Testing and modeling multivariate threshold models
Testing and modeling multivariate threshold models
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DOI：
10.1080/01621459.1998.10473779
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发表时间：
1998-09
影响因子：
3.7
通讯作者：
R. Tsay
中科院分区：
文献类型：
--
作者：
R. Tsay
摘要门限自回归模型的过程在门限空间中是分段线性的，近年来受到了广泛的关注。本文利用预测残差构造了检测向量时间序列中门限非线性的检验统计量，并提出了一种建立多元门限模型的方法。阈值和模型是基于Akaike信息准则联合选取的。通过仿真研究了该测试的有限样本性能。然后，该建模过程被用来研究证券市场上的套利行为，并在对合约的持有成本进行调整后，得出期货合约的对数与证券现货价格之间的门限协整关系。在这个特定的应用中，阈值部分由交易成本决定。我还将建议的程序应用于美国的月利率和冰岛的两个河流流量序列。
Abstract Threshold autoregressive models in which the process is piecewise linear in the threshold space have received much attention in recent years. In this article I use predictive residuals to construct a test statistic for detecting threshold nonlinearity in a vector time series and propose a procedure for building a multivariate threshold model. The thresholds and the model are selected jointly based on the Akaike information criterion. The finite-sample performance of the proposed test is studied by simulation. The modeling procedure is then used to study arbitrage in security markets and results in a threshold cointegration between logarithms of future contracts and spot prices of a security after adjusting for the cost of carrying the contracts. In this particular application, thresholds are determined in part by the transaction costs. I also apply the proposed procedure to U.S. monthly interest rates and two river flow series of Iceland.