COVID-19 crisis and stock market volatility in Nigeria: A GARCH model approach

C Onuorah Anastasia; C Ehiedu Victor; Okoh Ezekiel

doi:10.21744/irjmis.v9n3.2081

Authors

Onuorah Anastasia. C
anastasiaonuorah@gmail.com
Department of Banking and Finance, Delta State University, Abraka, Nigeria
Ehiedu Victor. C Department of Banking and Finance, Delta State University, Abraka, Nigeria
Okoh Ezekiel Department of Banking and Finance, Delta State University, Abraka, Nigeria

Keywords:

COVID-19, EGARCH, GARCH, Nigeria, stock volatility

Abstract

The economic downturns locally and internationally due to the COVID-19 crisis were the main motivation for this study. However, rather than broadly examining economic indices, this paper focused on the reaction of the Nigerian stock market in terms of volatility to the crisis. The specific objectives of the study were to identify differences in market performance due to the COVID crisis, determine volatility persistence and ascertain the leverage effects of the news on stocks on the stock exchange floor. Adopting an ex-post facto research design, monthly time-series All-Share Index data were analyzed using descriptive statistics, GARCH(1,1), and EGARCH models. It was found that volatility existed in the market during the COVID-19 crisis however volatility persistence was low. EGARCH results showed asymmetric parameters did not exist revealing the form of leverage effect COVID-19 posed to the market. The market thus had identical responses to both bad and good news of COVID-19 announcements of the same magnitude. It was recommended that regulatory authorities and policymakers be proactive in their approach to forecasting market performance to reduce the negative effects of bad news on market indices.

Downloads

Download data is not yet available.

References

Agnolucci, P. (2009). Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models. Energy Economics, 31(2), 316-321. https://doi.org/10.1016/j.eneco.2008.11.001

Atoi, N. V. (2014). Testing volatility in Nigeria stock market using GARCH models. CBN Journal of Applied Statistics (JAS), 5(2), 4.

Awartani, B. M., & Corradi, V. (2005). Predicting the volatility of the S&P-500 stock index via GARCH models: the role of asymmetries. International Journal of forecasting, 21(1), 167-183. https://doi.org/10.1016/j.ijforecast.2004.08.003

Barra Novoa, R. (2021). Macro and microeconomic analysis of the impact of the COVID-19 pandemic in Chile and the projections of the central bank’s. International Research Journal of Management, IT and Social Sciences, 8(3), 236-245. https://doi.org/10.21744/irjmis.v8n3.1471

Bello, A. I. (2020). Re-examining the effect of volatility persistence on Nigerian stock market returns: Mean-revert GARCH approach. The Journal of Accounting and Management, 10(2).

Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of econometrics, 31(3), 307-327. https://doi.org/10.1016/0304-4076(86)90063-1

Donaldson, R. G., & Kamstra, M. (1997). An artificial neural network-GARCH model for international stock return volatility. Journal of Empirical Finance, 4(1), 17-46. https://doi.org/10.1016/S0927-5398(96)00011-4

Eagle, R. F. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of UK inflation. Econometrica, 50(4), 987-1007.

Ehiedu V.C, Odita O.O & Kifordu A.A (2020).Estimators and Economic Growth Nexus in Financial

Ehiedu, V. C. (2014). The impact of liquidity on profitability of some selected companies: The financial statement analysis (FSA) approach. Research Journal of Finance and Accounting, 5(5), 81-90.

Ehiedu, V. C., & Toria, G. (2022). Audit indicators and financial performance of manufacturing firms in Nigeria. Linguistics and Culture Review, 6, 14-41.

Ekong, C. N., & Onye, K. U. (2017). Application of Garch models to estimate and predict financial volatility of daily stock returns in Nigeria.

Emenike, K. O. (2010). Modelling stock returns volatility in Nigeria using GARCH models.

Emenogu, N. G., Adenomon, M. O., & Nweze, N. O. (2020). On the volatility of daily stock returns of Total Nigeria Plc: evidence from GARCH models, value-at-risk and backtesting. Financial Innovation, 6(1), 1-25.

