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Modelling Stock Return Volatility Dynamics in Selected African Markets

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  • Daniel King
  • Ferdi Botha

Abstract

This paper examines whether accounting for structural changes in the conditional variance process, through the use of Markov-switching models, improves estimates and forecasts of stock return volatility over those of the more conventional single-state (G)ARCH models, within and across selected African markets for the period 2002-2012. In the univariate portion of the paper, the performances […]

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  • Daniel King & Ferdi Botha, 2014. "Modelling Stock Return Volatility Dynamics in Selected African Markets," Working Papers 410, Economic Research Southern Africa.
    • Handle: RePEc:rza:wpaper:410
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    1. King, Mervyn A & Wadhwani, Sushil, 1990. "Transmission of Volatility between Stock Markets," Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 5-33.
    2. Asger Lunde & Peter R. Hansen, 2005. "A forecast comparison of volatility models: does anything beat a GARCH(1,1)?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
    3. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    4. Andrew Ang & Allan Timmermann, 2012. "Regime Changes and Financial Markets," Annual Review of Financial Economics, Annual Reviews, vol. 4(1), pages 313-337, October.
    5. Dahlquist, Magnus & Gray, Stephen F., 2000. "Regime-switching and interest rates in the European monetary system," Journal of International Economics, Elsevier, vol. 50(2), pages 399-419, April.
    6. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    7. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    8. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    9. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
    10. Klaus Adam & Albert Marcet & Juan Pablo Nicolini, 2016. "Stock Market Volatility and Learning," Journal of Finance, American Finance Association, vol. 71(1), pages 33-82, February.
    11. Robert Engle, 2004. "Risk and Volatility: Econometric Models and Financial Practice," American Economic Review, American Economic Association, vol. 94(3), pages 405-420, June.
    12. Aggarwal, Reena & Inclan, Carla & Leal, Ricardo, 1999. "Volatility in Emerging Stock Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(1), pages 33-55, March.
    13. Wang, Ping & Theobald, Mike, 2008. "Regime-switching volatility of six East Asian emerging markets," Research in International Business and Finance, Elsevier, vol. 22(3), pages 267-283, September.
    14. Abel, Andrew B., 1988. "Stock prices under time-varying dividend risk : An exact solution in an infinite-horizon general equilibrium model," Journal of Monetary Economics, Elsevier, vol. 22(3), pages 375-393.
    15. Babikir, Ali & Gupta, Rangan & Mwabutwa, Chance & Owusu-Sekyere, Emmanuel, 2012. "Structural breaks and GARCH models of stock return volatility: The case of South Africa," Economic Modelling, Elsevier, vol. 29(6), pages 2435-2443.
    16. Garcia, Rene & Perron, Pierre, 1996. "An Analysis of the Real Interest Rate under Regime Shifts," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 111-125, February.
    17. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    18. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    19. Franc Klaassen, 2002. "Improving GARCH volatility forecasts with regime-switching GARCH," Empirical Economics, Springer, vol. 27(2), pages 363-394.
    20. Hamilton, James D & Gang, Lin, 1996. "Stock Market Volatility and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 573-593, Sept.-Oct.
    21. Andrew Stuart Duncan & Guangling“dave” Liu, 2009. "Modelling South African Currency Crises As Structural Changes In The Volatility Of The Rand," South African Journal of Economics, Economic Society of South Africa, vol. 77(3), pages 363-379, September.
    22. Lo, Andrew W & MacKinlay, A Craig, 1990. "Data-Snooping Biases in Tests of Financial Asset Pricing Models," Review of Financial Studies, Society for Financial Studies, vol. 3(3), pages 431-467.
    23. Dueker, Michael J, 1997. "Markov Switching in GARCH Processes and Mean-Reverting Stock-Market Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 26-34, January.
    24. Francis X. Diebold & Kamil Yılmaz, 2007. "Macroeconomic Volatility and Stock Market Volatility,World-Wide," Koç University-TUSIAD Economic Research Forum Working Papers 0711, Koc University-TUSIAD Economic Research Forum.
    25. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    26. Henry, Ólan T., 2009. "Regime switching in the relationship between equity returns and short-term interest rates in the UK," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 405-414, February.
    27. Tobias Knedlik & Rolf Scheufele, 2008. "Forecasting Currency Crises: Which Methods Signaled The South African Crisis Of June 2006?," South African Journal of Economics, Economic Society of South Africa, vol. 76(3), pages 367-383, September.
