2014
DOI: 10.1016/j.intfin.2014.01.007
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An analysis of South-Eastern European stock markets: Evidence on cointegration and portfolio diversification benefits

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Cited by 68 publications
(40 citation statements)
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References 45 publications
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“…In contrast, Guidi and Ugur (2014) report that Syllignakis and Kouretas (2011) show that correlations between Central and South-Eastern European markets and the USA and German markets vary over time, with a tendency to increase during periods of financial turmoil. Horvath and Petrovski (2013) compared Central and South Eastern Europe stock market integration.…”
Section: Literature Reviewmentioning
confidence: 92%
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“…In contrast, Guidi and Ugur (2014) report that Syllignakis and Kouretas (2011) show that correlations between Central and South-Eastern European markets and the USA and German markets vary over time, with a tendency to increase during periods of financial turmoil. Horvath and Petrovski (2013) compared Central and South Eastern Europe stock market integration.…”
Section: Literature Reviewmentioning
confidence: 92%
“…Guidi and Ugur (2014) identify three reasons for increased interest in this investment region. First, both the European Bank for Reconstruction and Development (EBRD) and the European Union (EU) are encouraging financial reforms in these countries in order to enable an inflow of FDI.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Many econometric techniques have been used by the researcher to found the linkages of stock markets; Correlation analysis, Return analysis, Descriptive analysis, Unit Root Analysis, Johnson Co-integration, Co-integration, Multivariate Co-integration, Granger Causality, Bidirectional Causality, Unidirectional Causality and Variance Decomposition Analysis are used to compute the relationship [32,35,[37][38][39][40][41]. Gupta and Guidi [39] found that no long run relationship between India and Asian developed market.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In this respect, this paper relates to the discussion of studies employing univariate and bivariate GARCH models and the effect of structural breaks. For studies employing other estimation methods (cointegrations, causality, spillover effects, wavelet analysis), or forecasting methods (in-sample, out-of sample), see Demiralay and Bayraci (2015), Dajčman (2013), Horváth and Petrovski (2013), Guidi and Ugur (2014), Harrison and Moore (2012). For instance, in a recent paper that employ Diebold and Yilmaz methodology, Demiralay and Bayraci (2015) explore volatility spillovers between CEE stock markets (Poland, Hungary, the Czech Republic) and developed markets (Germany, USA) or emerging markets (Russia).…”
Section: Introductionmentioning
confidence: 99%