100
Views
2
CrossRef citations to date
0
Altmetric
Research Article

Network Granger Causality Linkages in Nigeria and Developed Stock Markets: Bayesian Graphical Analysis

ORCID Icon, ORCID Icon &

References

  • Ahelegbey, D. F., Billio, M., & Casarin, R. (2016). Bayesian graphical models for structural vector autoregressive processes. Journal of Applied Econometrics, 31(2), 357–386. https://doi.org/10.1002/jae.2443
  • Ahmed, A. D., & Huo, R. (2018). China–africa financial markets linkages: Volatility and interdependence. Journal of Policy Modeling, 40(6), 1140–1164. https://doi.org/10.1016/j.jpolmod.2018.05.002
  • Alfreedi, A. A. (2019). Shocks and volatility spillover between stock markets of developed countries and GCC stock markets. Journal of Taibah University for Science, 13(1), 112–120. https://doi.org/10.1080/16583655.2018.1544348
  • Awokuse, T. O., & Bessler, D. A. (2003). Vector autoregressions, policy analysis, and directed Acyclic Graphs: An application to the U.S. economy. Journal of Applied Economics, 6(1), 1–24. https://doi.org/10.1080/15140326.2003.12040583
  • Bai, Z. D., Hui, Y. C., Jiang, D. D., Lv, Z. H., Wong, W. -K., Zheng, S. H., & Chen, C. W. S. (2018). A new test of multivariate nonlinear causality. Plos One, 13(1), e0185155. https://doi.org/10.1371/journal.pone.0185155
  • Bala, D. A., & Takimoto, T. (2017). Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach. Borsa Istanbul Review, 17(1), 25–48. https://doi.org/10.1016/j.bir.2017.02.002
  • Bekiros, S. D. (2014). Contagion, decoupling and the spillover effects of the US financial crisis: Evidence from the BRIC markets. International Review of Financial Analysis, 33, 58–69. https://doi.org/10.1016/j.irfa.2013.07.007
  • Bhandari, A., & Kamaiah, B. (2020). Time-varying nature of stock market interdependence: A global perspective time-varying nature of stock market interdependence-a global perspective. Economic and Political Weekly, 55(13). https://ssrn.com/abstract=3564211
  • Bhar, R., & Nikolova, B. (2009). Return, volatility spillovers and dynamic correlation in the BRIC equity markets: An analysis using a bivariate EGARCH framework. Global Finance Journal, 19(3), 203–218. https://doi.org/10.1016/j.gfj.2008.09.005
  • Billio, M., & DiSanzo, S. (2015). Granger-causality in Markov switching models. Journal of Applied Statistics, 42(5), 956–966. https://doi.org/10.1080/02664763.2014.993367
  • Blanchard, O., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturnbances. The American Economic Review, 79(4), 655–673.
  • Bloomberg. (2020). New York, United States. https://www.bloomberg.com
  • Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327. https://doi.org/10.1016/0304-4076(86)90063-1
  • Central Bank of Nigeria, Statistical Bulletin, 2021. Accessed 28th March, 2021. www.cbn.org.ng
  • Collins, D., & Abrahamson, M. (2004). African equity markets and the process of global financial integration. South African Journal of Economics, 72(4), 658–683. https://doi.org/10.1111/j.1813-6982.2004.tb00129.x
  • Collins, D., & Biekpe, N. (2003). Contagion and interdependence in African stock markets. South African Journal of Economics, 71(1), 181–194. https://doi.org/10.1111/j.1813-6982.2003.tb00077.x
  • Conlon, T., Corbet, S., & McGee, R. J. (2020). Are cryptocurrencies a safe haven for equity markets? An international perspective from the COVID-19 pandemic. Research in International Business and Finance, 54, 101248. https://doi.org/10.1016/j.ribaf.2020.101248
  • Corander, J., & Villian, M. (2006). A Bayesian Approach to Modelling Graphical Vector Autoregressions. Journal of Time Series Analysis, 27(1), 141–156. https://doi.org/10.1111/j.1467-9892.2005.00460.x
  • Demiralp, S., & Hoover, K. D. (2003). Searching for the causal structure of a vector autoregression. Oxford Bulletin of Economics and Statistics, 65(s1), 745–767. https://doi.org/10.1046/j.0305-9049.2003.00087.x
  • 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. https://doi.org/10.1080/01621459.1979.10482531
  • Disli, M., Nagayev, R., Salim, K., Rizkiah, S. K., & Aysan, A. F. (2021). In search of safe haven assets during COVID-19 pandemic: An empirical analysis of different investor types. Research in International Business and Finance, 58, 101461. https://doi.org/10.1016/j.ribaf.2021.101461
