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LSTUR regression theory and the instability of the sample correlation coefficient between financial return indices

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  • Tim Ginker
  • Offer Lieberman

Abstract

SummaryIt is well known that the sample correlation coefficient between many financial return indices exhibits substantial variation on any reasonable sampling window. This stylised fact contradicts a unit root model for the underlying processes in levels, as the statistic converges in probability to a constant under this modeling scheme. In this paper, we establish asymptotic theory for regression in local stochastic unit root (LSTUR) variables. An empirical application reveals that the new theory explains very well the instability, in both sign and scale, of the sample correlation coefficient between gold, oil, and stock return price indices. In addition, we establish spurious regression theory for LSTUR variables, which generalises the results known hitherto, as well as a theory for balanced regression in this setting.

Suggested Citation

  • Tim Ginker & Offer Lieberman, 2021. "LSTUR regression theory and the instability of the sample correlation coefficient between financial return indices," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 58-82.
    • Handle: RePEc:oup:emjrnl:v:24:y:2021:i:1:p:58-82.
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    File URL: http://hdl.handle.net/10.1093/ectj/utaa011
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