Full-text resources of CEJSH and other databases are now available in the new Library of Science.
Visit https://bibliotekanauki.pl

PL EN


2021 | 43 | 131-152

Article title

Testing for causality in mean and in variance among the U.S., China, and some Africa capital markets: A CCF approach

Content

Title variants

Languages of publication

EN

Abstracts

EN
Aim/purpose – Owing to the huge risk occasioned by negative contagion effects associ-ated with financial market linkages, markets participants and academia have continued to examine the capital market cross country interdependence at different levels. In this paper, we examined the causal relationships among the U.S., China and some top Afri-can capital market indexes. Design/methodology/approach – To examine the mean and variance causal effects, we estimated a univariate AR-EGARCH model for all capital market indexes. Then em-ployed the residual-based two-step bivariate cross-correlation function (CCF) test devel-oped by Cheung & Ng (1996). The test statistics had a well-defined asymptotic standard distribution that was robust to distributional assumptions. Findings – We detected both the feedback and unidirectional causality effects among African capital markets. These results show that African financial markets are still not fully integrated within the African continent. Expectedly, the results from our empirical analysis showed the existence of a unidirectional causality both in mean and variance from the U.S. and Chinese markets to African capital markets. This demonstrated that events in the U.S. and China are not irrelevant to African markets. Research implications – Owing to the fact that knowledge of other financial markets provides adequate information about a market situation, the results from this research paper will be helpful for the policymakers of African countries in shaping their econom-ic policies, help investors diversify investments with less risk, and international portfolio managers make portfolio allocation decisions. Originality/value/contribution – This paper examined the mean and risk dynamics of three top African, the U.S., and Chinese capital markets with their inter-dependence using the CCF approach. Furthermore, to the best of our knowledge, no previous re-search paper on this issue exists.

Year

Volume

43

Pages

131-152

Physical description

Contributors

  • Department of International Economics, School of Economics, Ural Federal University, Ekaterinburg, Russia

