Modelling Volatility Persistence and Asymmetry with Structural Break: Evidence from the Nigerian Stock Market
Abstract: This study contributes to existing literature on the Nigerian stock market by modelling the persistence and asymmetry of stock market volatility taking into account structural break. It utilises returns generated from data on monthly all-share index from January 1985 to December 2014. After identifying structural break in the return series, the study splits the sample period into pre-break period (January 1985 – November 2008) and post-break period (January 2009 – December 2014). Using the symmetric GARCH model, the study shows that the sum of ARCH and GARCH coefficients is higher in the pre-break period compared to the post-break period, thus indicating that persistence of shock to volatility is higher before structural break in the market. The asymmetric GARCH model provides no evidence of asymmetry as well as leverage effect with or without accounting for structural break in the Nigerian stock market. This study concludes that the Nigerian stock market is characterised by inefficiency, high degree of uncertainty and non-asymmetric volatility.
Keywords: Persistence, asymmetry, stock market volatility, structural break
Adesina, K. S. (2013). Modelling stock market return volatility: GARCH evidence from Nigerian Stock Exchange. International Journal of Financial Management, 3(3), 38-46.
Ahmed, A. M. A. & Suliman, S. Z. (2011). Modelling stock market volatility using GARCH models evidence from Sudan. International Journal of Business and Social Science, 2(23), 114-128.
Atoi, N. V. (2014). Testing volatility in Nigeria stock market using GARCH models.CBN Journal of Applied Statistics, 5(2), 65-93.
Banumathy, K. & Azhagaiah, R. (2015). Modelling stock market volatility: evidence from India. Managing Global Transitions, 13(1), 27-42.
Boako, G., Agyemang-Badu, A. A. & Frimpong, J. M. (2015). Volatility dynamics in equity returns: A multi-GARCH approach. European Journal of Business and Innovation Research, 3(4), 36-45.
Bollerslev, T. (1986). Generalised autoregressive conditional heteroskedasticity. Journal of Econometrics, 31, 307-327.
Bundo, S. K. (2011). Asset price developments in an emerging stock market: The case of Mauritius (AERC Research Paper 219). Nairobi: African Economic Research Consortium.
Coffie, W. (2015). Modelling and forecasting the conditional heteroskedasticity of stock returns using asymmetric models: Empirical evidence from Ghana and Nigeria. Journal of Accounting and Finance, 15(5), 109-123.
Emenike, K. O. (2010). Modelling stock returns volatility in Nigeria using GARCH models (MPRA Paper No. 23432). Retrieved from http://mpra.ub.uni-muenchen.de/23432/.
Emenike, K. O. & Aleke, S. F. (2012). Modelling asymmetric volatility in the Nigerian Stock Exchange. European Journal of Business and Management, 4(12), 52-59.
Gabiax, X., Gopikrishnan, P., Plerou, V. & Stanley, H. E. (2006). Institutional investors and stock market volatility. The Quarterly Journal of Economics, 5, 461-504.
Guo, H. (2002). Stock market returns, volatility, and future output. Federal Reserve Bank of St. Louis, September/October, 75-86.
Goudarzi, H. & Ramanarayanan, C. S. (2010). Modelling and estimation of volatility in the Indian stock market. International Journal of Business and Management, 5(2), 86-98.
Harvey, R. C. (1995). Predictable risk and returns in emerging markets. The Review of Financial Studies, 8(3), 773-816.
Karolyi, G. A. (2001). Why stock return volatility really matters. Institutional Investor Journal Series, February. Paper presented for Inaugural Issue of Strategic Investor Relations.
Kumar, D. & Maheswaran, S. (2012). Modelling asymmetry and persistence under the impact of sudden changes in the volatility of the Indian stock market. IIMB Management Review, 24, 123-136.
Kupiec, P. (1991). Stock market volatility in OECD countries: Recent trends. Consequences for the real economy and the proposals for reform. Economic Studies, 17, 32-60.
Lamoureux, C. G. & Lastrapes, W. D. (1990). Persistence in variance, structural change and the GARCH model. Journal of Business and Economics Statistics, 68, 225-234.
LeRoy, S. F. & Porter, R. D. (1981). The present-value relation: Tests based on implied variance bounds. Econometrica, 49, 555-574.
Li, Q., Yang, J., Hsiao, C. & Chang, Y. (2005).The relationship between stock returns and volatility in international stock markets. Journal of Empirical Finance, 12, 650-665.
Mele, A. (2008). Understanding stock market volatility – A business cycle perspective. London: London School of Economics.
Namugaya, J., Weke, P. G. O. & Charles, W. M. (2014). Modelling stock returns volatility on Ugandan Securities Exchange. Applied Mathematical Sciences, 8(104), 5173-5184.
Ndwiga, D. & Muriu, P. W. (2016). Stock returns and volatility in an emerging equity market: Evidence from Kenya. European Scientific Journal, 12(4), 79-98.
N’dri, K. L. (2007). Stock market returns and volatility in the BRVM. African Journal of Business Management, 1(5), 107-112.
Niyitegeka, O. & Tewari, D. D. (2013). Volatility clustering at the Johannesburg Stock Exchange: Investigation and analysis. Mediterranean Journal of Social Sciences, 4(14), 621-626.
Nelson, D. (1991). Conditional heteroscedasticity in asset returns: A new approach. Econometrica, 59(2), 347-370.
Oloko, T. F. (2016). Portfolio diversification between developed and less developed economies: The case of US and UK investors in Nigeria (CSEA Working Paper WPS/16/02). Abuja: Centre for the Study of Economies of Africa.
Osazevbaru, H. O. (2014). Measuring Nigerian stock market volatility. Singaporean Journal of Business Economics and Management Studies, 2(8), 1-14.
Owidi, O. H. & Mugo-Waweru, F. (2016).Analysis of asymmetric and persistence in stock return volatility in the Nairobi Securities Exchange market phases. Journal of Finance and Economics, 4(3), 63-73.
Perron, P. (1997). Further evidence on breaking trend functions in macroeconomic variables. Journal of Econometrics, 80, 335-385.
Perron, P. (2006). Dealing with structural breaks. In Palgrave Handbook of Econometrics, 1, 278-352.
Shiller, R. J. (1981). Do stock prices move too much to be justified by subsequent changes in dividends? American Economic Review, 71(3), 421-435.
Shiller, R. J. (2003). From efficient markets theory to behavioural finance. Journal of Economic Perspectives, 17(1), 83-104.
Shittu, O. I., Yaya, O. S. & Oguntade, E. S. (2009). Modelling volatility of stock returns on the Nigerian stock exchange. Global Journal of Mathematics and Statistics, 1(2), 87-94.
Turtle, H. J. & Zhang, C. (2014).Structural breaks and portfolio performance in global equity markets. Faculty Publications-School of Business, Paper 52. Retrieved from http://digitalcommons.georgefox.edu/gfsb/52.
Wang, Y. & Ma, J. (2014).Excess volatility and the cross-section of stock returns. North American Journal of Economics and Finance, 27, 1-16.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Author (s) should affirm that the material has not been published previously. It has not been submitted and it is not under consideration by any other journal. At the same time author (s) need to execute a publication permission agreement to assume the responsibility of the submitted content and any omissions and errors therein. After submission of revised paper in the light of suggestions of the reviewers editorial team at IFRD edits and formats manuscripts to bring uniformity and standardization in published material.
Moreover, this work will be licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) and under condition of the license, users are free to read, copy, remix, transform, redistribute, download, print, search or link to the full texts of articles and even build upon their work as long as they credit the author for the original work.