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The Epps effect revisited

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  • Bence Toth
  • Janos Kertesz

Abstract

We analyse the dependence of stock return cross-correlations on the data sampling frequency, known as the Epps effect: for high-resolution data the cross-correlations are significantly smaller than their asymptotic value as observed for daily data. The former description implies that a changing trading frequency should alter the characteristic time of the phenomenon. This is not true for empirical data: the Epps curves do not scale with market activity. The latter result indicates that the time scale of the phenomenon is related to the reaction time of market participants (this we denote as the human time scale), independent of market activity. In this paper we give a new description of the Epps effect through the decomposition of cross-correlations. After testing our method on a model of generated random walk price changes we justify our analytical results by fitting the Epps curves of real-world data.

Suggested Citation

  • Bence Toth & Janos Kertesz, 2009. "The Epps effect revisited," Quantitative Finance, Taylor & Francis Journals, vol. 9(7), pages 793-802.
    • Handle: RePEc:taf:quantf:v:9:y:2009:i:7:p:793-802
    DOI: 10.1080/14697680802595668
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    References listed on IDEAS

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    1. Neil Shephard & Ole E. Barndorff-Nielsen & Department of Mathematical Sciences & University of Aarhus & Denmark, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," Economics Series Working Papers 240, University of Oxford, Department of Economics.
    2. Gençay, Ramazan & Dacorogna, Michel & Muller, Ulrich A. & Pictet, Olivier & Olsen, Richard, 2001. "An Introduction to High-Frequency Finance," Elsevier Monographs, Elsevier, edition 1, number 9780122796715.
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    Cited by:

    1. Stanisław Drożdż & Ludovico Minati & Paweł Oświȩcimka & Marek Stanuszek & Marcin Wa̧torek, 2019. "Signatures of the Crypto-Currency Market Decoupling from the Forex," Future Internet, MDPI, vol. 11(7), pages 1-18, July.
    2. Nicolas Huth & Frédéric Abergel, 2012. "The times change: multivariate subordination, empirical facts," Post-Print hal-00620841, HAL.
    3. Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Marcin Wk{a}torek, 2023. "What is mature and what is still emerging in the cryptocurrency market?," Papers 2305.05751, arXiv.org.
    4. Stanis{l}aw Dro.zd.z & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek & Marcin Wk{a}torek, 2019. "Signatures of crypto-currency market decoupling from the Forex," Papers 1906.07834, arXiv.org, revised Jul 2019.
    5. Iacopo Mastromatteo & Matteo Marsili & Patrick Zoi, 2010. "Financial correlations at ultra-high frequency: theoretical models and empirical estimation," Papers 1011.1011, arXiv.org, revised Feb 2011.
    6. Gabriele La Spada & J. Doyne Farmer & Fabrizio Lillo, 2010. "Tick size and price diffusion," Papers 1009.2329, arXiv.org, revised Oct 2010.
    7. Nicolas Huth & Frédéric Abergel, 2010. "High frequency correlation modelling," Post-Print hal-00621244, HAL.
    8. Henryk Gurgul & Artur Machno, 2017. "The impact of asynchronous trading on Epps effect on Warsaw Stock Exchange," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(2), pages 287-301, June.
    9. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.

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