Fakhfekh, M., & Jeribi, A. (2020). Volatility dynamics of crypto-currencies’ returns: Evidence from asymmetric and long memory GARCH models. Research in International Business and Finance, 51, 101075. https://doi.org/10.1016/j.ribaf.2019.101075

Franses, P. H., & Ghijsels, H. (1999). Additive outliers, GARCH and forecasting volatility. International Journal of forecasting, 15(1), 1-9. https://doi.org/10.1016/S0169-2070(98)00053-3

He, Q., Liu, J., Wang, S., & Yu, J. (2020). The impact of COVID-19 on stock markets. Economic and Political Studies, 8(3), 275-288.

Katsiampa, P. (2017). Volatility estimation for Bitcoin: A comparison of GARCH models. Economics Letters, 158, 3-6. https://doi.org/10.1016/j.econlet.2017.06.023

Liu, H. C., & Hung, J. C. (2010). Forecasting S&P-100 stock index volatility: The role of volatility asymmetry and distributional assumption in GARCH models. Expert Systems with Applications, 37(7), 4928-4934. https://doi.org/10.1016/j.eswa.2009.12.022

Lu, X. F., & Lai, K. K. (2012). Relationship between stock indices and investors' sentiment index in Chinese financial market. Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice, 32(3), 621-629.

Mandasari , I. C. S. ., & Pratama , I. G. S. . (2020). The use of e-commerce during COVID-19 pandemic towards revenue and volume of MSMEs sales. International Research Journal of Management, IT and Social Sciences, 7(6), 124-130. https://doi.org/10.21744/irjmis.v7n6.1022

Maxwell, O., Happiness, O. I., Alice, U. C., & Chinedu, I. U. (2018). An empirical assessment of the impact of Nigerian all share index, Market Capitalization, and Number of Equities on Gross Domestic Product. Open Journal of Statistics, 8(3), 584-602.

Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica: Journal of the Econometric Society, 347-370.

Obiakor, R. T., Afolayan, O. T., Oresanwo, A. M., & Okoh, J. I. (2021). Does Entrepreneurship Financing Create Employment in Nigeria? The Role of Small and Medium Scale Enterprises (SMEs). Economic Insights-Trends & Challenges, (4).

Okafor, C., & Arowoshegbe, A. O. (2011). Stimulating economic development through the capital market: the Nigerian experience. Journal of Research in National Development, 9(2), 404-412.

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 Science, 17, 1-10.

Olayungbo, D. O., Olaniyi, C. O., & Ojeyinka, T. A. (2020). Asymmetric Effects of Remittances on Economic Growth in Nigeria: Evidence From Non-linear ARDL Analysis.

Onuorah, A. C. (2018). Role of non oil exports in the economic growth of Nigeria. Journal of Emerging Trends in Economics and Management Sciences, 9(3), 132-140.

Onuorah, A. C. C., & Chigbu, E. E. (2016). Federal government treasury single account (TSA) deposits and commercial banks performance. Journal of Social and Management Sciences, 11(3), 01-13.

Onuorah, A. C., & Friday, I. O. (2016). Corporate governance and financial reporting quality in selected Nigerian company. International Journal of Management Science and Business Administration, 2(3), 7-16.

Palm, F. C. (1996). 7 GARCH models of volatility. Handbook of statistics, 14, 209-240. https://doi.org/10.1016/S0169-7161(96)14009-8

Raifu, I. A., Kumeka, T. T., & Aminu, A. (2021). Reaction of stock market returns to COVID-19 pandemic and lockdown policy: evidence from Nigerian firms stock returns. Future Business Journal, 7(1), 1-16.

Takyia, P. O., and Bentum-Enninb, I., 2020, The impact of COVID-19 on stock market performance in Africa: A Bayesian structural time series approach. Journal of Economics and Business. doi, 10.

Tully, E., & Lucey, B. M. (2007). A power GARCH examination of the gold market. Research in International Business and Finance, 21(2), 316-325. https://doi.org/10.1016/j.ribaf.2006.07.001