IDEAS home Printed from https://ideas.repec.org/a/afj/journl/v13y2011i1p14-27.html
   My bibliography  Save this article

Predictability of Stock Price Behaviour in South Africa: A Non-Parametric Approach

Author

Listed:
  • John Mwamba

    (University of Johannesburg, South Africa)

Abstract

This paper investigates the forecasting power of stock prices using two methods, namely, the random walk and the non-parametric methods. Using daily prices of the FTSE/JSE All Share index it is found that non-parametric methodology reveals distributional behaviour in the time series that is not captured by the random walk model. Based on the out-of-sample predicted mean square error, the F-test for two variances (those of both the observed series and the predicted one) and the bootstrap confidence interval and volatility, this method predicts the future behaviour of stock prices more accurately than the traditional random walk model has done.

Suggested Citation

  • John Mwamba, 2011. "Predictability of Stock Price Behaviour in South Africa: A Non-Parametric Approach," The African Finance Journal, Africagrowth Institute, vol. 13(1), pages 14-27.
    • Handle: RePEc:afj:journl:v:13:y:2011:i:1:p:14-27
    as

    Download full text from publisher

    File URL: http://www.journals.co.za/ej/ejour_finj.html
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Muteba Mwamba, John & Mhlanga, Isaah, 2013. "Extreme conditional value at risk: a coherent scenario for risk management," MPRA Paper 64387, University Library of Munich, Germany.
    2. Muteba Mwamba, John & Thabo, Lethaba & Uwilingiye, Josine, 2014. "Modelling the short-term interest rate with stochastic differential equation in continuous time: linear and nonlinear models," MPRA Paper 64386, University Library of Munich, Germany.
    3. Muteba Mwamba, John & Mokwena, Paula, 2013. "International diversification and dependence structure of equity portfolios during market crashes: the Archimedean copula approach," MPRA Paper 64384, University Library of Munich, Germany.

    More about this item

    Keywords

    kernel function; Epanechnikov density distribution; non-parametric regression;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    Statistics

    Access and download statistics

    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:afj:journl:v:13:y:2011:i:1:p:14-27. See general information about how to correct material in RePEc.

    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.

    We have no bibliographic references for this item. You can help adding them by using 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Kirk De Doncker (email available below). General contact details of provider: https://edirc.repec.org/data/afrgrza.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.