  • Engle, R. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal of the Econometric Society, 50(4), 987–1007. https://doi.org/10.2307/1912773
  • Forbes, K. J., & Rigobon, R. (2002). No Contagion, only interdependence: Measuring stock market comovements. The Journal of Finance, 57(5), 2223–2261. https://doi.org/10.1111/0022-1082.00494
  • French, K. R., Schwert, G. W., & Stambaugh, R. F. (1986). Expected stock returns and volatility. Working Paper Series No. MERC 85-10.
  • Gallo, G. M., & Otranto, E. (2007). Volatility Spillovers, Interdependence And Co-movements: A Markov SWITCHING APPRoach, Working Paper 2007/11, Dipartimento di Statistica G. Parenti, Viale Morgagni 59 – 50134 Firenze www.ds.unifi.it
  • Gebka, B., & Serwa, D. (2006). Are Financial spillovers stable across regimes? Evidence from the 1997 Asian Crisis. Journal of International Financial Markets, Institutions and Money, 16(4), 301–317. https://doi.org/10.1016/j.intfin.2005.03.002
  • Gilmore, C. G., & McManus, G. M. (2002). International portfolio diversification: US and Central European equity markets. Emerging Markets Review, 3(1), 69–83. https://doi.org/10.1016/S1566-0141(01)00031-0
  • Giovannetti, G., & Velucchi, M. (2013). A spillover analysis of shocks from US, UK and China on African financial markets. Review of Development Finance, 3(4), 169–179. https://doi.org/10.1016/j.rdf.2013.10.002
  • Granger, C. W. J. (1969). Investigating causal relations by econometrics models and cross-spectral methods. Econometrica, 37(3), 424–438.
  • Grzegorczyk, M., & Husmeier, D. (2008). Improving the structure MCMC sampler for Bayesian networks by introducing a new edge reversal move. Journal of Machine Learning, 71(2–3), 265–305. https://doi.org/10.1007/s10994-008-5057-7
  • Hakim, A., & Mansur, M. (2016). Evidence of cross-country portfolio diversification benefits: The case of Saudi Arabia, https://mpra.ub.ub.uni-muenchen.de/72180/MPRA paper No. 72180.
  • Ji, Q., Bouri, E., Gupta, R., & Roubaud, D. (2018). Network causality structures among Bitcoin and other financial assets: A directed acyclic graph approach. The Quarterly Review of Economics and Finance, 70, 203–213. https://doi.org/10.1016/j.qref.2018.05.016
  • Kearney, C., & Daly, K. (1998). The causes of stock market volatility in Australia. Applied Financial Economics, 8(6), 597–605. Electronic copy available at. http://ssm.com/abstract=1734769
  • Lamba, A. S., & Otchere, I. (2001). An analysis of the dynamic relationships between the South African equity market and major world equity markets. Multinational Finance Journal, 5(3), 201–224. https://doi.org/10.17578/5-3-3
  • Liu, H., Manzoor, A., Wang, C., Zhang, L., & Manzoor, Z. (2020). The COVID-19 outbreak and affected countries stock markets response. International Journal of Environmental Research and Public Health, 17(8), 1–19. https://doi.org/10.3390/ijerph17082800
  • Madigan, York, J., Madigan, D., & Allard, D. (1995). Bayesian graphical models for discrete data. International Statistical Review, 63(2), 215–232. https://doi.org/10.2307/1403615
  • Mandelbrot, B. B. (1963). The variation of certain speculative prices. The Journal of Business, 36(4), 392–417. https://doi.org/10.1086/294632
  • Maneschiold, P. (2005). International diversification benefits between US, Turkish and Egyptian stock markets. Review of Middle East Economics and Finance, 3(2), 115–133. https://doi.org/10.1080/14753680500166458
  • Markowitz, T. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77–91.
  • Masson, P. (1998). Contagion: Monsoonal effects, spillovers, and jumps between multiple equilibria. IMF Working Paper 98/142. International Monetary Funds.
  • Mcmillan, D. G., Ziadat, S. M., & Herbst, P. (2021). The role of oil as a determinant of stock market interdependence: The case of the USA and GCC. Energy Economics, 95, 105102. https://doi.org/10.1016/j.eneco.2021.105102
  • Merton, R. C. (1980). On estimating the expected return on the market: An exploratory investigation. Journal of Financial Economics, 8(4), 323–361. https://doi.org/10.1016/0304-405X(80)90007-0
