Abstract
We introduce the Markov regime switching model to describe the uncertainty in graphs and design the algorithm by the Markov chain Monte Carlo method. The regime-switching graphical model is applied to the stock market of Shanghai in China to study the conditional dynamic correlation of five segments of the stock market. Empirical results show that the two regimes reflect high and low correlation and the persistent probability of regime is comparatively large. Our results have potential implication for portfolio selection.
The research was supported by the National Natural Science Foundation of China (NSFC 10971042) and the Project of Wenzhou Science & Technology Bureau (R2010030).
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© 2011 Springer-Verlag Berlin Heidelberg
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Cai, F., Li, Y., Wang, H. (2011). Modelling Uncertainty in Graphs Using Regime-Switching Model. In: Wu, D., Zhou, Y. (eds) Modeling Risk Management for Resources and Environment in China. Computational Risk Management. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18387-4_56
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DOI: https://doi.org/10.1007/978-3-642-18387-4_56
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