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On the applicability of the Lead/Lag Ratio in causality assessment

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  • Zanin, Massimiliano
  • Belkoura, Seddik

Abstract

Within the large set of metrics that have been proposed to assess the presence of a causality relationship between time series, the Lead/Lag Ratio (LLR) has recently attracted increasing attention, especially in the econophysics community. It is based on the analysis of the asymmetry between the correlations obtained when one time series is shifted back or ahead in time with respect to the second one; or, in other words, on the assessment of whether one time series is leading the other. In spite of its popularity, undoubtedly due to its conceptual and computational simplicity, no empirical validation of the LLR has hitherto been proposed. We here take a first step towards this validation, by presenting results corresponding to a large set of analyses on synthetic time series, and comparing them with those yielded by the celebrated Granger Causality metric. We show how, in spite of behaving similarly to the Granger Causality in some specific situations, the LLR presents important drawbacks, among which its unreliableness and the absence of a statistical significance test stand out, that discourage its use in real-world analyses.

Suggested Citation

  • Zanin, Massimiliano & Belkoura, Seddik, 2018. "On the applicability of the Lead/Lag Ratio in causality assessment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 186-196.
    • Handle: RePEc:eee:phsmap:v:506:y:2018:i:c:p:186-196
    DOI: 10.1016/j.physa.2018.04.076
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    References listed on IDEAS

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    1. Granger, C. W. J., 1988. "Causality, cointegration, and control," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 551-559.
    2. Chester Curme & Michele Tumminello & Rosario N. Mantegna & H. Eugene Stanley & Dror Y. Kenett, 2015. "Emergence of statistically validated financial intraday lead-lag relationships," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1375-1386, August.
    3. Mantegna,Rosario N. & Stanley,H. Eugene, 2007. "Introduction to Econophysics," Cambridge Books, Cambridge University Press, number 9780521039871, September.
    4. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Hamad Alsayed & Frank McGroarty, 2014. "Ultra‐High‐Frequency Algorithmic Arbitrage Across International Index Futures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 391-408, September.
    5. Buerhan Saiti, 2017. "The Lead-Lag Relationship among East Asian Economies: A Wavelet Analysis," International Business Research, Canadian Center of Science and Education, vol. 10(3), pages 57-68, March.
    6. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    7. Franck Jovanovic & Christophe Schinckus, 2013. "The Emergence of Econophysics: A New Approach in Modern Financial Theory," History of Political Economy, Duke University Press, vol. 45(3), pages 443-474, Fall.
    8. Granger, C. W. J., 1988. "Some recent development in a concept of causality," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 199-211.
    9. Franck Jovanovic & Christophe Schinckus, 2017. "Econophysics and Financial Economics," Post-Print hal-03541391, HAL.
    10. Geweke, John, 1984. "Inference and causality in economic time series models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 19, pages 1101-1144, Elsevier.
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