The Co‐movement Dynamics of European Frontier Stock Markets

Abstract

We examine, through application of wavelet coherency, the co‐movement of European frontier stock markets with the USA and developed markets in Europe. We find that the strength of co‐movement varies considerably across the frontier markets, at different frequencies (time horizons), and over time. Co‐movement is relatively weaker for the frontier markets of Central and Southeastern Europe than in the Baltic region. Of the markets examined, Slovakia in particular shows low dependence, whereas Lithuania seems to be the most dependent market. Co‐movement is stronger at lower frequencies (longer horizons) and increases during the turbulent period of the global financial crisis of 2008/2009. We identify several macroeconomic factors related to variations in co‐movement at different time frequencies.

Benefits of wavelet-based carry trade diversification

“…See, e.g. Graham and Nikkinen (2011), Graham et al (2012), Kiviaho et al (2012), Nikkinen et al (2012) and Loh (2013). 4 The results of the study are consistent with previous findings of carry trade excess returns over uncovered interest parity (e.g.…”

Impact of financial market uncertainty and macroeconomic factors on stock–bond correlation in emerging markets

“…Readers interested in the VIF measure should refer to O'Brien (2007). 12 A similar approach to determining short and long horizons is applied in Kiviaho et al (2014). business cycle pattern is the least influential macroeconomic factor in the short run as it is significant in only two markets, suggesting that the emerging market stock-bond return correlation is virtually unaffected by the domestic business cycle patterns at the short horizon.…”

“…Third, we extend the literature on financial market uncertainty by examining 1 A wavelet analysis approach has been applied in several studies to analyze financial time-series. For example, Rua and Nunes (2009), Kiviaho et al (2014), and el Alaoui et al (2015) apply wavelet squared coherency to analyze international co-movement of stock market returns. Kim and In (2007) apply wavelet analysis to examine the relationship between changes in stock prices and bond yields in G7 countries, while Aloui et al (2015) utilize wavelet approach to examine co-movement between Islamic stocks and bonds in the Gulf Cooperation Council (GCC) countries.…”

Rational Speculative Bubbles in the Frontier Emerging Stock Markets

“…Therefore, we should be equipped with further formal econometric tests to detect the existence of bubbles in those rapidly growing frontier emerging stock markets for various practical and academic reasons such as investments, portfolio diversifications, risk managements, and monetary policy and regulation purposes. In addition, the bubble detection is important to examine co-movement dynamics of frontier stock markets (Kiviaho, Nikkinen & Piljak 2014) and investor herds and regime-switching (Balcilar, Demirer & Hammoudeh 2013).…”