Journal of Economics and Financial Analysis, 5 (2), pp. 63-84, [2021]
URI: https://ojs.tripaledu.com/index.php/jefa/article/view/68/79

Country Risk Dynamics and Stock Market Volatility: Evidence from the JSE Cross-Sector Analysis





DOI: http://dx.doi.org/10.1991/jefa.v5i2.a46

Abstract

The rapid integration of the global markets and financial system has increased stock market volatility due to the increased exposure to various risks. Using different GARCH family models, this study investigates the impact of country risk components shocks on stock market return volatility of the Johannesburg Stock Exchange (JSE) and its sectors for the 1996-2018 period. High positive correlations were found among the sectors, which potentially erodes diversification benefits. The research found that the South African stock market volatility is mainly driven by own/internal shocks, while the effect of county risk shocks on stock return volatility differs across the JSE sectors. We found that financial risk shocks negatively transmit to the volatility of oil and gas sector returns, leading to an increase in conditional volatility. Regarding economic risk, we found a statistically significant relationship between economic risk shocks and the entire JSE and financial and oil and gas sectors. The results show that political risk shocks negatively transmit to stock return volatility in the industrial sector, basic materials, consumer goods, financial, and the oil and gas sectors, leading to higher conditional volatility. Thus, the return volatility of most of the JSE sectors is primarily affected by political dynamics, emphasising the role of political instability in destabilising stock market volatility.

Keywords

Country Risk; Stock Return; Volatility; GARCH Models; JSE, Stock Market Sectors.

JEL Classification

D53, E44, G1, L6, I10.

Full Text:


References

Acemoglu, D., Finkelstein, A., & Notowidigdo, M.J. (2013). Income and health spending: Evidence from oil price shocks. Review of Economics and Statistics, 95(4), 1079-1095.

Agyei-Ampomah, S. (2011). Stock market integration in Africa. Managerial Finance, 37(3), 242-256.

Andersen, T.G., Bollerslev, T., Diebold, F.X., & Ebens, H. (2001). The distribution of realized stock return volatility. Journal of Financial Economics, 61(1), 43-76.

Ang, A., Hodrick, R.J., Xing, Y., & Zhang, X. (2009). High idiosyncratic volatility and low returns: International and further US evidence. Journal of Financial Economics, 91(1), 1-23.

Arestis, P., Demetriades, P.O., & Luintel, K.B. (2001). Financial development and economic growth: the role of stock markets. Journal of Money, Credit and Banking, 33(1), 16-41.

Aye, G., Gupta, R., Hammoudeh, S., & Kim, W.J. (2015). Forecasting the price of gold using dynamic model averaging. International Review of Financial Analysis, 41(C), 257-266.

Beber, A., Brandt, M.W., & Kavajecz, K.A. (2011). What does equity sector orderflow tell us about the economy? Review of Financial Studies, 24(11), 3688-3730.

Bekaert, G., & Hoerova, M. (2014). The VIX, the variance premium and stock market volatility. Journal of Econometrics, 183(2), 181-192.

Bekiros, S., Gupta, R., & Kyei, C. (2016). On economic uncertainty, stock market predictability and nonlinear spillover effects. The North American Journal of Economics and Finance, 36, 184-191.

Bilson, C. M., Brailsford, T. J., & Hooper, V. C. (2002). The explanatory power of political risk in emerging markets. International Review of Financial Analysis, 11(1), 1-27.

Bimha, A., & Nhamo, G. (2017). Sustainable Development, Share Price and Carbon Disclosure Interactions: Evidence From South Africa’s JSE 100 Companies. Sustainable Development, 25(5), 400-413.

Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327.

Brooks, C. (2019). Introductory econometrics for finance. Cambridge university press.

Cermeno, R., & Suleman, M.T. (2014). Country Risk and Volatility of Stock Returns: Panel-GARCH Evidence for Latin America. Available at SSRN 2482038.

Chinzara, Z. (2011). Macroeconomic uncertainty and conditional stock market volatility in South Africa. South African Journal of Economics, 79(1), 27-49.

Chopra, V.K., & Ziemba, W.T. (2013). The effect of errors in means, variances, and covariances on optimal portfolio choice. In Handbook of the Fundamentals of Financial Decision Making: Part I (pp. 365-373): World Scientific.

Dickey, D.A., & Fuller, W.A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a), 427-431.

Engle, R.F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. 987-1007.

Engle, R.F., & Bollerslev, T. (1986). Modelling the persistence of conditional variances. Econometric Reviews, 5(1), 1-50.

Engle, R.F., Lilien, D.M., & Robins, R. P. (1987). Estimating time varying risk premia in the term structure: The ARCH-M model. Econometrica: Journal of the Econometric Society, 55(2), 391-407.

Engle, R.F., & Patton, A.J. (2004). Impacts of trades in an error-correction model of quote prices. Journal of Financial Markets, 7(1), 1-25.

Erb, C.B., Harvey, C.R., & Viskanta, T.E. (1995). Country risk and global equity selection. Journal of Portfolio Management, 21(2), 74-83.

