一个新的稳健ARCH检验和YJ-GARCH模型
李海奇
厦门大学王亚南经济研究院
S.Y.Park
香港中文大学经济系
5/23/2011 5:08:04 PM
摘要:
众所周知,Engle (1982) 的ARCH检验对于条件均值模型误设并不稳健,特别地,当条件均值是非线性过程而我们仅对之建立线性模型时,它过度地拒绝真实的原假设,导致出现严重的水平扭曲 (size distortion)。因此,本文在文献当中首次利用Yeo-Johnson变换方法来转换均值模型的因变量以排除ARCH 过程中均值部分的非线性,进而提出一个新的稳健ARCH检验以及一个新的GARCH模型——Yeo-Johnson (YJ) GARCH模型。蒙特卡罗模拟结果表明,稳健的ARCH检验在水平 (size) 和势 (power) 方面的表现要显著优于Engle (1982) 的ARCH检验。对上证综指收益率的实证研究结果表明,YJ-GARCH模型的拟合效果要显著优于线性GARCH模型。
关键词: 
稳健ARCH检验; Yeo-Johnson变换; YJ-GARCH模型;水平扭曲
Abstract:
It is quite well known that Engle (1982)’s ARCH test is not robust to misspecification of the conditional mean model. Especially, when the conditional mean is nonlinear process and we model it by a linear model, it rejects the true null hypothesis too often and thus causes the serious size distortion. This paper proposes a new robust ARCH test using the Yeo-Johnson transformation in which the dependent variable is transformed to deal with nonlinearity. This alternative model specification yields a new GARCH model, i.e. Yeo-Johnson (YJ) GARCH by product. The Monte Carlo simulation results show that the robust ARCH test is significantly superior to Engle (1982)’s ARCH test in terms of the size and power. Empirical application to the returns of Shanghai Composite index illustrates that the goodness-of-fit for YJ-GARCH model is clearly better than the linear GARCH model.
Keyword: 
Robust ARCH Test, Yeo-Johnson Transformation, YJ-GARCH Model, Size Distortion