Mapping the stocks in MICEX: Who is central in Moscow Stock Exchange?
Mustafa Eratalay () and
No Ec-01/17, EUSP Department of Economics Working Paper Series from European University at St. Petersburg, Department of Economics
In this article we use partial correlations to derive bidirectional connections between the major firms listed in MICEX. We obtain the coefficients of partial correlation from the correlation estimates of constant conditional correlation GARCH (CCC-GARCH) and consistent dynamic conditional correlation GARCH (cDCC-GARCH) models. We map the graph of partial correlations using the Gaussian graphical model and apply network analysis to identify the most central firms in terms of shock propagation and in terms of connectedness with others. Moreover, we analyze some macro characteristics of the network over time and measure the system vulnerability to external shocks. Our findings suggest that during the crisis interconnectedness between firms strengthen and system becomes more vulnerable to systemic shocks. In addition, we found that the most connected firms are Sberbank and Lukoil while most central in terms of systemic risk are Gazprom and FGC UES.
Keywords: Multivariate GARCH; Volatility Spillovers; Network connections; MICEX (search for similar items in EconPapers)
JEL-codes: C01 C13 C32 C52 (search for similar items in EconPapers)
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Persistent link: http://EconPapers.repec.org/RePEc:eus:wpaper:ec0117
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