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A misspecification test for multiplicative error models of non-negative time series processes

机译:非负时间序列过程的乘法误差模型的误判测试

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摘要

In recent years, analysis of financial time series focuses largely on data related to market trading activity. Apart from modeling of the conditional variance of returns within the generalized autoregressive conditional heteroskedasticity (GARCH) family of models, presently attention is also devoted to that of other market variables, for instance volumes, number of trades or financial durations. To this end, a large group of researchers focus their studies on a class of model that is referred to in the literature as the multiplicative error model (MEM), which is considered particularly for modeling non-negative time series processes. The goal of the current paper is to establish an alternative misspecification test for the MEM of non-negative time series processes. In the literature, although several procedures are available to perform hypothesis testing for the MEM, the newly proposed testing procedure is particularly useful in the context of the MEM of waiting times between financial events since its outcomes have a number of important implications on the fundamental concept of point processes. Finally, the current paper makes a number of statistical contributions, especially in making a head way into nonparametric hypothesis testing of unobservable variables. (C) 2015 Elsevier B.V. All rights reserved.
机译:近年来,对金融时间序列的分析主要集中在与市场交易活动有关的数据上。除了在广义自回归条件异方差(GARCH)模型系列中对收益的条件方差建模之外,目前还关注其他市场变量,例如交易量,交易数量或财务期限。为此,大量研究人员将研究重点放在一类模型上,该模型在文献中被称为乘性误差模型(MEM),该模型尤其被认为是用于对非负时间序列过程进行建模。本文的目的是为非负时间序列过程的MEM建立替代的错误规范测试。在文献中,尽管有几种程序可用于对MEM进行假设检验,但是新提出的测试程序在MEM财务事件之间等待时间的上下文中特别有用,因为其结果对基本概念有许多重要影响点过程。最后,本论文做出了许多统计贡献,特别是在对不可观察变量进行非参数假设检验方面取得了进展。 (C)2015 Elsevier B.V.保留所有权利。

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