Erb, C.B., Harvey, C.R., & Viskanta, T.E. (1996). Political risk, economic risk, and financial risk. Financial Analysts Journal, 52(6), 29-46.

Fama, E. F. (1965). The behavior of stock-market prices. The Journal of Business, 38(1), 34-105.

Gaston, R.T., Obalade, A.A. and Muzindutsi, P.F. (2020). Financial Crisis and Stock Return Volatility of the JSE General Mining Index: GARCH Modelling Approach. The Journal of Accounting and Management, 10(3), 114-12..

Guo, H., & Kliesen, K.L. (2005). Oil price volatility and US macroeconomic activity. Review-Federal Reserve Bank of Saint Louis, 87(6), 669.

Hassan, M.K., Maroney, N.C., El-Sady, H.M., & Telfah, A. (2003). Country risk and stock market volatility, predictability, and diversification in the Middle East and Africa. Economic Systems, 27(1), 63-82.

Hentschel, L. (1995). All in the family nesting symmetric and asymmetric garch models. Journal of Financial Economics, 39(1), 71-104.

Hoshi, T., Kashyap, A., & Scharfstein, D. (1991). Corporate structure, liquidity, and investment: Evidence from Japanese industrial groups. The Quarterly Journal of Economics, 106(1), 33-60.

Hoti, S., McAleer, M., & Shareef, R. (2005). Modelling country risk and uncertainty in small island tourism economies. Tourism Economics, 11(2), 159-183.

Howell, L.D. (2011). International country risk guide methodology. East Syracuse, NY: PRS Group.

Howell, L.D. (2013). ICRG Methodology. The PRS Group. Retrieved 10 February 2019 from: https://www.prsgroup.com.

Howell, L.D., & Chaddick, B. (1994). Models of political risk for foreign investment and trade: An assessment of three approaches. The Columbia Journal of World Business, 29(3), 70-91.

Makoko, K., & Muzindutsi, P.F. (2018). Modelling Return Volatility in the Main Board and the Alternative Exchange of the Johannesburg Stock Exchange: Application of GARCH Models. EuroEconomica, 37(3).

Miah, M., & Rahman, A. (2016). Modelling Volatility of Daily Stock Returns: Is GARCH (1, 1) Enough? American Scientific Research Journal for Engineering, Technology, and Sciences, 18(1), 29-39.

Næs, R., Skjeltorp, J.A., & Odegaard, B.A. (2011). Stock market liquidity and the business cycle. The Journal of Finance, 66(1), 139-176.

Narayan, P.K., & Narayan, S. (2007). Modelling oil price volatility. Energy Policy, 35(12), 6549-6553.

Nelson, D.B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica: Journal of the Econometric Society, 59(2), 347-370.

Nhlapho R.N. & Muzindutsi, P.F. (2020) The Impact of Disaggregated Country Risk on the South African Equity and Bond Market. International Journal of Economics and Finance Studies, 12 (1), 189-203

Ramcharran, H. (2003). Estimating the impact of risks on emerging equity market performance: Further evidence on data from rating agencies. Multinational Business Review, 11(3), 77-90.

Rapach, D., & Zhou, G. (2013). Forecasting stock returns. In Handbook of Economic Forecasting (Vol. 2, pp. 328-383): Elsevier.

Regnier, E. (2007). Oil and energy price volatility. Energy Economics, 29(3), 405-427.

Silvennoinen, A., & Terasvirta, T. (2009). Multivariate GARCH models. In Handbook of Financial Time Series (pp. 201-229): Springer.

Suleman, M.T., & Daglish, T.C. (2015). Political uncertainty in developed and emerging markets. Available at SSRN 2647888.

Suleman, M.T., & Randal, J. (2016). Dynamics of Political Risk Rating and Stock Market Volatility. Available at SSRN 2315645.

Suleman, T., Gupta, R., & Balcilar, M. (2017). Does country risks predict stock returns and volatility? Evidence from a nonparametric approach. Research in International Business and Finance, 42, 1173-1195.

Tan, F.H. (2005). Option Pricing, the GARCH-M Approach. Erasmus University, Faculty of Economics. Retrived from: http://people.few.eur.nl/jvandenberg/bachelor_theses/fookhwabachelor.

Verma, R. (2014). Land grabs, power, and gender in East and Southern Africa: So, what’s new? Feminist Economics, 20(1), 52-75.

Wagstaff, A. (2007). The economic consequences of health shocks: evidence from Vietnam. Journal of Health Economics, 26(1), 82-100.

Wagstaff, A., & Lindelow, M. (2010). Are health shocks different? Evidence from a multi-shock survey in Laos. The World Bank.

Wooldridge, J.M. (2003). Cluster-sample methods in applied econometrics. American Economic Review, 93(2), 133-138.

Yang, C., Hwang, M.-J., & Huang, B.-N. (2002). An analysis of factors affecting price volatility of the US oil market. Energy Economics, 24(2), 107-119.




Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.