[1]汤丹,赵昕东.应用Gibbs Sampler的GARCH模型选择[J].华侨大学学报(自然科学版),2011,32(4):443-446.[doi:10.11830/ISSN.1000-5013.2011.04.0443]
　TANG Dan,ZHAO Xin-dong.GARCH Model Selecion Based on Gibbs Sampler[J].Journal of Huaqiao University(Natural Science),2011,32(4):443-446.[doi:10.11830/ISSN.1000-5013.2011.04.0443]
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应用Gibbs Sampler的GARCH模型选择()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第32卷
期数:
2011年第4期
页码:
443-446
栏目:
出版日期:
2011-07-20

文章信息/Info

Title:
GARCH Model Selecion Based on Gibbs Sampler
文章编号:
1000-5013(2011)04-0443-04
作者:
汤丹; 赵昕东
华侨大学数量经济研究院
Author(s):
TANG Dan;  ZHAO Xin-dong
College of Economics and Finance, Huaqiao University, Quanzhou 362021, China
关键词:
广义自回归条件异方差模型模型;  Gibbs样本生成器;  准则值;  参数估计
Keywords:
generalized auto-regressive conditional heteroskedasticity model;  Gibbs sampler;  criterion value;  parameter estimation
分类号:
O211.62
DOI:
10.11830/ISSN.1000-5013.2011.04.0443
文献标志码:
A
摘要:
为了解决候选模型较多,无法一一比较其准则值的问题,提出基于Gibbs样本生成器(Gibbs sampler)的广义自回归条件异方差(GARCH)模型的选择方法.模拟实验结果表明:该模型选择方法可以高效、准确地从大量的候选模型中选择出准则值最小的模型.
Abstract:
In order to solve the problem of more candidate models that we can′t compare the criterion values one by one,we put forward a selecting method of the GARCH(generalized auto-regressive conditional heteroskedasticity) model based on Gibbs sampler.The method estabish a connection between criterion values of candidate models and probabilities of candidate models.When the number of the models generated becomes large enough,the model with the lowest criterion value will tend to appear early and frequently.The result shows that we can choose the model with the lowest criterion value,accurately and efficiently,from the candidate models.

参考文献/References:

[1] CLAYTON M K, GEISSER S, JENNINGS D E. A comparison of several model selection procedures [A]. New York:Elsevier Science Publishing Company, 1986.199-212.
[2] GRANGER C J W, KING M L, WHITE H. Comments on the testing economic theries and the use of model selection criteria [J]. Journal of Econometrics, 1995(1):173-187.doi:10.1016/0304-4076(94)01632-A.
[3] VERHOFEN M. Markov Chain Monte Carlo methods in financial econometrics [J]. Swiss Society for Financial Market Research, 2005(4):397-340.
[4] CMASELLA G, GEORGE E I. Explaining the Gibbs sampler [J]. American Statistician, 1992(3):167-174.
[5] 赵昕东, 耿鹏. 基于Gibbs Sampler的线性回归模型选择 [J]. 宁波大学学报(人文科学版), 2009(4):89-93.doi:10.3969/j.issn.1001-5124.2009.04.015.
[6] 赵昕东, 钱国骐. 基于吉伯斯样本生成器的向量自回归模型选择 [J]. 统计研究, 2008(1):86-92.doi:10.3969/j.issn.1002-4565.2008.01.018.
[7] 赵昕东. 基于蒙特卡洛-马尔科夫链(MCMC)的ARMA模型选择 [J]. 数理统计与管理, 2006(2):161-165.doi:10.3969/j.issn.1002-1566.2006.02.007.
[8] GILKS W R, RICHARDSON S, SPIEGELHALTER D J. Intwducing Markov Chain Monte Carlo [M]. London:Chapman and Hall Press, 1996.1-17.

备注/Memo

备注/Memo:
福建省自然科学基金资助项目(2009J01312)
更新日期/Last Update: 2014-03-23