Advanced Search
MyIDEAS: Login to save this paper or follow this series

Dynamical Models of Stock Prices Based on Technical Trading Rules Part III: Application to Hong Kong Stocks

Contents:

Author Info

  • Li-Xin Wang
Registered author(s):

    Abstract

    In Part III of this paper, we apply the price dynamical model with big buyers and big sellers developed in Part I of this paper to the daily closing data of the top 20 stocks in Hang Seng Index in Hong Kong Stock Exchange. The basic idea is to estimate the strength parameters of the big buyers and the big sellers in the model and make buy/sell decisions based on these parameter estimates. We develop two trading strategies: (i) Follow-the-Big-Buyer which buys when big buyer begins to appear and there is no sign of big sellers, holds the stock as long as the big buyer is still there, and sells all holdings of this stock once the big buyer disappears; and (ii) Ride-the-Mood which buys as soon as the big buyer strength begins to surpass the big seller strength and sells all holdings of the stock once the big seller strength is larger than the big buyer strength. Based on the testing over 198 two-year intervals uniformly distributed across the six-year period from 03-July-2007 to 28-June-2013 which includes a variety of scenarios, the net profits would increase 47% or 64% on average if an investor switched from the benchmark Buy-and-Hold strategy to the Follow-the-Big-Buyer or Ride-the-Mood strategies during this period, respectively.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://arxiv.org/pdf/1401.1892
    File Function: Latest version
    Download Restriction: no

    Bibliographic Info

    Paper provided by arXiv.org in its series Papers with number 1401.1892.

    as in new window
    Length:
    Date of creation: Jan 2014
    Date of revision:
    Handle: RePEc:arx:papers:1401.1892

    Contact details of provider:
    Web page: http://arxiv.org/

    Related research

    Keywords:

    This paper has been announced in the following NEP Reports:

    References

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
    as in new window
    1. Andrei A. Kirilenko & Andrew W. Lo, 2013. "Moore's Law versus Murphy's Law: Algorithmic Trading and Its Discontents," Journal of Economic Perspectives, American Economic Association, American Economic Association, vol. 27(2), pages 51-72, Spring.
    2. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, American Finance Association, vol. 25(2), pages 383-417, May.
    3. Menkhoff, Lukas, 2010. "The use of technical analysis by fund managers: International evidence," Journal of Banking & Finance, Elsevier, Elsevier, vol. 34(11), pages 2573-2586, November.
    4. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, American Finance Association, vol. 55(4), pages 1705-1770, 08.
    5. Andrew W. Lo, 2012. "Reading about the Financial Crisis: A Twenty-One-Book Review," Journal of Economic Literature, American Economic Association, American Economic Association, vol. 50(1), pages 151-78, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:arx:papers:1401.1892. 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: (arXiv administrators).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 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.