Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/52414 
Year of Publication: 
2011
Series/Report no.: 
Kiel Working Paper No. 1739
Publisher: 
Kiel Institute for the World Economy (IfW), Kiel
Abstract: 
In the current era of strong worldwide market couplings the global financial village became highly prone to systemic collapses, events that can rapidly sweep through out the entire village. Here we present a new methodology to assess and quantify inter-market relations. The approach is based on the correlations between the market index, the index volatility, the market Index Cohesive Force and the meta-correlations (correlations between the intra-correlations.) We investigated the relations between six important world markets - U.S., U.K., Germany, Japan, China and India from January 2000 until December 2010. We found that while the developed western'' markets (U.S., U.K., Germany), are highly correlated, the interdependencies between these markets and the developing eastern'' markets (India and China) are very volatile and with noticeable maxima at times of global world events (2001: 9/11-attacks, 2003: Iraq war, SARS, etc). The Japanese market switches identity'' - it switches between periods of high meta-correlations with the western'' markets and periods that it behaves more similar to the eastern'' markets. These and additional reported findings illustrate that the methodological framework provides a way to quantify the evolvement of interdependencies in the global market, to evaluate a world financial network and quantify changes in the world inter market relations. Such changes can be used as precursors to the agitation of the global financial village. Hence, the new approach can help to develop a sensitive financial seismograph'' to detect early signs of global financial crises so they can be treated before developed into world wide events.
Subjects: 
financial markets
comovement
financial crisis
stock correlations
networks
JEL: 
G15
G01
F36
Document Type: 
Working Paper

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