The Behaviour of Asset Return and Volatility Spillovers in Turkey: A Tale of Two Crises

Abstract

This paper examines return and volatility spillovers between the Turkish stock market with international stock, exchange rate and commodity markets. Our aim is not only to examine spillover behaviour with a large emerging market but also to examine crossasset spillovers and how they vary across two periods of financial market crisis; the dotcom crash and the liquidity-induced financial crisis. This is to be compared with existing work that typically focuses on industrialised countries or single asset markets only. Using the spillover index methodology we uncover an interesting distinction between these two periods of markets stress. Over the dotcom period spillovers are largely between the same asset class, notably two exchange rate series and two international stock markets series. However, in the period including the financial crisis, spillovers both increase and cross asset types and suggest a much greater degree of market interdependence. Understanding this changing nature in spillovers is key for investors, regulators and academics involved in theoretical model development.

An Analysis of the Stock Market Volatility Spread in Emerging Countries

“…The determination of volatility spread and testing of volatility models in indices within Borsa Istanbul have become widespread especially since the 2000s, and Borsa Istanbul 100 Index volatility has an ARCH effect (Doğanay, 2003;Duran & Şahin, 2006;Akgün & Sayyan (2007); Sevüktekin & Nargeleçekenler, 2006;Atakan, 2009). After the 2008 financial crisis, studies testing the effects of volatility on Borsa Istanbul Stock Exchange with the help of GARCH models have increased significantly (Tülin, 2009, Çağıl & Okur, 2010Yorulmaz & Ekici, 2010;Güriş & Saçıldı, 2011;Demir & Çene, 2012;Evlimoğlu & Çondur, 2012;Çukur et al 2012;Kutlar & Torun, 2013;Er & Fidan, 2013;Samırkaş & Düzakın, 2013;Demirhan, 2013;Demirgil & Gök, 2014;Karabacak et al 2014;Gürsoy & Balaban, 2014;Gökbulut & Pekkaya, 2014;Eryılmaz, 2015, McMillan et al 2016Kırkulak & Ezzat, 2017, Baykut & Kula, 2018Kocabaş, 2019,). In addition to GARCH models, the EGARCH model can estimate volatility, taking into account the asymmetry of the shocks.…”