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MODELING THE DYNAMIC INTERDEPENDENCE OF MAJOR EUROPEAN STOCK MARKETS
Author(s) -
Koutmos Gregory
Publication year - 1996
Publication title -
journal of business finance and accounting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.282
H-Index - 77
eISSN - 1468-5957
pISSN - 0306-686X
DOI - 10.1111/j.1468-5957.1996.tb01035.x
Subject(s) - stock (firearms) , financial economics , economics , business , history , archaeology
The growing globalization of financial markets has been accompanied by a growing body of empirical research attempting to describe and quantify the ways in which financial markets within and across countries interact. Better understanding of the nature of cross market linkages and interactions could be of help to investors and policy makers alike. With respect to policy, aspects of market interaction that promote efficiency could, in principle, be facilitated whereas, those with undesirable side effects could be controlled. Likewise, investment and hedging strategies could be more effective if the nature of market interactions were better understood. The extant literature provides convincing evidence that financial markets do influence each other. For example, Koch and Koch (1991) provide evidence on the evolution of contemporaneous and lead/lag relationships among eight national stock markets. They suggest that regional interdependencies have grown over time. Becker, Finnerty, and Gupta (1990) show that information generated in the US stock market could be used to trade profitably in Japan, contrary to the market efficiency hypothesis. However, when transaction costs and transfer taxes are included into the analysis, excess profits vanish. Eun and Shim (1989) document that markets around the globe respond to innovations in a way that is consistent with the notion of informationally efficient international stock markets. King and Wadhwani (1990) use a rational expectations model with asymmetric information to test for 'contagion effects' i.e., the notion that valuation mistakes in one market can be transmitted to other markets.' More recent papers extend the scope of market interaction to include second moment linkages. This extension allows testing ofthe hypothesis that information generated in a given market at time / is useful in terms of predicting the conditional mean and variance in another market at time t+l. Hamao, Masulis and Ng (1990) examine first and second moment interdependencies in the three major stock markets (New York, Tokyo, and London) using univariate GARCH models. For the period after the October 1987 worldwide stock market crash, they find that innovations coming from