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Residual-based diagnostic tests for noninvertible ARMA models

Listed author(s):
  • Nyholm, Juho

This paper proposes two residual-based diagnostic tests for noninvertible ARMA models. The tests are analogous to the portmanteau tests developed by Box and Pierce (1970), Ljung and Box (1978) and McLeod and Li (1983) in the conventional invertible case. We derive the asymptotic chi-squared distribution for the tests and study the size and power properties in a Monte Carlo simulation study. An empirical application employing financial time series data points out the usefulness of noninvertible ARMA model in analyzing stock returns and the use of the proposed test statistics.

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File URL: https://mpra.ub.uni-muenchen.de/81033/1/MPRA_paper_81033.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 81033.

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Date of creation: Aug 2017
Handle: RePEc:pra:mprapa:81033
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  12. Jian Huang, 2000. "Quasi-likelihood Estimation of Non-invertible Moving Average Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(4), pages 689-702.
  13. Olivier Blanchard & Roberto Perotti, 2002. "An Empirical Characterization of the Dynamic Effects of Changes in Government Spending and Taxes on Output," The Quarterly Journal of Economics, Oxford University Press, vol. 117(4), pages 1329-1368.
  14. Andrews, Beth & Davis, Richard A. & Jay Breidt, F., 2006. "Maximum likelihood estimation for all-pass time series models," Journal of Multivariate Analysis, Elsevier, vol. 97(7), pages 1638-1659, August.
  15. Markku Lanne & Mika Meitz & Pentti Saikkonen, 2013. "Testing for Linear and Nonlinear Predictability of Stock Returns," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 11(4), pages 682-705, September.
  16. Kian‐Ping Lim & Robert Brooks, 2011. "The Evolution Of Stock Market Efficiency Over Time: A Survey Of The Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 69-108, February.
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