IDEAS home Printed from https://ideas.repec.org/p/stz/wpaper/eth-rc-11-005.html
   My bibliography  Save this paper

Strategies used as Spectroscopy of Financial Markets Reveal New Stylized Facts

Author

Listed:
  • Wei-Xing Zhou
  • Guo-Hua Mu
  • Si-Wei Chen
  • Didier Sornette

    ()

Abstract

We propose a new set of stylized facts quantifying the structure of financial markets. The key idea is to study the combined structure of both investment strategies and prices in order to open a qualitatively new level of understanding of financial and economic markets. We study the detailed order flow on the Shenzhen Stock Exchange of China for the whole year of 2003. This enormous dataset allows us to compare (i) a closed national market (A-shares) with an international market (B-shares), (ii) individuals and institutions and (iii) real traders to random strategies with respect to timing that share otherwise all other characteristics. We find in general that more trading results in smaller net return due to trading frictions, with the exception that the net return is independent of the trading frequency for A-share individual traders. We unveiled quantitative power laws with non-trivial exponents, that quantify the deterioration of performance with frequency and with holding period of the strategies used by traders. Random strategies are found to perform much better than real ones, both for winners and losers. Surprising large arbitrage opportunities exist, especially when using zero-intelligence strategies. This is a diagnostic of possible inefficiencies of these financial markets.

Suggested Citation

  • Wei-Xing Zhou & Guo-Hua Mu & Si-Wei Chen & Didier Sornette, "undated". "Strategies used as Spectroscopy of Financial Markets Reveal New Stylized Facts," Working Papers ETH-RC-11-005, ETH Zurich, Chair of Systems Design.
  • Handle: RePEc:stz:wpaper:eth-rc-11-005
    as

    Download full text from publisher

    File URL: ftp://web.sg.ethz.ch/RePEc/stz/wpaper/pdf/ETH-RC-11-005.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Gao-Feng Gu & Wei Chen & Wei-Xing Zhou, 2006. "Quantifying bid-ask spreads in the Chinese stock market using limit-order book data: Intraday pattern, probability distribution, long memory, and multifractal nature," Papers physics/0701017, arXiv.org, revised Mar 2007.
    2. Gervais, Simon & Odean, Terrance, 2001. "Learning to be Overconfident," Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 1-27.
    3. Donald MacKenzie, 2008. "An Engine, Not a Camera: How Financial Models Shape Markets," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262633671, January.
    4. J. Doyne Farmer, 2002. "Market force, ecology and evolution," Industrial and Corporate Change, Oxford University Press, vol. 11(5), pages 895-953, November.
    5. Terrance Odean, 1998. "Volume, Volatility, Price, and Profit When All Traders Are Above Average," Journal of Finance, American Finance Association, vol. 53(6), pages 1887-1934, December.
    6. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    7. C. H. Hommes, 2001. "Financial markets as nonlinear adaptive evolutionary systems," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 149-167.
    8. Biais, Bruno & Hillion, Pierre & Spatt, Chester, 1995. " An Empirical Analysis of the Limit Order Book and the Order Flow in the Paris Bourse," Journal of Finance, American Finance Association, vol. 50(5), pages 1655-1689, December.
    9. Brad M. Barber & Terrance Odean & Ning Zhu, 2009. "Do Retail Trades Move Markets?," Review of Financial Studies, Society for Financial Studies, vol. 22(1), pages 151-186, January.
    10. Glaser, Markus & Weber, Martin, 2009. "Which past returns affect trading volume?," Journal of Financial Markets, Elsevier, vol. 12(1), pages 1-31, February.
    11. Laurent Barras & Olivier Scaillet & Russ Wermers, 2010. "False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas," Journal of Finance, American Finance Association, vol. 65(1), pages 179-216, February.
    12. J. B. Satinover & D. Sornette, 2007. "”Illusion of control” in Time-Horizon Minority and Parrondo Games," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 60(3), pages 369-384, December.
    13. Satinover, J.B. & Sornette, D., 2007. "Illusion of control in a Brownian game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 386(1), pages 339-344.
    14. Brad M. Barber & Terrance Odean, 2000. "Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors," Journal of Finance, American Finance Association, vol. 55(2), pages 773-806, April.
    15. Markus Glaser & Martin Weber, 2007. "Overconfidence and trading volume," The Geneva Papers on Risk and Insurance Theory, Springer;International Association for the Study of Insurance Economics (The Geneva Association), vol. 32(1), pages 1-36, June.
    16. LeBaron, Blake & Arthur, W. Brian & Palmer, Richard, 1999. "Time series properties of an artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1487-1516, September.
    17. Gode, Dhananjay K & Sunder, Shyam, 1993. "Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality," Journal of Political Economy, University of Chicago Press, vol. 101(1), pages 119-137, February.
    18. Ehrentreich, Norman, 2006. "Technical trading in the Santa Fe Institute Artificial Stock Market revisited," Journal of Economic Behavior & Organization, Elsevier, vol. 61(4), pages 599-616, December.
    19. Meir Statman & Steven Thorley & Keith Vorkink, 2006. "Investor Overconfidence and Trading Volume," Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1531-1565.
    20. Robert Kosowski & Allan Timmermann & Russ Wermers & Hal White, 2006. "Can Mutual Fund "Stars" Really Pick Stocks? New Evidence from a Bootstrap Analysis," Journal of Finance, American Finance Association, vol. 61(6), pages 2551-2595, December.
    21. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    22. Alexander Ljungqvist & Christopher Malloy & Felicia Marston, 2009. "Rewriting History," Journal of Finance, American Finance Association, vol. 64(4), pages 1935-1960, August.
    23. Richard Deaves & Erik Lüders & Guo Ying Luo, 2009. "An Experimental Test of the Impact of Overconfidence and Gender on Trading Activity," Review of Finance, European Finance Association, vol. 13(3), pages 555-575.
    24. Terrance Odean, 1999. "Do Investors Trade Too Much?," American Economic Review, American Economic Association, vol. 89(5), pages 1279-1298, December.
    25. J. B. Satinover & D. Sornette, 2009. "Illusory versus genuine control in agent-based games," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 67(3), pages 357-367, February.
    26. Eugene F. Fama & Kenneth R. French, 2010. "Luck versus Skill in the Cross-Section of Mutual Fund Returns," Journal of Finance, American Finance Association, vol. 65(5), pages 1915-1947, October.
    27. Brad M. Barber & Yi-Tsung Lee & Yu-Jane Liu & Terrance Odean, 2009. "Just How Much Do Individual Investors Lose by Trading?," Review of Financial Studies, Society for Financial Studies, vol. 22(2), pages 609-632, February.
    Full references (including those not matched with items on IDEAS)

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:stz:wpaper:eth-rc-11-005. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Claudio J. Tessone). General contact details of provider: http://edirc.repec.org/data/dmethch.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.