IIARD INTERNATIONAL JOURNAL OF BANKING AND FINANCE RESEARCH (IJBFR )
E-ISSN 2695-1886
P-ISSN 2672-4979
VOL. 5 NO. 2 2019
Ihejirika, Peters O.
This study estimated and analyzed the risk – return volatility nexus in the Nigerian Stock Exchange for the period January 1985 to April 2019, by applying the non-linear symmetric and asymmetric Exponential Generalized Auto Regressive Conditional Heteroscedasticity (EGARCH) model. The study results indicate that the Nigerian stock exchange all share index log relative return has a leptokurtic distribution and is negatively skewed. The ADF Unit Root Test show that the Nigerian stock exchange all share index log relative return is integrated of order zero i.e. I(0). The results also indicate that the Nigerian stock exchange index returns exhibits volatility clustering meaning that the market experience mean reversion. Another stylized fact exhibited by the Nigerian stock exchange index returns is volatility persistence (long memory) as revealed by the study. These results indicate that investors are well able to predict the future parts of return in the Nigerian stock exchange and therefore should embrace models that are capable of forecasting the risk and return relationships such as the EGARCH model in making investment decisions to avoid bearing avoidable risks
Risk–Return Volatility, EGARCH, Heteroskedasticity, Leptokurtosis, Asymmetric effect, Long-Memory, Volatility Clustering
Acemoglu, D & Zilibotti, F (1997), Was Prometheus Unbound by Chance? Risk, Diversification
and Growth, Journal of Political Economy. 105: 709-51.
Ajao, M.A & M.U. Wemambu (2012), Volatility Estimation and Stock Price Prediction in
the Nigerian Stock Market, International Journal of Financial Research Vol. 3, No. 1
Andersen, T., Bollerslev, T., Diebold, F.X.& Ebens, H. (2001), The Distribution of Realized
Stock Return Volatility," Journal of Financial Economics, 61, 43-76.
Atoi, N. V. (2014), Testing Volatility in Nigeria Stock Market using GARCH Models CBN
Journal of Applied Statistics Vol. 5 No.2 (December, 2014) 65
Black, F. & Scholes, M. (1973), The Pricing of Options and Corporate Liabilities, Journal of
Political Economy, 637- 654
Black, F. (1976), Studies in Stock Price Volatility Changes, Proceedings from the American
Statistical Association, Business and Economics Statistics Section, 177-181.
Bollerslev, T. (1986) Generalized autoregressive conditional heteroskedasticity, Journal of
Econometrics, Vol. 31, No. 3, pp.307–327.
Dickey, D. A., & Fuller, W. A. (1979), Distribution of the Estimators for Autoregressive Time
Series with a Unit Root. Journal of American Statistical Association, 74: 427-431.
Emenike K.O. & O. Odili (2014), Stock Market Return Volatility and Macroeconomic Variables
in Nigeria. International Journal of Empirical Finance Vol. 2, No. 2, 75-82
Emenike K.O. & Opara C.C. (2014), the relationship between stock returns volatility and trading
volume in Nigeria, Business systems and Economics vol. 4 (2)
Engle, R.F. (1982), Autoregressive Conditional Heteroskedasticity with Estimates of the
Variance of United Kingdom Inflation, Econometrica,50, 987-1007.
Engle, R. F. (2003), Risk and Volatility: Econometric Models and Financial Practice. Noble
Lecture (December 8). New York: Salomon Centre.
Engle, R.F. & V.K. Ng (1993), “Measuring and Testing the Impact of News on Volatility,”
Journal of Finance, 48, 1749-1778.
E-views 10, 1994 – 2015 HIS Global Inc. Quantitative Micro Software, LLC www.eviews.
Grimes, A.H. (2014), https://adamhgrimes.com/volatility-clustering/ Aug 11,
Gurley, J & Shaw, E. (1955), Financial Aspects of Development and Growth, American
Economic Review, (September), 515-38.
Ihejirika P.O & Anyanwu G.I. (2013), Characterization of Volatilities in the Nigerian Stock
Exchange: Prospects for Options Trading, Research Journal of Finance and Accounting
Vol.4, No.16
Investopedia, LLC (2018), Generalized Autoregressive Conditional Heteroskedasticity (GARCH)
Process
Islam, M.A. (2014), Applying Generalized Autoregressive Conditional Heteroscedasticity
Models to Model Univariate Volatility. Journal of Applied Sciences, 14: 641-650.
Ivanovski, Z., Stojanovski T. & Narasanov Z. (2015), Volatility and Kurtosis of Daily Stock
Returns at Macedonian Stock Exchange, UTMS Journal of Economics 6 (2): 209–221.
Krishnamurti, C., Tian, G. G., Xu, M., & Li, G. (2013), No news is not good news: Evidence
from the intra-day return volatility–volume relationship in Shanghai stock exchange.
Journal of the Asia Pacific Economy, 18, 149–167.
https://doi.org/10.1080/13547860.2012.742709
Mandelbrot, B. B. (1963), The Variation of Certain Speculative Prices, The Journal of Business
36, No. 4, 394-419
Nelson, D.B. (1991), Conditional heteroskedasticity in asset returns: A new approach,
Econometrica,59,347-370
Okpara, G.C & Nwezeaku, N.C. (2009), Idiosyncratic Risk and the Cross-Section of Expected
Stock Returns: Evidence from Nigeria, European Journal of Economics, Finance and
Administrative Sciences Vol. 17 http://www.eurojournals.com
Omorokunwa, O.G. & Ikponmwosa, N. (2014) Macroeconomic Variables and Stock Price
Volatility in Nigeria. Annals of the University of Petro?ani, Economics, 14(1), 259-268
259
Osahon, O.H (2014) Measuring Nigerian stock market volatility Singaporean Journal of
Business Economics, and Management studies Vol.2, No.8
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
Paulo S.G., David A. S., Tiago A.E.F., & George D.C.C. (2011) Market volatility modeling for
short time window Physica A 390 3444–3453 journal homepage:
www.elsevier.com/locate/physa
Reza, R., Tularam, G.A & Li, B. (2018), Returns and volatility of water investments, Cogent
Economics & Finance Vol.6: https://doi.org/10.1080/23322039.2018.1438724
Sokpo, J.T., Iorember, T.U. & Usar, T. (2017), Inflation and Stock Market Returns Volatility:
Evidence from the Nigerian Stock Exchange 1995Q1-2016Q4: An E-GARCH Approach
International Journal of Econometrics and Financial Management, Vol. 5, No. 2, 69-76
Available online at http://pubs.sciepub.com/ijefm/5/2/9 ©Science and Education
Publishing DOI:10.12691/ijefm-5-2-6
Stavroyiannis, S., Makris, I., Nikolaidis, V.& Zarangas, L. (2012), Econometric modeling and
value-at-risk using the Pearson type-IV distribution, International Review of Financial
Analysis, Vol. 22, pp.10–17.
Yertey, A. C. (2008), The Determinants of stock market development in Emerging Economies:
Is South Africa Different. IMF Working Paper, WP/08/32
Yong, T., & Christos, F. (2012), Stock market volatility and bank performance in China, Studies
in Economics and Finance, Vol. 29 Issue: 3, pp.211-228,
https://doi.org/10.1108/10867371211246885