Network approach for the Russian stock market
- 566 Downloads
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 finding 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.
KeywordsRussian stock market Market graph Maximum clique
We would like to thank the anonymous referees for their useful comments for improving the quality and the presentation of the paper. The authors are partially supported by LATNA Laboratory, NRU HSE, RF, government grant ag. 11.G34.31.0057.
- Boginski V, Butenko S, Pardalos PM (2003) On structural properties of the market graph. In: Nagurney A (ed) Innovations in financial and economic networks. Edward Elgar Publishing, UK, pp 29–45.Google Scholar
- Bron C, Kerbosh J (1973) Algorithm 457—finding all cliques of an undirected graph. Commun of ACM 16:575–577Google Scholar
- Jallo D, Budai D, Boginski V, Goldengorin B, Pardalos PM (2013) Network-based representation of stock market dynamics: an application to American and Swedish stock markets. In: Goldengorin B, Kalyagin V, Pardalos PM (eds) Models, algorithms, and technologies for network analysis Springer proceedings in mathematics and statistics. Springer, Berlin, pp 93–106Google Scholar
- Mantegna RN, Stanley HE (2000) An introduction to econophysics: corrleations and complexity in finance. Cambridge Universiy Press, CambridgeGoogle Scholar
- Schweitzer F, Fagiolo G, Sornette D, Vega-Redondo F, Vespignani A, White DR (2009) Economic networks: the new challenges. Science 325:422–425Google Scholar