Using Hidden Markov Switching-Mixed Normal Distribution Model to Study the Distribution of Chinese Stock Index Returns

摘要：

Understanding the distribution of financial asset returns is critical for investment and risk management. The traditional assumption of normal distribution does not well describe the skewness and kurtosis of log returns. Most of the currently proposed return distribution models lack the capability to allow time-varying distribution. Thus in this paper, we introduce Markov switching structure into the distribution of Chinese stock index returns, propose the hidden Markov switching-mixed normal distribution(HMS-MND) model, and give the Expectation-Maximization(EM) algorithm for model parameter estimation. The log daily and weekly returns on the major stock indexes of Shanghai stock exchange are used for empirical tests. Parameter estimates as well as likelihood ratio test results show that, the introduction of Markov switching structure could significantly improve the models fitting capability. It is also shown that HMS-MND model could well describe the statistics of stock index log returns. Therefore, we argue that using hidden Markov switching-mixed normal distribution model to study the distribution of Chinese stock index returns is of practical value.

作者: Hui Qu Honghai Yu

作者单位: School of Management and Engineering Nanjing University Nanjing, China

会议类型: 国际会议

会议名称: International Conference on Management and Service Science(2011年第五届管理与服务科学国际会议 MASS 2011)

会议地点: 武汉

会议语种:英文

页码: 1-4

在线出版日期: 2011-08-12（万方平台首次上网日期，不代表论文的发表时间）