On a multivariate conditional heteroscedastic model

• 成果类型: Article
• 署名作者: Wong, H; Li, WK
• 署名单位: University of Hong Kong
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/84.1.111
• 发表日期: 1997
• 页码: 111123
• 关键词: arch; inflation

摘要

Tsay (1987) developed the conditional heteroscedastic, autoregressive moving-average model, which includes the conditional heteroscedastic autoregressive and random coefficient autoregressive models as special cases. This paper establishes the multivariate conditional heteroscedastic autoregressive moving-average model, and considers its theoretical properties and applications. Maximum likelihood estimation of the model is discussed in detail. A representation of the information matrix is obtained using the star product. This enhances estimation and statistical inferences procedures. Some simulation results and an application to the volatility of the Standard & Poor's 500 and Sydney's All Ordinaries indices are also considered.