Normal mixture GARCH(1,1): Applications to exchange rate modelling
Normal mixture GARCH(1,1): Applications to exchange rate modelling
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DOI：
10.1002/jae.849
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发表时间：
2006-04-01
影响因子：
2.1
通讯作者：
Lazar, E
中科院分区：
文献类型：
--
作者：
Alexander, C;Lazar, E
最近的一些规格Gesthem误差过程明确假设conditionad方差，这是由正常成分的混合物，虽然有一些参数的限制。本文分析了一般的正态混合GARCH（1，1）模型，该模型能同时捕捉到条件偏度和峰度的时间变化。本文的一个主要重点是提供证据表明，对于汇率建模，广义双组分正态混合GARCH（1，1）模型的表现优于那些有三个或更多的组件，并优于对称和倾斜的学生的t-GARCH模型。除了基于模拟和三个美元汇率的历史数据的大量实证结果外，（磅、欧元和日元），导出了所有模型的条件矩和无条件矩的表达式，保证第二、第四条件矩和无条件矩为正且有限的参数条件;以及模型参数的最大似然估计和估计的标准误差的解析导数。版权所有（c）2006约翰威利父子有限公司。
Some recent specifications for GARCH error processes explicitly assume a conditionad variance that is generated by a mixture of normal components, albeit with some parameter restrictions. This paper analyses the general normal mixture GARCH(1,1) model which can capture time variation in both conditional skewness and kurtosis. A main focus of the paper is to provide evidence that, for modelling exchange rates, generalized two-component normal mixture GARCH(1,1) models perform better than those with three or more components, and better than symmetric and skewed Student's t-GARCH models. In addition to the extensive empirical results based on simulation and on historical data on three US dollar foreign exchange rates (British pound, euro and Japanese yen), we derive: expressions for the conditional and unconditional moments of all models; parameter conditions to ensure that the second and fourth conditional and unconditional moments are positive and finite; and analytic derivatives for the maximum likelihood estimation of the model parameters and standard errors of the estimates. Copyright (c) 2006 John Wiley & Sons, Ltd.