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Abstract
In this study, we apply directed acyclic graphs and search algorithm designed for time
series with non-Gaussian distribution to obtain causal structure of innovations from an error
correction model. The structure of interdependencies among six international stock markets is
investigated. The results provide positive empirical evidence that there exist long-run
equilibrium and contemporaneous causal structure among these stock markets.
DAG analysis results show that Hong Kong is influenced by all other open markets in
contemporaneous time, whereas Shanghai is not influenced by any of the other markets in
contemporaneous time. Historical decompositions indicate that New York and Shanghai stock
markets are highly exogenous and Germany and Hong Kong are the least exogenous markets.
Further, we find that New York is the most influential stock market with consistent impact on
price movements.
One implication is that diversification between US and Germany may not provide desired
immunity from financial crisis contagion as much as it does diversification between US and
Shanghai.