方差伽玛分布的可加性及其在金融分析中的应用(英文)

Additivity of variance Gamma distribution and its application in financial analysis

在现代金融数据分析中,金融收益率数据的一个重要性质——在较长时间服从同一类分布——与收益率数据的其他典型特征:非对称性,尖峰厚尾,波动群聚性等有着同样的重要性.本文研究了方差伽玛分布的可加性及其在金融数据分析上的应用,并运用其验证了金融数据收益率数据满足上面的性质.作者采用贝叶斯方法对分布的参数进行了估计,并与R软件中的ghyp程序包的结果进行了比较,最后也对贝叶斯方法产生的Markov链的收敛性运用CODA软件进行了诊断.

There is an important property in today’s financial analysis ,which is that data follow a distri-bution in a longer term .Along with other topical characteristics ：asymmetry ,excess kurtosis and vola-tility clustering ,the property plays an important role .T his paper investigates the additivity of variance Gamma distribution and its application in analyzing data ,and proves the property above .Bayesian meth-od is employed for the estimation of the parameters of the distribution .T he result from Bayesian analy-sis is compared with ghyp package in software R .Extensive convergence diagnostics for the chain ob-tained from BUGS are performed by using the CODA software .