Testing and modeling multivariate threshold models

被引:336
作者
Tsay, RS [1 ]
机构
[1] Univ Chicago, Grad Sch Business, Chicago, IL 60637 USA
关键词
Akaike information criterion; arranged autoregression; model change; nonlinearity test; predictive residuals; recursive least squares; threshold cointegration;
D O I
10.2307/2669861
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
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 lest 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 markers 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.
引用
收藏
页码:1188 / 1202
页数:15
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