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Modeling South African Banks closing stock prices: a Markov-Switching Approach

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  • Diteboho Xaba
  • Ntebogang Dinah Moroke
  • Johnson Arkaah
  • Charlemagne Pooe

Abstract

In this paper, we provide evidence that the five variables used in the study were nonlinear in nature, while finding a better Markov-switching model. The study used dailydata obtained from the Johannesburg Stock Exchange over the period from January 2010 to December 2012. An extension of Markov Switching with autoregressive model was used for empirical analysis. Prior to using this model, the series were tested for nonlinear unit root with modified Kapetanois-Shin-Snell nonlinear Augmented Dickey-Fuller (KSS-NADF) test which successfully provided positive results.Other preliminary tests selected the first lag as optimal and confirmed that stock prices may switch between two regimes. Further empirical findings proved that stock prices can be successfully modelled with Markov Switching Autoregressive model of order one. First National bank was found to have 99.64% longer stock price stability if adjustments regards tofinancialpolicies are made. Capitec Bank was the least favoured among the banks.

Suggested Citation

  • Diteboho Xaba & Ntebogang Dinah Moroke & Johnson Arkaah & Charlemagne Pooe, 2016. "Modeling South African Banks closing stock prices: a Markov-Switching Approach," Journal of Economics and Behavioral Studies, AMH International, vol. 8(1), pages 36-40.
    • Handle: RePEc:rnd:arjebs:v:8:y:2016:i:1:p:36-40
    DOI: 10.22610/jebs.v8i1(J).1204
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    References listed on IDEAS

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    Cited by:

    1. Andile Khula & Ntebogang Dinah Moroke, 2017. "The Performance of Maximum Likelihood Factor Analysis on South African Stock Price Performance," Journal of Economics and Behavioral Studies, AMH International, vol. 8(6), pages 40-51.

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