摘要
通过选取不同的分布对自回归条件极差模型进行了改进,选择GARCH模型对对数收益率的波动率进行了建模,运用贝叶斯对两种模型中的参数进行分析.通过用沪深300指数数据进行实证分析,WinBUGS软件对两种模型当中的参数进行仿真,由参数估计值分析得到,自回归条件极差模型对波动短期效应有更好的捕捉能力,而GARCH模型优势在长期效应.
In 2005,Chou suggested an approach to conduct the volatility analysis by use of the Auto-regressive Range Model,yet the model was blame for its deficiencies found in the distribution assumptions of logarithmic mean value.By selection of different distributions,improvements were made to the model.By contrast,modeling was made of the volatility rate of the logarithmic return rate by selection of the GARCH Model and by use of Bayesian the parameters of the two models were subjected to a parameter analysis and an empirical analysis was done by taking advantage of the SCI300 index data;and a parameter simulation was also done to the two models by WinBugs.By means of the analysis of the parameter estimates it was concluded that the Auto-Regressive Model is of a better performance in capturing the short-term effects while the GARCH Model is better at capturing the long-term effects.
出处
《内江师范学院学报》
2015年第4期9-13,共5页
Journal of Neijiang Normal University
作者简介
王亮（1988-），男，山西长治人，四川大学研究生．研究方向：金融数学
