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Forecasting Stock Return Volatility: Evidence from the West African Regional Stock Market

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  • N’dri Konan Léon

Abstract

This paper compares the out-of-sample forecasting performance of the GARCH, EGARCH, and GJR-GARCH models across the Normal distribution, Student-t distribution, and Generalized Error Distribution (GED) in the regional stock market of the West African Economic and Monetary Union called the BRVM. The study uses weekly returns ranging from 4 January 1999 to 10 March 2005 for in-sample estimation of conditional variance models, and the period from 11 March 2005 to 29 July 2005 for out-of-sample forecasting. Using the RMSE and MAE as measures of forecasting accuracy, I find that the EGARCH model outperforms both the GARCH and the GJR-GARCH models under the Student-t distribution and the GED.

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  • N’dri Konan Léon, 2015. "Forecasting Stock Return Volatility: Evidence from the West African Regional Stock Market," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 5(6), pages 1-2.
    • Handle: RePEc:spt:apfiba:v:5:y:2015:i:6:f:5_6_2
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    1. Alagidede, Paul & Panagiotidis, Theodore, 2009. "Modelling stock returns in Africa's emerging equity markets," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 1-11, March.
    2. Jiranyakul, Komain, 2007. "Behavior of Stock Market Index in the Stock Exchange of Thailand," MPRA Paper 45961, University Library of Munich, Germany.
    3. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. Awartani, Basel M.A. & Corradi, Valentina, 2005. "Predicting the volatility of the S&P-500 stock index via GARCH models: the role of asymmetries," International Journal of Forecasting, Elsevier, vol. 21(1), pages 167-183.
    6. Bae, Jinho & Kim, Chang-Jin & Nelson, Charles R., 2007. "Why are stock returns and volatility negatively correlated?," Journal of Empirical Finance, Elsevier, vol. 14(1), pages 41-58, January.
    7. Appiah-Kusi, Joe & Menyah, Kojo, 2003. "Return predictability in African stock markets," Review of Financial Economics, Elsevier, vol. 12(3), pages 247-270.
    8. I.-Yuan Chuang & Jin-Ray Lu & Pei-Hsuan Lee, 2007. "Forecasting volatility in the financial markets: a comparison of alternative distributional assumptions," Applied Financial Economics, Taylor & Francis Journals, vol. 17(13), pages 1051-1060.
    9. 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.
    10. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    11. Turan Bali, 2007. "Modeling the dynamics of interest rate volatility with skewed fat-tailed distributions," Annals of Operations Research, Springer, vol. 151(1), pages 151-178, April.
    12. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-730, August.
    13. Christie, Andrew A., 1982. "The stochastic behavior of common stock variances : Value, leverage and interest rate effects," Journal of Financial Economics, Elsevier, vol. 10(4), pages 407-432, December.
    14. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
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