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

John Weirstrass Muteba Mwamba

The African Finance Journal, 2011, vol. 13, issue 1, 14-27

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.

Keywords: kernel function; Epanechnikov density distribution; non-parametric regression (search for similar items in EconPapers)
JEL-codes: C14 C53 G17 (search for similar items in EconPapers)
Date: 2011
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.journals.co.za/ej/ejour_finj.html (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:afj:journl:v:13:y:2011:i:1:p:14-27

Access Statistics for this article

More articles in The African Finance Journal from Africagrowth Institute Contact information at EDIRC.
Bibliographic data for series maintained by Kirk De Doncker ().