Modelling conditional heteroskedasticity and skewness using the skew-normal distribution

被引：0

作者：

Corns, Thomas ^{[1
]}

Satchell, Stephen ^{[2
,3
]}

机构：

[1] SAC Global Investors LLP, 10 Paternoster Sq, London EC4M 7EJ, England

[2] Univ Cambridge Trinity Coll, Cambridge CB2 1TQ, England

[3] Univ Sydney, Sydney, NSW 2000, Australia

来源：

METRON-INTERNATIONAL JOURNAL OF STATISTICS | 2010年 / 68卷 / 03期

关键词：

Skew-normal; Skew-symmetric; Conditional heteroskedasticity; Skewness; GARCH;

D O I：

暂无

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

The skew-normal distribution presents itself as a natural candidate for modelling conditional heteroskedasticity in financial time series since it generalises the normal distribution as a special case and departures from normality are skewed and leptokurtic. Conditional heteroskesdacity models are presented in addition to conditional skewness models. The skewness is regulated by a single parameter which is allowed to vary in an autoregressive manner. A generalisation of the GARCH-in-mean model is permitted to include the skewness parameter to capture any skewness premium in asset returns. Extensive empirical applications are applied to the FTSE Small Capitalisation Index.

引用

页码：251 / 263

页数：13

共 21 条

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