Markov regime-switching quantile regression models and financial contagion detection

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.     

左截断数据下非参数回归模型的复合分位数回归估计

利用局部多项式方法研究了误差具有异方差结构的非参数回归模型,在左截断数据下构造了回归函数的复合分位数回归估计,并得到了该估计的渐近正态性结果,最后通过模拟,在服从一些非正态分布的误差下,得到该估计比局部线性估计更有效.