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Comput Manag Sci (2014) 11:4555
DOI 10.1007/s10287-013-0165-7
ORIGINAL PAPER
Received: 31 July 2012 / Accepted: 4 March 2013 / Published online: 18 April 2013 Springer-Verlag Berlin Heidelberg 2013
Abstract We consider a market graph model of the Russian stock market. To study the peculiarity of the Russian market we construct the market graphs for different time periods from 2007 to 2011. As characteristics of constructed market graphs we use the distribution of correlations, size and structure of maximum cliques, and relationship between return and volume of stocks. Our main nding is that for the Russian market there is a strong connection between the volume of stocks and the structure of maximum cliques for all periods of observations. Namely, the most attractive Russian stocks have a strongest correlation between their returns. At the same time as far as we are aware this phenomenon is not related to the well developed USA stock market.
Keywords Russian stock market Market graph Maximum clique
1 Introduction
The study of the economic networks and understanding new important properties of their structure is very important nowadays (Schweitzer et al. 2009; Mantegna and Stanley 2000). One of the network models of the stock market is the market graph model. The market graph notion used in this paper was introduced by Boginski et al. (2003). This model was applied to analyze the US stockmarket (Boginski et al. 2003,
A. Vizgunov (B) V. Kalyagin A. Koldanov P. Koldanov P. M. Pardalos
National Research University Higher School of Economics, 25/12 Bolshaja Pecherskaja Ulitsa, Nizhny Novgorod 603155, Russiae-mail: [email protected]
B. Goldengorin P. M. Pardalos
Industrial and Systems Engineering Department, University of Florida, 303 Weil Hall, Gainesville, FL, USA
Network approach for the Russian stock market
A. Vizgunov B. Goldengorin V. Kalyagin
A. Koldanov P. Koldanov P. M. Pardalos
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46 A. Vizgunov et al.
2005, 2006), Swedish stock market (Jallo et al. 2013), Chinese stock market (Huang et al. 2009), Iranian stock market (Namaki et al. 2011) and others (Salter-Townshend et al. 2012). The majority of publications on the market graph use the following characteristics for their study: the distribution of correlations of returns, edge density, size and structure of maximum cliques and maximum independent sets. The focus of this paper is to apply the market...