Identifying influential stock indices from global stock markets: A social network analysis approach

Abstract

Abstract We have proposed a method to rank the stock indices from across the globe using social network analysis approach. The temporal evolution of correlation network and Minimum Spanning Tree (MST) of global stock indices have been analyzed using weekly returns of 93 stock indices for five-year period from the year 2006 through 2010 obtained from Bloomberg. We have chosen this period to study the behaviour of the stock market network before and after the collapse of Lehman Brothers in the USA. Our study attempts to answer the questions about identifying the most influential stock indices in the global stock market, regional influence on the comovement of stock indices, and the impact of the collapse of Lehman Brothers in the USA and the associated global financial crisis that followed on the dynamics of stock market network.