A STUDY ON THE VOLATILITY SPILLOVER BETWEEN NIGERIAN AND BRICS ECONOMIES USING MULTIVARIATE GARCH MODELS
Abstract
BRIC-African relation has been of interest to key stakeholders especially given the inclusion of South Africa. In the existing literature some researchers hypothesized inclusion of Nigeria will accelerate BRICS objective of enhancing market access to ensure rapid economic growth among other objectives. This study utilized daily exchange rates of Naira/Dollar together with BRICS Dollar exchange rate for a period of 18 years. The study aimed to determine the volatility spillover between Nigerian and BRICS nations via Multivariate GARCH family: VECH, DBEKK and CCC Models. The result of VECH and DBEKK Models showed that all parameters were significant at 5% level, indicating clearly that there is positive impact of Exchange Rate shocks of Nigeria on the Exchange Rate Volatility of the BRICS economies, while for the CCC model only one parameter was significant at 5% level. This clearly indicated the existence of positive impacts of Exchange rates shocks of Nigeria on the Exchange Rate Volatility of the BRICS economies. On the other hand, only VECH model was able to capture the volatility spillover (own and cross) both on negative direction, suggesting a causal relationship between past volatility shocks in Nigeria and current volatility in the BRICS economies. Conclusively based on the information above VECH model was found to be appropriate to capture the volatility spillover between Nigerian exchange rate and that of the BRICS nations.
References
Abimbola, D. (2016). Russia/Nigeria Diplomatic Ties: Historical perspective. European Scientific Journal. Vol 12(1). P 323-334. DOI: https://doi.org/10.19044/esj.2016.v12n1p323
Ademuyiwa I, Onyekwena C, Taiwo O & Uneze E. (2014) "Nigeria and the BRICS: Current and Potential Trade Relations and Their Implications for the Nigerian Economy", Occasional Paper 184. Johannesburg: South African Institute of In- ternational Affairs.
Aja, A.A. (2012) "Nigeria-China Relations: Dynamics, Challenges and Strategic Options", in Thomas A. Imobighe and Warisu O. Alli (eds.) Perspectives on Nigeria’s National Politics and External Relations: Essays in Honour of Professor
A. Bolaji Akinyemi, Ibadan: University Press PLC, pp. 347-366
Alao, A (2011). "Nigeria and the BRICS: Diplomatic, Trade, Cultural and Military Relations", South African Foreign Policy and African Drivers Programme: SAIIA: Occasional paper. No. 101.
Bala D.A. and Takimoto T. (2017). "Stock Markets Volatility Spillovers during Financial Crises: A DCC-MGARCH with skewed-t density approach" 17: 248. DOI: https://doi.org/10.1016/j.bir.2017.02.002
Benjamin I. E. (2019). The impact of exchange rate volatility on the Nigerian economic growth: An empirical investigation Journal of Economics & Management, 37(3), 45-68. http:// doi.org/10.22367/jem.2019.37.03 DOI: https://doi.org/10.22367/jem.2019.37.03
Bollerslev, T. (1990). Modeling the coherence in short-run nominal exchange rates: A Multivariate generalized ARCH model. The review of Economics and Statistics, 498-505. DOI: https://doi.org/10.2307/2109358
Breusch T. S. (1978). Testing for autocorrelation in dynamic linear models. Australian Economic Papers, 17, 334-355. DOI: https://doi.org/10.1111/j.1467-8454.1978.tb00635.x
Bunnag, T. (2015). Hedging petroleum futures with Multivariate GARCH Models. International Journal of Energy Economics and Policy, 5(1), 105-120.
Das R. and Debnath A. (2022). Analyzing the COVID-19 Pandemic Volatility Spillover Influence on the Collaboration of Foreign and Indian Stock Markets. Network of Scientific Journals from Latin America and the Caribbean, Spain and PortugalVol. 14, no. 2, pp. 411-452 DOI: https://doi.org/10.14718/revfinanzpolitecon.v14.n2.2022.5
Engle, R. F., and Kroner, K. F. (1995). Multivariate simultaneous generalized ARCH. Econometric Theory 11, 01, 122-150. DOI: https://doi.org/10.1017/S0266466600009063
Folarin S. F., Jide I., & Felix C. (2016). Nigeria and the BRICS: Regional Dynamics in Developing Economies’ Studies. Department of Political Science and International Relations Covenant University Ota, Ogun State, Nigeria.
