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Spurious regression due to neglected of non-stationary volatility

Author

Listed:
  • Hao Jin

    (Xi’an University of Science and Technology)

  • Si Zhang

    (Xi’an University of Science and Technology)

  • Jinsuo Zhang

    (Yan’an University)

Abstract

This paper examines the effects of permanent changes in the variance of the errors on routine applications of standard t-ratio test in regression models. It is shown the asymptotic distribution of t-ratio test is not invariant to non-stationary in variance, and the phenomenon of spurious regression will occur independently of the structure assumed for these time series. The intuition behind this is that the non-stationary volatility can increase persistency in the level of regression errors, which then leads to spurious correlation. Monte Carlo experiment evidence indicates that, in contrast to the broken level/trend case, the presence of spurious relationship critically depends on the location and magnitude of changes, regardless of the sample size. Finally, some real data sets from the Shanghai stock database are reported for illustration.

Suggested Citation

  • Hao Jin & Si Zhang & Jinsuo Zhang, 2017. "Spurious regression due to neglected of non-stationary volatility," Computational Statistics, Springer, vol. 32(3), pages 1065-1081, September.
    • Handle: RePEc:spr:compst:v:32:y:2017:i:3:d:10.1007_s00180-016-0687-x
    DOI: 10.1007/s00180-016-0687-x
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    Cited by:

    1. Si Zhang & Hao Jin & Menglin Su, 2024. "Modified Block Bootstrap Testing for Persistence Change in Infinite Variance Observations," Mathematics, MDPI, vol. 12(2), pages 1-25, January.

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