IDEAS home Printed from https://ideas.repec.org/p/unu/wpaper/wp-2020-162.html
   My bibliography  Save this paper

Identifying structural changes in the exchange rates of South Africa as a regime-switching process

Author

Listed:
  • Katleho Makatjane
  • Roscoe van Wyk

Abstract

Exchange rate volatility is said to exemplify the economic health of a country. Exchange rate break points (known as structural breaks) have a momentous impact on the macroeconomy of a country. Nonetheless, this country study makes use of both unsupervised and supervised machine learning algorithms to classify structural changes as regime shifts in real exchange rates in South Africa. Weekly data for the period January 2003-June 2020 are used.

Suggested Citation

  • Katleho Makatjane & Roscoe van Wyk, 2020. "Identifying structural changes in the exchange rates of South Africa as a regime-switching process," WIDER Working Paper Series wp-2020-162, World Institute for Development Economic Research (UNU-WIDER).
    • Handle: RePEc:unu:wpaper:wp-2020-162
    as

    Download full text from publisher

    File URL: https://www.wider.unu.edu/sites/default/files/Publications/Working-paper/PDF/wp2020-162.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Salisu, Afees A. & Fasanya, Ismail O., 2013. "Modelling oil price volatility with structural breaks," Energy Policy, Elsevier, vol. 52(C), pages 554-562.
    2. Chkili, Walid & Nguyen, Duc Khuong, 2014. "Exchange rate movements and stock market returns in a regime-switching environment: Evidence for BRICS countries," Research in International Business and Finance, Elsevier, vol. 31(C), pages 46-56.
    3. Andrew Phiri, 2020. "Structural changes in exchange rate-stock returns dynamics in South Africa: examining the role of crisis and new trading platform," Economic Change and Restructuring, Springer, vol. 53(1), pages 171-193, February.
    4. Seabelo T Nyawo & Roscoe Bertrum van Wyk, 2018. "The Impact of Policy Uncertainty on Macro-Economy of Developed and Developing Countries," Journal of Economics and Behavioral Studies, AMH International, vol. 10(1), pages 33-41.
    5. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Mathias Manguzvane & Mduduzi Biyase, 2023. "Exchange rate risk and sovereign debt risk in South Africa: A Regime Dependent Approach," Economics Working Papers edwrg-04-2023, College of Business and Economics, University of Johannesburg, South Africa, revised 2023.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Malik, Farooq, 2021. "Volatility spillover between exchange rate and stock returns under volatility shifts," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 605-613.
    2. Salisu, Afees A. & Mobolaji, Hakeem, 2013. "Modeling returns and volatility transmission between oil price and US–Nigeria exchange rate," Energy Economics, Elsevier, vol. 39(C), pages 169-176.
    3. Afees A. Salisu & Tirimisyu F. Oloko, 2017. "Are daily agricultural grains prices stationary? New evidence from GARCH-based unit root tests," Working Papers 036, Centre for Econometric and Allied Research, University of Ibadan.
    4. Nazlioglu, Saban & Gupta, Rangan & Gormus, Alper & Soytas, Ugur, 2020. "Price and volatility linkages between international REITs and oil markets," Energy Economics, Elsevier, vol. 88(C).
    5. Mushtaq Hussain Khan & Junaid Ahmed & Mazhar Mughal & Imtiaz Hussain Khan, 2023. "Oil price volatility and stock returns: Evidence from three oil‐price wars," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 3162-3182, July.
    6. Liu, Zhicao & Ye, Yong & Ma, Feng & Liu, Jing, 2017. "Can economic policy uncertainty help to forecast the volatility: A multifractal perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 181-188.
    7. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2015. "Structural breaks, dynamic correlations, asymmetric volatility transmission, and hedging strategies for petroleum prices and USD exchange rate," Energy Economics, Elsevier, vol. 48(C), pages 46-60.
    8. Aliyu, Shehu Usman Rano, 2020. "What have we learnt from modelling stock returns in Nigeria: Higgledy-piggledy?," MPRA Paper 110382, University Library of Munich, Germany, revised 06 Jun 2021.
    9. Tarek Bouazizi & Mongi Lassoued & Zouhaier Hadhek, 2021. "Oil Price Volatility Models during Coronavirus Crisis: Testing with Appropriate Models Using Further Univariate GARCH and Monte Carlo Simulation Models," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 281-292.
    10. Charles, Amélie & Darné, Olivier, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Energy Economics, Elsevier, vol. 67(C), pages 508-519.
    11. Oscar V. De la Torre-Torres & Evaristo Galeana-Figueroa & María de la Cruz Del Río-Rama & José Álvarez-García, 2022. "Using Markov-Switching Models in US Stocks Optimal Portfolio Selection in a Black–Litterman Context (Part 1)," Mathematics, MDPI, vol. 10(8), pages 1-28, April.
    12. Akbar Komijani & Esmaeil Naderi & Nadiya Gandali Alikhani, 2014. "A hybrid approach for forecasting of oil prices volatility," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 38(3), pages 323-340, September.
    13. Salisu, Afees A. & Adeleke, Adegoke I., 2016. "Further application of Narayan and Liu (2015) unit root model for trending time series," Economic Modelling, Elsevier, vol. 55(C), pages 305-314.
    14. Chkili, Walid, 2017. "Is gold a hedge or safe haven for Islamic stock market movements? A Markov switching approach," Journal of Multinational Financial Management, Elsevier, vol. 42, pages 152-163.
    15. Zavadska, Miroslava & Morales, Lucía & Coughlan, Joseph, 2020. "Brent crude oil prices volatility during major crises," Finance Research Letters, Elsevier, vol. 32(C).
    16. Prince Osei Mensah & Anokye M. Adam, 2020. "Copula-Based Assessment of Co-Movement and Tail Dependence Structure Among Major Trading Foreign Currencies in Ghana," Risks, MDPI, vol. 8(2), pages 1-20, June.
    17. Xiao, Yang, 2020. "The risk spillovers from the Chinese stock market to major East Asian stock markets: A MSGARCH-EVT-copula approach," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 173-186.
    18. Svetlana Borovkova & Diego Mahakena, 2015. "News, volatility and jumps: the case of natural gas futures," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1217-1242, July.
    19. Nonejad, Nima, 2017. "Parameter instability, stochastic volatility and estimation based on simulated likelihood: Evidence from the crude oil market," Economic Modelling, Elsevier, vol. 61(C), pages 388-408.
    20. Ewing, Bradley T. & Malik, Farooq, 2017. "Modelling asymmetric volatility in oil prices under structural breaks," Energy Economics, Elsevier, vol. 63(C), pages 227-233.

    More about this item

    Keywords

    Machine learning; Markov switching; Principal component analysis; South Africa;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:unu:wpaper:wp-2020-162. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc 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 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: Siméon Rapin (email available below). General contact details of provider: https://edirc.repec.org/data/widerfi.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.