A bootstrapped spectral test for adequacy in weak ARMA models

Ke Zhu () and Wai Keung Li

Journal of Econometrics, 2015, vol. 187, issue 1, 113-130

Abstract: This paper proposes a Cramér–von Mises (CM) test statistic to check the adequacy of weak ARMA models. Without posing a martingale difference assumption on the error terms, the asymptotic null distribution of the CM test is obtained. Moreover, this CM test is consistent, and has nontrivial power against the local alternative of order n−1/2. Due to the unknown dependence of error terms and the estimation effects, a new block-wise random weighting method is constructed to bootstrap the critical values of the test statistic. The new method is easy to implement and its validity is justified. The theory is illustrated by a small simulation study and an application to S&P 500 stock index.

Keywords: Block-wise random weighting method; Diagnostic checking; Least squares estimation; Spectral test; Weak ARMA models; Wild bootstrap (search for similar items in EconPapers)
JEL-codes: C01 C12 C22 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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Working Paper: A bootstrapped spectral test for adequacy in weak ARMA models (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:187:y:2015:i:1:p:113-130

DOI: 10.1016/j.jeconom.2015.02.005

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