    28. Markus Haas, 2004. "A New Approach to Markov-Switching GARCH Models," Journal of Financial Econometrics, Oxford University Press, vol. 2(4), pages 493-530.
    29. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    30. Ntim, Collins G, 2012. "Why African Stock Markets Should Formally Harmonise and Integrate their Operations," MPRA Paper 45806, University Library of Munich, Germany.
    31. Schwert, G William, 1989. " Why Does Stock Market Volatility Change over Time?," Journal of Finance, American Finance Association, vol. 44(5), pages 1115-1153, December.
    32. Bollen, Nicolas P. B. & Gray, Stephen F. & Whaley, Robert E., 2000. "Regime switching in foreign exchange rates: Evidence from currency option prices," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 239-276.
    33. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    34. Edwards, Sebastian & Susmel, Raul, 2001. "Volatility dependence and contagion in emerging equity markets," Journal of Development Economics, Elsevier, vol. 66(2), pages 505-532, December.
    35. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    36. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    37. Marcucci Juri, 2005. "Forecasting Stock Market Volatility with Regime-Switching GARCH Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(4), pages 1-55, December.
    38. Peter Reinhard Hansen, 2001. "An Unbiased and Powerful Test for Superior Predictive Ability," Working Papers 2001-06, Brown University, Department of Economics.
    39. Chen, Shiu-Sheng, 2009. "Predicting the bear stock market: Macroeconomic variables as leading indicators," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 211-223, February.
    40. Giorgio Canarella & Stephen Pollard, 2007. "A switching ARCH (SWARCH) model of stock market volatility: some evidence from Latin America," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 54(4), pages 445-462, December.
    41. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    42. Garcia, Rene, 1998. "Asymptotic Null Distribution of the Likelihood Ratio Test in Markov Switching Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(3), pages 763-788, August.
    43. Ming‐yuan leon Li, 2009. "Change In Volatility Regimes And Diversification In Emerging Stock Markets," South African Journal of Economics, Economic Society of South Africa, vol. 77(1), pages 59-80, March.
    44. Hsiang-Tai Lee & Jonathan Yoder, 2007. "A bivariate Markov regime switching GARCH approach to estimate time varying minimum variance hedge ratios," Applied Economics, Taylor & Francis Journals, vol. 39(10), pages 1253-1265.
    45. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-234, April.
    46. World Bank, 2014. "World Development Indicators 2014," World Bank Publications - Books, The World Bank Group, number 18237, December.
    47. Cai, Jun, 1994. "A Markov Model of Switching-Regime ARCH," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 309-316, July.
    48. Ramchand, Latha & Susmel, Raul, 1998. "Volatility and cross correlation across major stock markets," Journal of Empirical Finance, Elsevier, vol. 5(4), pages 397-416, October.
    49. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    50. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
    51. Sebastian Edwards & Raul Susmel, 2003. "Interest-Rate Volatility in Emerging Markets," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 328-348, May.
    52. Tsui, Albert K. & Yu, Qiao, 1999. "Constant conditional correlation in a bivariate GARCH model: evidence from the stock markets of China," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 48(4), pages 503-509.
    53. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    54. AfDB AfDB, . "2010 African Fixed Income Guidebook," African Fixed Income Guidebook, African Development Bank, number 48 edited by Sodji Agossou Francis Kohoue.
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    Cited by:

    1. Lumengo Bonga-Bonga & Maphelane Palesa Phume, 2022. "Return and volatility spillovers between South African and Nigerian equity markets," African Journal of Economic and Management Studies, Emerald Group Publishing Limited, vol. 13(2), pages 205-218, January.
    2. Bala A. Dahiru & Pam W. Jim & Kalu N. Nwonyuku, 2017. "Equity markets volatility dynamics in developed and newly emerging economies: EGARCH-with-skewed-t density approach," Economics Bulletin, AccessEcon, vol. 37(4), pages 2394-2412.
    3. Liu, De-Chih & Liu, Chih-Yun, 2016. "The source of stock return fluctuation in Taiwan," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 77-88.
    4. M. MALLIKARJUNA & R. Prabhakara RAO, 2019. "Volatility experience of major world stock markets," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(621), W), pages 35-52, Winter.
    5. repec:agr:journl:v:4(621):y:2019:i:4(621):p:35-52 is not listed on IDEAS

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    More about this item

    Keywords

    Africa; Other Macroeconomic Variables; Quantitative Methods; Risk and Uncertainty; Time Series Analysis;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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