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Frequency Effects on Predictability of Stock Returns

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  • Pawe{l} Fiedor

Abstract

We propose that predictability is a prerequisite for profitability on financial markets. We look at ways to measure predictability of price changes using information theoretic approach and employ them on all historical data available for NYSE 100 stocks. This allows us to determine whether frequency of sampling price changes affects the predictability of those. We also relations between price changes predictability and the deviation of the price formation processes from iid as well as the stock's sector. We also briefly comment on the complicated relationship between predictability of price changes and the profitability of algorithmic trading.

Suggested Citation

  • Pawe{l} Fiedor, 2013. "Frequency Effects on Predictability of Stock Returns," Papers 1310.5540, arXiv.org, revised Nov 2013.
  • Handle: RePEc:arx:papers:1310.5540
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    File URL: http://arxiv.org/pdf/1310.5540
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    References listed on IDEAS

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    1. R. Steuer & L. Molgedey & W. Ebeling & M.A. Jiménez-Montaño, 2001. "Entropy and optimal partition for data analysis," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 19(2), pages 265-269, January.
    2. Lee, Chien-Chiang & Lee, Jun-De, 2009. "Energy prices, multiple structural breaks, and efficient market hypothesis," Applied Energy, Elsevier, vol. 86(4), pages 466-479, April.
    3. Xue-Zhong He & Youwei Li, 2005. "Heterogeneity, Profitability and Autocorrelations," Research Paper Series 147, Quantitative Finance Research Centre, University of Technology, Sydney.
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    Cited by:

    1. Paweł Fiedor, 2014. "Information-theoretic approach to lead-lag effect on financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 87(8), pages 1-9, August.
    2. Fiedor, Paweł, 2014. "Sector strength and efficiency on developed and emerging financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 180-188.
    3. Pawe³ Fiedor & Artur Ho³da, 2016. "The Effects Of Bankruptcy On The Predictability Of Price Formation Processes On Warsaw’S Stock Market," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 12(1), pages 32-42, June.
    4. Pawe{l} Fiedor, 2014. "Maximum Entropy Production Principle for Stock Returns," Papers 1408.3728, arXiv.org.
    5. Jacopo Rocchi & Enoch Yan Lok Tsui & David Saad, 2016. "Emerging interdependence between stock values during financial crashes," Papers 1611.02549, arXiv.org.
    6. Paweł Fiedor, 2015. "Multiscale Analysis of the Predictability of Stock Returns," Risks, MDPI, Open Access Journal, vol. 3(2), pages 1-15, June.
    7. Tao You & Paweł Fiedor & Artur Hołda, 2015. "Network Analysis of the Shanghai Stock Exchange Based on Partial Mutual Information," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 8(2), pages 1-19, June.

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