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Predicting Regime Shifts in Johannesburg Stock Exchange All-Share Index (JSE-ALSI): A Markov-Switching Approach

Author

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  • Katleho Daniel Makatjane

    (Basetsana Consultants, Republic of South Africa)

  • Edward Kagiso Molefe

    (University of the Free State, Republic of South Africa)

Abstract

It has been proven several times that linear models are unable to encapsulate nonlinear dynamics of macroeconomic and financial data such as inflation rates, exchange rates and stock prices to mention fewer. As a result, to overcome this problem, this current study adopted the nonlinear models due to the fact that they have required qualities to apprehend nonlinearity in a dataset. In order to predict a regime shifts, a five-day Johannesburg stock exchange allshare index (JSE-ALSI) spanning period from 02 January 2003 to 28 June 2019 was used as an experimental unit. This current study firstly employed Teräsvirta neural network test to detect the presence of nonlinearity and proceeded to estimate a two regime Markov-Switching autoregressive (MS-AR). The results of Teräsvirta neural network test revealed a highly significant nonlinearity with permanent seasonality as demonstrated by Kruskal-Wallis test. The predicted regime shifts by a latent dynamic allowed the autoregressive and variance parameters to promptly react to vital systemic shocks. As a result, this current study allowed volatility to oscillate between high and low volatility regimes that produced an expected duration of high volatility of two year and two months. This was a clear indication that there is a regime shifts in JSE-ALI which are modeled using Markov-Chain (MC) stochastic process. These findings may be used to inform robust policy making with the aim of safeguarding both the JSE and other global stock markets from the episodes of stock market crash. Moreover, other researchers can utilize the results of this study to calculate the risk associated with structural breaks and high volatility periods.

Suggested Citation

  • Katleho Daniel Makatjane & Edward Kagiso Molefe, 2020. "Predicting Regime Shifts in Johannesburg Stock Exchange All-Share Index (JSE-ALSI): A Markov-Switching Approach," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 8(2), pages 95-103.
  • Handle: RePEc:ejn:ejefjr:v:8:y:2020:i:2:p:95-103
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    Cited by:

    1. Xing Li & Xiangyu Ge & Cong Chen, 2022. "Several explorations on how to construct an early warning system for local government debt risk in China," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-27, February.

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