基于复合分位数回归的股市风险研究

The Research of Credit Risk of Corporate Bonds Based on Composite Quantile Regression

摘要: 本文对GARCH模型的方差方程进行对数变换，得到的模型用于估计股市波动率。这样不仅能保证模型误差的独立同分布性，而且在做对数逆变换后也能保证波动率的非负性。针对模型误差非对称性，利用更为稳健的复合分位数回归方法估计变换后的GARCH模型。实证分析表明：变换后的模型对波动率的估计更为有效，并且复合分位数回归可以更有效的克服模型误差非正态性影响，是一种非常稳健的估计方法。

Abstract: In this paper, we establish the model, which changed the variance equation of the GARCH model with logarithmic transformation, to estimate the volatility of credit spread of corporate Bonds. It can ensure the independent identical distribution of model error. Also, the volatility is not negative after the logarithmic inverse transform. Owing to the asymmetry of model error, we use composite quantile regression, which is a more robust method, to estimate the modified GARCH model. The empirical analysis shows that the estimation of volatility is more effective with the modified model. Composite quantile regression is a very robust estimation method, and it is more effective to overcome the non-normality of the model error.