On Mixture Memory GARCH Models

CORC > 厦门大学 > 王亚南院－已发表论文

	On Mixture Memory GARCH Models
	Muyi Li ; Wai Keung Li ; Guodong Li
刊名	http://www.wise.xmu.edu.cn/paperInfor.asp?id=288
	2013-11-08
关键词	long memory in volatility covariance stationarity mixture ARCH(∞) EM algorithm.
英文摘要	We propose a new volatility model, which is called the mixture memory GARCH (MM-GARCH) model. The MM-GARCH model has two mixture components, of which one is a short memory GARCH and the other is the long memory FIGARCH. The new model, a special ARCH(∞) process with random coefficients, possesses both the properties of long memory volatility and covariance stationarity. The existence of its stationary solution is discussed. A dynamic mixture of the proposed model is also introduced. Other issues, such as the EM algorithm as a parameter estimation procedure, the observed information matrix which is relevant in calculating the theoretical standard errors, and a model selection criterion are also investigated. Monte Carlo experiments demonstrate our theoretical findings. Empirical application of the MM-GARCH model to the daily S&P 500 index illustrates its capabilities. ; This paper is accepted by Journal of Time Series Analysis.
语种	中文
内容类型	期刊论文
源URL	[http://dspace.xmu.edu.cn/handle/2288/56920]
专题	王亚南院－已发表论文
推荐引用方式 GB/T 7714	Muyi Li,Wai Keung Li,Guodong Li. On Mixture Memory GARCH Models[J]. http://www.wise.xmu.edu.cn/paperInfor.asp?id=288,2013.
APA	Muyi Li,Wai Keung Li,&Guodong Li.(2013).On Mixture Memory GARCH Models.http://www.wise.xmu.edu.cn/paperInfor.asp?id=288.
MLA	Muyi Li,et al."On Mixture Memory GARCH Models".http://www.wise.xmu.edu.cn/paperInfor.asp?id=288 (2013).