  • Mohti, W., Dionisio, A., Viera, I., & Ferreira, P. (2019). Financial contagion analysis in frontier markets: Evidence from the US subprime and the Eurozone debt crises. Physica A: Statistical Mechanics and Its Applications, 525, 1388–1398. https://doi.org/10.1016/j.Physa.2019.03.094
  • Moneta, A., & Spirtes, P. (2006). Graphical models for the identification of causal structure in multivariate time series models. Joint Conference on Information Sciences Proceedings. Atlantis Press, Amsterdam, Netherlands.
  • National Bureau of Statistics. (2021). Accessed 28th, Janauary, 2022. Independence Avenue Central Business District, www.nigerianstat.gov.ng
  • Nigerian exchange. (2021), Domestic & foreign portfolio investment report of Nigerian Exchange Limited. www.ngxgroup.com/exchange/data/foreignportfolio-investment-report. Acessed 1st April, 2022.
  • Nigerian Stock Market (NSE). (2020). Lagos, Nigeria. www.nse.com.ng
  • Officer, R. R. (1973). The variability of the market factor of the New York stock exchange. The Journal of Business, 46(3), 434–453. https://doi.org/10.1086/295551
  • Olayungbo, D. O. (2019). Bayesian graphical model application for monetary policy and macroeconomic performance in Nigeria. In D. Mcnair (Ed.), A Bayesian Network Advances and Novel Applications. London, United Kingdom: IntechOpen. https://doi.org/10.5772/Intechopen.75254.
  • Oloko, T. F. (2018). Portfolio diversification between developed and developing stock markets: The case of US and UK investors in Nigeria. Research in International Business and Finance, Elsevier, 45, 219–222. https://doi.org/10.1016/j.ribaf.2017.07.153
  • Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regressions. Biometrica, 75(2), 335–346. https://doi.org/10.1093/biomet/75.2.335
  • Rehman, M. U., Ahmad, N., Shahzad, S. J. H., & Xuan Vinh, V. (2022). Dependence dynamics of shocks market during COVID-19. Emerging Markets Review, 51(Part B). https://doi.org/10.1016/j.ememar.2022.100894
  • Sarantitis, G. A., Papadimitriou, T., & Gogas, P. (2016). A network analysis of the United Kingdom’s consumer price index. Computational Economics, 51(2), 173–193. https://doi.org/10.1007/s10614-016-9625-9
  • Schwert, G. W., (1989). Business cycles, financial crises and stock volatility. Carnegie-Rochester conferences series on public policy (Vol. 31, pp. 83–126). New York, United States: North-Holland.
  • Shehzad, K., Liu, X., Tiwari, A., Anf, M., & Rauf, A. (2019). Analysing time difference and volatility linkages between China and the United States during financial crises and stable period using VARX-DCC-MEGARCH model. International Journal of Finance & Economics, 26(1), 814–833. https://doi.org/10.1002/ijfe.1822
  • Spirtes, P., Glymour, C., & Scheines, R. (2000). Causation, prediction, and search. MIT Press.
  • Su, E. (2020). Testing stock market contagion properties between large and small stock markets. Review of Quantitative Finance and Accounting, 57(1), 147–202. https://doi.org/10.1007/s11156-020-00942-5
  • Swanson, N. R., & Granger, C. W. J. (1997). Impulse response functions based on a causal approach to residual orthogonalization in Vector Autoregressions. Journal of the American Statistical Association, 92(437), 357–367. https://doi.org/10.1080/01621459.1997.10473634
  • Toda, H. Y., & Phillips, P. C. B. (1993). Vector autoregressions and causality. Econometrica, 61(6), 1367–93. https://doi.org/10.2307/2951647
  • Trading economics. 2021, https://tradingeconomics.com. Accessed 31th December, 2021.
  • World Federating Exchange.2021. World-exchanges.org. Accessed 28th December, 2021.
  • Yin, L., & Ma, X. (2018). Causality between oil shocks and exchange rate: A Bayesian, graph-based VAR approach. \Physica A: Statistical Mechanics and its Applications, 508, 434–453. https://doi.org/10.1016/j.physa.2018.05.064
  • Yi, Y., Zhang, Y., Xiao, J., & Wang, X. (2022). Forecasting the Chinese stock market volatility with G7 Stock market volatilities: A scaled PCA approach. Emerging Markets Finance and Trade, 58(13), 3639–3650. https://doi.org/10.1080/1540496x.2022.2061348

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.