koşullu Korelasyon (CCC) ve Diagonal BEKK gibi M-GARCH modellerini, Frobenius, Eigenvalue ve Foerstner Metric gibi metrik uzaklık teknikleri açısından karşılaştırmaktadır. Diagonal VEC, benchmark olarak düşünülmüştür. Temel bulgu, Diagonal BEKK tahminlerinin CCC modeline göre benchmark modelinin sonuçlarına daha yakın sonuçlar verdiği yönündedir

Anahtar Kelimeler

• M-GARCH, metrik uzaklık

The Comparative Analysis Of M-GARCH Models

Öz

The ARCH model in capturing time-varying variance of economic data in the univariate case has been extended to the multivariate case. An important problem with these models is the a large number of parameters that have to be estimated. This paper compares different M-GARCH type models, namely The Diagonal VEC, Constant Conditional Correlation (CCC) and Diagonal BEKK in terms of their matrix distance metrics. apply three distance metrics, namely Frobenius, Eigenvalue ve Foerstner Metric. The Diagonal VEC is considered as the bencmark. The main finding is that Diagonal BEKK estimation gives more close results with the bencmark than CCC.

Anahtar Kelimeler

• M-GARCH, metric distance

Kaynakça

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