Garrick K. (2013). “Bilateral business between Nigeria and Brazil: The Way Forward” Retrieved August 8, 2022 from http://www.vanguardngr.com/2013/08/nigeria-brazil-trade-below-volume- potential/
Hammoudeh S., Ramazan S., Mehmet U. and Tengdong L. (2013). The dynamics of BRICS’s country risk ratings and domestic stock markets, U.S stock market and oil price. Mathematics and Computer in Simulation 94. 277-294 www.sciencedirect.com DOI: https://doi.org/10.1016/j.matcom.2012.01.002
Hashiru M. and Tufekci O. (2018). Putting the ’N’ or replacing the ’S’ in the BRICS, Nigeria’s rise as an Emerging Power. Journal of management and economics re- search Volume: 16, issue: 3, September 2018, pp. 11-23 DOI: https://doi.org/10.11611/yead.465370
IMF (2021). International Financial Statistics (IFS) database. https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(PPP)
Joseph, C. E. (2013). An Evaluation of Nigeria - South Africa Bilateral Relations.
Journal of International Relations and Foreign Policy, 1(1); 32-40.
Joshi P. (2014). Multivariate GARCH Model of Transmission of volatility: A Study of BRIC Stock Markets. International Journal of Marketing & Financial Management Volume 2, issue 7, Aug-2014, pp 01-10.
Marcus L. (2023). Visualising The BRICS expansion in 4 Charts Graphics/Design: Bhabna Banerjee. Publish Augsut 24, 2023
Mohammed M. T., Ngozi V. A. and Tari K. (2023). Returns and Volatility Spillover
between Nigeria and selected global stock markets: a Diebold- Yilmaz approach https://www.researchgate.net/publication/370818478
Mthuli, N., L. L. Charles, and V. Desire, (2011). Brazil’s Economic Engagement with Africa. African Development Bank Group Chief Economist Complex. Retrieved November 24, 2015.
Musa T., Yakubu M. & Gulumbe S. U. (2014). Exchange rate volatility of Nigerian Naira against some major currencies in the world: An application of multivariate GARCH models. International Journal of Mathematics and Statistics Invention (IJMSI) ISSN: 2321 – 4759
Musyoki D., Pokhariyal G. P., & Pundo M. (2012). The impact of real exchange rate volatility on economic growth: Kenyan evidence. Business and Economic Horizons, 7(1), 59-75. Retrieved from https://ageconsearch.umn.edu/bitstream/249373/2/v7_1_5.pdf DOI: https://doi.org/10.15208/beh.2012.5
O’Neill J. and Goldman S. (2001). Building better global economic BRICs. Goldman Sachs.
Opusunji M. I., Akyuz M., & Inim E. V. (2020). Assessment of India-Nigeria Trade Relations (1999-2018). American International Journal of Business Management (AIJBM). ISSN- 2379-106X, www.aijbm.com Volume 3, Issue 5 (May 2020), PP 62-70
Sasu D. D. (2022). Population of Nigeria 1950 – 2022. Statista Accounts. Online; ttps/www.statista.com. March 10
Sule, A. (2011). BRICS can build common currency. China Daily Europe, 21th of April, 2011. Retrieved on May 3rd, 2011 from http://europe.chinadaily.com.cn/epaper/2011- 04/08/content_12291921.htm
Trivedi J., Spulbar C., Biraou R. and Mehdiabadi A. (2021). Modelling volatility spillovers, cross-market correlation and co-movements between stock markets in European Union:an empirical case study. Business, Management and Economics Engineering ISSN: 2669-2481 / eISSN: 2669-249X 2021 Volume 19 Issue 1: 70–90 DOI: https://doi.org/10.3846/bmee.2021.13588
Tsay, R.S. (2005). Analysis of Financial Time Series, Wiley, New Jersey DOI: https://doi.org/10.1002/0471746193
Tsay, R. (2010). Analysis of Financial Time Series, Third Edition. John Wiley & Sons, Inc., 3 edition. DOI: https://doi.org/10.1002/9780470644560
Vardi N. (2011) Brazil lead BRICS in export growth-WTO. Forbes, March 24th, 2011. Retrieved on May 21st, 2021 from http://blogs.forbes.com/kenrapoza/2011/03/14/brazil-leads-brics-inexport-growth-wto/
Yamakawa T., Ahmed S., & Kelston A. (2009). BRICs monthly.Issue No 09/07, August 6, 2009. Goldman Sachs Global Economics, Com- modities and Strategy Research. http://www2.goldmansachs.com/ideas/brics/drivers-of-globalconsumption-doc.pdf
Copyright (c) 2024 FUDMA JOURNAL OF SCIENCES
This work is licensed under a Creative Commons Attribution 4.0 International License.
FUDMA Journal of Sciences
