TVP-VAR Based CARR-Volatility Connectedness: Evidence from The Russian-Ukraine Conflict

Year 2022, Volume: 7 Issue: 3, 590 - 607, 30.09.2022

Yakup Arı

https://doi.org/10.30784/epfad.1138999

Cited By: 1

Abstract

This paper aims to examine the spillover between volatilities obtained from the Conditional Autoregressive Range (CARR) process with the Time-Varying Parameter Vector Autoregressive (TVP-VAR) based Diebold-Yilmaz approach. We apply Gumbel distributed CARR (1,1) to estimate the volatilities. The summary statistics for the volatility series indicate that the series are not normally distributed, and innovations fit the Gumbel distribution. Also, the obtained volatility series are stationary. We also observe that a significant autocorrelation emerges in all series and the square series. Therefore, using a TVP-VAR model with a time-varying variance-covariance structure is a proper econometric framework to capture all these empirical properties. Moreover, we investigate the impact of the Ukraine-Russia Conflict on global markets as an example. For this purpose, we consider the Russian stock market index and indices selected from among the twenty largest stock exchanges by asset size to perform the connectedness analysis. In TVP-VAR based connectedness approach, we calculate averaged connectedness measures of two panels, without and with the Russian stock exchange. The findings show that the total connectedness index is 79.91% in the first panel, and it increases to 81.44% with the addition of Russian market.

Keywords

CARR, Diebold-Yilmaz, TVP-VAR, Volatility Connectedness, Russian-Ukraine War

TVP-VAR Tabanlı CARR Oynaklık Bağlantılılığı: Rusya-Ukrayna Çatışmasından Kanıtlar

Abstract

Bu çalışma Zamanla Değişen Parametreli Vektör Otoregresif (TVP-VAR) tabanlı Diebold-Yılmaz yaklaşımı ile Koşullu Otoregresif Aralık (CARR) sürecinden elde edilen oynaklıklar arasındaki yayılmayı incelemeyi amaçlamaktadır. Çalışmada volatiliteleri tahmin etmek için Gumbel olasılık dağılımına sahip CARR (1,1) uygulanmıştır. Özet istatistikler serilerin normal dağılım göstermediğini ve inovasyonların Gumbel dağılımına uyduğunu göstermektedir. Ayrıca elde edilen oynaklık serileri durağandır. Bunların yanında tüm serilerde ve kare serilerde anlamlı bir otokorelasyonun ortaya çıktığı gözlemlenmiştir. Bu nedenle, zamanla değişen varyans-kovaryans yapısına sahip bir TVP-VAR modeli tüm bu ampirik özellikleri yakalamak için uygun bir ekonometrik çerçevedir. Metodolojik yaklaşıma örnek olarak Ukrayna-Rusya Savaşının küresel piyasalar üzerindeki etkisini ortaya koyan bir uygulama sunulmuştur. Bu amaçla, bağlantılılık analizini gerçekleştirmek için varlık büyüklüğüne göre küresel ölçekte en büyük yirmi borsa arasından seçilen endeksler ile Rus borsa endeksi verisini içeren TVP-VAR analizi iki gruba ayrılmıştır. İlk grubu oluşturan panelde Rus borsa endeksinin oynaklığı dahil edilmezken, ikinci panele dahil edilerek ortalama toplam bağlantılılık endeksleri hesaplanmıştır. Bulgular, toplam bağlantılılık endeksinin ilk panelde %79,91 olduğunu ve Rusya pazarının eklenmesiyle %81,44'e yükseldiğini göstermektedir.

Keywords

CARR, Diebold-Yilmaz, Oynaklık Bağlantılılığı, Rusya-Ukrayna Savaşı

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