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Testing for non-linear and time irreversible probabilistic structure in high frequency financial time series data

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  • Phillip Wild
  • John Foster
  • Melvin. J. Hinich

Abstract

type="main" xml:id="rssa12037-abs-0001"> We present three non-parametric trispectrum tests that can establish whether the spectral decomposition of kurtosis of high frequency financial asset price time series is consistent with the assumptions of Gaussianity, linearity and time reversiblility. The detection of non-linear and time irreversible probabilistic structure has important implications for the choice and implementation of a range of models of the evolution of asset prices, including Black–Scholes–Merton option pricing model, auto-regressive conditional heteroscedastic or generalized auto-regressive conditional heteroscedastic and stochastic volatility models. We apply the tests to a selection of high frequency Australian stocks.

Suggested Citation

  • Phillip Wild & John Foster & Melvin. J. Hinich, 2014. "Testing for non-linear and time irreversible probabilistic structure in high frequency financial time series data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 177(3), pages 643-659, June.
    • Handle: RePEc:bla:jorssa:v:177:y:2014:i:3:p:643-659
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    File URL: http://hdl.handle.net/10.1111/rssa.2014.177.issue-3
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    Cited by:

    1. Shibin Zhang, 2023. "A copula spectral test for pairwise time reversibility," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(5), pages 705-729, October.

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