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Mapping the Stocks in MICEX: Who Is Central in Moscow Stock Exchange?

Author

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  • M. Hakan Eratalay
  • Evgenii Vladimirov
Abstract
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.

Suggested Citation

  • M. Hakan Eratalay & Evgenii Vladimirov, 2017. "Mapping the Stocks in MICEX: Who Is Central in Moscow Stock Exchange?," EUSP Department of Economics Working Paper Series 2017/01, European University at St. Petersburg, Department of Economics.
    • Handle: RePEc:eus:wpaper:ec2017_01
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    References listed on IDEAS

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    Cited by:

    1. Ariana Paola Cortés Ángel & Mustafa Hakan Eratalay, 2022. "Deep diving into the S&P Europe 350 index network and its reaction to COVID-19," Journal of Computational Social Science, Springer, vol. 5(2), pages 1343-1408, November.
    2. Mustafa Hakan Eratalay & Ariana Paola Cortés Ángel, 2022. "The Impact of ESG Ratings on the Systemic Risk of European Blue-Chip Firms," JRFM, MDPI, vol. 15(4), pages 1-41, March.
    3. Ariana Paola Cortés à ngel & Mustafa Hakan Eratalay, 2021. "Deedp Diving Into The S&P 350 Europe Index Network Ans Its Reaction To Covid-19," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 134, Faculty of Economics and Business Administration, University of Tartu (Estonia).

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    More about this item

    Keywords

    Multivariate GARCH; Volatility Spillovers; Network connections; MICEX;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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