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The Study of Bayesian Clustering of Generalized Autoregressive Conditional Heteroscedasitcity

  • Journal of Knowledge Information Technology and Systems
  • Abbr : JKITS
  • 2012, 7(6), pp.245-254
  • Publisher : Korea Knowledge Information Technology Society
  • Research Area : Interdisciplinary Studies > Interdisciplinary Research
  • Published : December 31, 2012

Yoo Hee Kyung 1 정수정 2 Sung Kyung 3

1강원대학교
2(주)시벅스테크놀러지
3목원대학교

Accredited

ABSTRACT

There are many data on stocks in the stock market. They can be characterized by GARCH (,) models, specifically in this paper we assume that each stock data follows GARCH(1,1) model. This paper presents a model-based clustering method of stock data into several groups where each group has the same model and the same parameters. For the choosing the number of groups, we exploit the BIC (Bayesian Information Criterion). And the group parameters which present the characteristics of groups are estimated through Bayesian approach.

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