A New Regime Switching Model with State-Varying Endogeneity

• 来源期刊: 管理科学学报（英文版）
• 关键词: Regime switching models Latent factor State-varying endogeneity Maximum likelihood estimation Markov chain
• 年，卷（期）: 2018,（4）
• 页码范围: 214-231
• 页数: 18页
• 语种: 中文
• DOI: 10.3724/SP.J.1383.304012

摘要

In this paper,we propose a state-varying endogenous regime switching model (the SERS model),which includes the endogenous regime switching model by Chang et al.,the CCP model,as a special case.To estimate the unknown parameters in the SERS model,we propose a maximum likelihood estimation method.Monte Carlo simulation results show that in the absence of state-varying endogeneity,the SERS model and the CCP model perform similarly,while in the presence of state-varying endogeneity,the SERS model performs much better than the CCP model.Finally,we use the SERS model to analyze Chinese stock market returns,and our empirical results show that there exists strongly state-varying endogeneity in volatility switching for the Shanghai Composite Index returns.Moreover,the SERS model can indeed produce a much more realistic assessment for the regime switching process than the one obtained by the CCP model.