BIST100 Bankacılık Sektöründeki Bağımlılığın Asma Kopula ile İncelenmesi

Son yıllarda sıklıkla gözlemlenen finansal piyasalar arasındaki bağımlılık ve zamana bağlı görülen değişim, modelleme ve fiyatlama açısından önem taşımaktadır. Bu çalışmada, BIST100’de işlem gören bankacılık sektörüne ait hisselerin arasındaki bağımlılık yapısının, zaman serileri ve kurallı asma (R-Vine) kopula modeli ile incelenmesi amaçlanmaktadır. Bankacılık hisselerinden eşit ağırlıklandırılarak oluşturulan portföy için, riske maruz değer (VaR) ve beklenen kayıp (ES) risk ölçütleri hesaplanmış ve geriye dönük yöntemlerle test edilmiştir. Türkiye bankacılık hisseleri özelinde yapılan bu çalışmada, GARCH ve kurallı asma kopula modellerinin birlikte uygulanmasının, geleneksel GARCH tabanlı yaklaşımlara kıyasla VaR ve ES risk ölçütü tahminlerini iyileştirdiğine dair bulgular elde edilmiştir.

Dependence Analysis of the ISE100 Banking Sector Using Vine Copula

The frequently observed time-varying trends and dependence in recent years within financial markets have been essential for modeling and pricing. This study aims to analyze the dependence structure of banking sector stocks traded on the ISE100 index using time series and regular vine (R-vine) copula models. The study calculates the risk measures of value-at-risk (VaR) and expected shortfall (ES) and tests with backtesting methods for the portfolio that are constructed by equally weighting the banking stocks. This study’s findings on banking stocks specifically indicate that the application of the R-vine copula combined with the generalized auto-regressive conditional heteroskedasticity (GARCH) model improved the VaR and ES estimates compared to traditional GARCH-based approaches.

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