TREND ANALYSIS OF GLOBAL STOCK MARKET LINKAGE BASED ON A DYNAMIC CONDITIONAL CORRELATION NETWORK

Author:

YIN Kedong1,LIU Zhe1,LIU Peide2

Affiliation:

1. Ocean University of China

2. Shandong University of Finance and Economics

Abstract

The paper analyses the trend of global stock market linkages via daily data of 51 stock indices spanning the period 22 July 2005 to 30 June 2016 which covers four regions: America, Europe, Asia Pacific and Africa. A dynamic conditional multivariate generalized autoregressive conditional heteroskedasticity (DCC-MVGARCH) approach was used to calculate dynamic correlation coefficient in order to construct the volatility networks. The methods of minimum spanning tree (MST) and low pass filter were for the first time applied to analyze the variable periodicity of the comovement. The original contribution of this paper is that contrary to previous works, financial events such as Quantitative Easing (QE) and Bailouts are accounted for rather than only crisis factors such as the 2008 financial crisis and the European Debt crisis. The main findings of the paper are as follows: (1) Financial crisis promotes and strengthens global stock markets linkage in the short run; (2) Linkage cycles post crisis are significantly short, due to the effect of monetary policy spillover effects caused by QE from developed to developing countries; and (3) European stock markets are the information transmission hub for global stock market. The research conclusions would be significant for both government to regulate markets as well as for investors to diversify risks.

Funder

The ministry of education philosophy and social sciences development report breeding project

National Natural Science Foundation of China

Taishan Scholars Project of Shandong Province

national social science fund major projects

Public welfare industry research projects

Publisher

Vilnius Gediminas Technical University

Subject

Economics and Econometrics,Business, Management and Accounting (miscellaneous)

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