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Price clustering and discreteness: is there chaos behind the noise?

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  • Antoniou, Antonios
  • Vorlow, Constantinos E.

Abstract

We investigate the “compass rose” patterns introduced by Crack and Ledoit (J. Finance 51(2)(1996) 751) as revealed in phase portraits (delay plots) of stock returns. The structures observed in these diagrams have been attributed mainly to price clustering and discreteness and the tick size. Using wavelet-based denoising, we examine the noise-free versions of a set of FTSE100 stock returns time series. We reveal evidence of non-periodic cyclical dynamics. As a second stage we apply surrogate data analysis on the original and denoised stock returns. Our results suggest that there is a strong nonlinear and possibly deterministic signature in the data generating processes of the stock returns sequences.

Suggested Citation

  • Antoniou, Antonios & Vorlow, Constantinos E., 2005. "Price clustering and discreteness: is there chaos behind the noise?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 348(C), pages 389-403.
  • Handle: RePEc:eee:phsmap:v:348:y:2005:i:c:p:389-403
    DOI: 10.1016/j.physa.2004.09.006
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Viviana Fernandez & Brian M Lucey, 2006. "Portfolio management implications of volatility shifts: Evidence from simulated data," Documentos de Trabajo 219, Centro de Economía Aplicada, Universidad de Chile.
    2. Fernandez, Viviana & Lucey, Brian M., 2007. "Portfolio management under sudden changes in volatility and heterogeneous investment horizons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 612-624.
    3. repec:spt:apfiba:v:7:y:2017:i:4:f:7_4_2 is not listed on IDEAS
    4. Emmanuel Haven & Xiaoquan Liu & Chenghu Ma & Liya Shen, 2013. "Revealing the Implied Risk-neutral MGF with the Wavelet Method," WISE Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    5. Chakrabarty, Anindya & De, Anupam & Gunasekaran, Angappa & Dubey, Rameshwar, 2015. "Investment horizon heterogeneity and wavelet: Overview and further research directions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 45-61.
    6. Leontitsis, Alexandros & Vorlow, Constantinos E., 2006. "Accounting for outliers and calendar effects in surrogate simulations of stock return sequences," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 368(2), pages 522-530.
    7. Münnix, Michael C. & Schäfer, Rudi & Guhr, Thomas, 2010. "Impact of the tick-size on financial returns and correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4828-4843.
    8. Marisa Faggini, 2011. "Chaotic Time Series Analysis in Economics: Balance and Perspectives," Working papers 25, Former Department of Economics and Public Finance "G. Prato", University of Torino.
    9. Mitchell, Heather & McKenzie, Michael D., 2006. "A note on the Wang and Wang measure of the quality of the compass rose," Journal of Banking & Finance, Elsevier, vol. 30(12), pages 3519-3524, December.
    10. Haven, Emmanuel & Liu, Xiaoquan & Ma, Chenghu & Shen, Liya, 2009. "Revealing the implied risk-neutral MGF from options: The wavelet method," Journal of Economic Dynamics and Control, Elsevier, vol. 33(3), pages 692-709, March.

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