Markov regime-switching quantile regression models and financial contagion detection |
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Affiliation: | 1. Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei 230026, PR China;2. University of Nottingham Business School China, University of Nottingham Ningbo, Ningbo 315100, PR China;1. School of Economics and Management, China University of Geosciences, Beijing, 100083, China;2. Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and Resources, Beijing, 100083, China;3. Trinity Business School, Trinity College Dublin, Dublin 2, Ireland |
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Abstract: | In this paper, we propose a Markov regime-switching quantile regression model, which considers the case where there may exist equilibria jumps in quantile regression. The parameters are estimated by the maximum likelihood estimation (MLE) method. A simulation study of this new model is conducted covering many scenarios. The simulation results show that the MLE method is efficient in estimating the model parameters. An empirical analysis is also provided, which focuses on the detection of financial crisis contagion between United States and some European Union countries during the period of sub-prime crisis from the angle of financial risk. The degree of financial contagion between markets is subsequently measured by utilizing the quantile regression coefficients. The empirical results show that in a crisis situation, the interdependence between United States and European Union countries dramatically increases. |
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Keywords: | Risk analysis Financial contagion Markov regime-switching Quantile regression Laplace distribution |
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