Maximum entropy autoregressive conditional heteroskedasticity model

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	Maximum entropy autoregressive conditional heteroskedasticity model
	Sung Y. Park ; Anil K. Bera
刊名	http://www.wise.xmu.edu.cn/paperInfor.asp?id=137
	2013-11-08
关键词	Maximum entropy density ARCH models Excess kurtosis Asymmetry Peakedness of distribution Stock returns data
英文摘要	In many applications, it has been found that the autoregressive conditional heteroskedasticity (ARCH) model under the conditional normal or Student’s t distributions are not general enough to account for the excess kurtosis in the data. Moreover, asymmetry in the financial data is rarely modeled in a systematic way. In this paper, we suggest a general density function based on the maximum entropy (ME) approach that takes account of asymmetry, excess kurtosis and also of high peakedness. The ME principle is based on the efficient use of available information, and as is well known, many of the standard family of distributions can be derived from the ME approach. We demonstrate how we can extract information functional from the data in the form of moment functions. We also propose a test procedure for selecting appropriate moment functions. Our procedure is illustrated with an application to the NYSE stock returns. The empirical results reveal that the ME approach with a fewer moment functions leads to a model that captures the stylized facts quite effectively.; This paper was published in Journal of Econometrics 150(2009) 219–230
语种	中文
内容类型	期刊论文
源URL	[http://dspace.xmu.edu.cn/handle/2288/56881]
专题	王亚南院－已发表论文
推荐引用方式 GB/T 7714	Sung Y. Park,Anil K. Bera. Maximum entropy autoregressive conditional heteroskedasticity model[J]. http://www.wise.xmu.edu.cn/paperInfor.asp?id=137,2013.
APA	Sung Y. Park,&Anil K. Bera.(2013).Maximum entropy autoregressive conditional heteroskedasticity model.http://www.wise.xmu.edu.cn/paperInfor.asp?id=137.
MLA	Sung Y. Park,et al."Maximum entropy autoregressive conditional heteroskedasticity model".http://www.wise.xmu.edu.cn/paperInfor.asp?id=137 (2013).