References

  • Akkoc, U., & Civcir, I. (2019). Dynamic linkage between strategic commodities and stock market in Turkey: Evidence from SVAR-DCC-GARCH model. Resources Policy, 62, 231-239. https://doi.org/10.1016/j.resourpol.2019.03.017
  • Atenga, E. M. E., & Mougue, M. (2020). Return and volatility spillover to African equi-ty markets and their determinants. Empirical Economics. Retrieved from https:// link.springer.com/article/10.1007/s00181-020-01881-9
  • Awad, A., & Yussof, I. (2017). Africa’s economic regionalism: Is there any other obsta-cle? Journal of Economic Studies, 44(3), 344-361. https://doi.org/10.1108/JES-02-2016-0039
  • Bollerslev, T. (1986, April). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327. https://doi.org/10.1016/0304-4076(86) 90063-1
  • Bouri, E., Chen, Q., Lien, D., & Lv, X. (2017, March). Causality between oil prices and the stock market in China: The relevance of the reformed oil product pricing mech-anism. International Review of Economics and Finance, 48(C), 34-48. https:// doi.org/10.1016/j.iref.2016.11.004
  • Belkhouja, M., & Boutahary, M. (2011, May). Modeling volatility with time varying FIGARCH models. Economic Modelling, 28(3), 1106-1116. https://doi.org/10.1016/ j.econmod.2010.11.017
  • Ben Nasr, A., Ajmi, A. N., & Gupta, R. (2014). Modelling the volatility of the Dow Jones Islamic Market World Index using a fractionally integrated time varying GARCH (FITVGARCH) model. Applied Financial Economics, 24(14), 993-1004. https://doi.org/10.1080/09603107.2014.920476
  • Ben Nasr, A., Boutahar, M., & Trabelsi, A. (2010). Fractionally integrated time varying GARCH model. Statistical Methods and Application, 19(3), 399-430. https:// doi.org/10.1007/s10260-010-0131-2
  • Bhar, R., & Hamori, S. (2005, May). Causality in variance and the type of traders in crude oil futures. Energy Economics, 27(3), 527-539. https://doi.org/10.1016/ j.eneco.2004.12.003
  • Bissoondoyal-Bheenick, E., Brooks, R., Wei, C., & Hung, X. D. (2018). Volatility spill- -over between the US, Chinese and Australian Stock Markets. Australian Journal of Management, 43(2). https://doi.org/10.1177/0312896217717305
  • Bonga-Bonga, L., & Hoveni, J. (2011). Volatility spillovers between the equity market and foreign exchange market in South Africa (Working Papers, No. 252). Cape Town: Economic Research Southern Africa. Retrieved from https://ideas.repec.org/ p/rza/wpaper/252.html
  • Boubaker, A., & Sebai, S. (2009). Inter-market information flow: A non-linear approach. Applied Economics Letters, 16(10), 1009-1015. https://doi.org/10.1080/17446540 802345414
  • Breitung, J., & Candelon, B. (2006, June). Testing for short-and long run causality: A frequency-domain approach. Journal of Econometrics, 132, 363-378. https:// doi.org/10.1016/j.jeconom.2005.02.004
  • Cheung, Y.-W., & Ng, L. K. (1996, May-June). A causality-in-variance test and its ap-plication to financial market prices. Journal of Econometrics, 72, 33-48. https:// doi.org/10.1016/0304-4076(94)01714-X
  • Çevik, E. I., Çevik, N. K., & Gurkan, S. (2012). Analyzing of relationship among stock markets of the U.S., Germany and Turkey with MS-VAR model. Journal of BRSA Banking and Financial Markets, 6(1), 133-155. Retrieved from https://ideas. repec.org/a/bdd/journl/v6y2012i1p133-155.html
  • Diebold, F. X., & Nerlove, M. (1989). The dynamics of exchange rate volatility: A mul-tivariate latent factor ARCH model. Journal of Applied Econometric, 4, 1-21. https://doi.org/10.1002/jae.3950040102
  • Diebold, F. X., & Yilmaz, K. (2009, January). Measuring financial asset return and vola-tility spillovers with application to global equity markets. The Economic Journal, 119(534), 158-171. https://doi.org/10.1111/j.1468-0297.2008.02208.x
  • Dewandaru, G., Masih, R., & Masih, M. (2017, September). Regional spillover across transitioning emerging and frontier equity markets: A multi-time scale wavelet analysis. Economic Modelling, 65, 30-40. https://doi.org/10.1016/j.econmod.2017. 04.026
  • El Abed, R., Boukadida, S., & Jaidane, W. (2019). Financial stress transmission from sovereign credit market to financial market: A multivariate FIGARCH-DCC ap-proach. Global Business Review, 20(5), 1122-1140. https//doi.org/10.1177/0972150 919846994
  • Engle, R. F. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987-1007. https:// doi.org/10.2307/1912773
  • Ekpo, A., & Chuku, C. (2017). Regional financial integration and economic activity in Africa. Journal of African Economies, 26, 40-75. https://doi.org/10.1093/jae/ejx030
  • Feldman, R. A., & Wagner, N. (2002). The financial sector, macroeconomic policy and performance. EIB Papers, 7(2), 13-30. Retrieved from http://hdl.handle.net/ 10419/44819
  • Giovannetti, G., & Velucchi, M. (2013). A spillover analysis of shock 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
  • Gradojevic, N., & Dobardzic, E. (2013). Causality between Regional Stock Markets: A frequency domain approach. Panoeconomicus, 60(5), 633-647, https://doi.org/ 10.2298/PAN1305633G
  • Granger, C. W. J. (1969, July). Investigating causal relations by econometric models and cross spectral methods. Econometrical, 37, 424-438. https://doi.org/10.2307/ 1912791
  • Granger, C. W. J. (1980). Testing for causality: A personal viewpoint. Journal of Eco-nomic Dynamics and Control, 2, 52-329. https://doi.org/10.1016/0165-1889(80) 90069-X
  • Grant, W., & Wilson, G. K. (2012). The consequences of the global financial crisis: The rhetoric of reform and regulation. Oxford: Oxford University Press. https://doi.org/ 10.1093/acprof:oso/9780199641987.001.0001
  • Gumede, V., Oloruntoba, S. O., & Kamga, S. D. (2020). Regional integration and mi-gration in Africa: Lessons from Southern and West Africa. https://doi.org/ 10.1163/9789004411227
  • Guo, B., & Ibhagui, O. (2019). China-Africa stock market linkages and the global finan-cial crisis. Journal of Asset Management, 20, 301-316. https://doi.org/10.1057/ s41260-019-00122-8
  • Hafner, C. M., & Herwartz, H. (2006, September). A Lagrange multiplier test for causal-ity in variance. Economic Letters, 93, 137-141. https://doi.org/10.1016/j.econlet. 2006.04.008
  • Hanabusa, K. (2009, May). Causality relationship between the prices of oil and econom-ic growth in Japan. Energy Policy, 37(5), 1953-1957, https://doi.org/10.1016/ j.enpol.2009.02.007
  • Kang, S. H., & Yoon, S.-M. (2020, April). Dynamic correlation and volatility spillovers across Chinese stock and commodity futures markets. International Journal of Fi-nance and Economics, 25(2), 261-273. https://doi.org/10.1002/ijfe.1750
  • Kiliç, R. (2011). A conditional variance tale from an emerging economy’s freely floating exchange rate. Applied Economics, 43(19), 2465-2480. https://doi.org/10.1080/ 00036840903266812
  • Marozva, G. (2017). Africa stock market cross-market linkages: A time-varying dynam-ic conditional correlations (DCC-GARCH) approach. Journal of Applied Business Research, 33(2), 321. https://doi.org/10.19030/jabr.v33i2.9904
  • Mensi, W., Hammoudeh, S., Nguyen, D. K., & Kang, S. H. (2016, March). Global fi-nancial crisis and spillover effects among the U.S. and BRICS stock markets. International Review of Economics and Finance, 42, 257-276. https://doi.org/10. 1016/j.iref.2015.11.005
  • Moon, G.-H., & Yu, W.-C. (2010). Volatility spillovers between the US and China stock markets: Structural break test with symmetric and as symmetric GARCH ap-proaches. Global Economic Review, 39(2), 129-149. https://doi.org/10.1080/ 1226508X.2010.483834
  • Nishimura, Y., Tsutsui, Y., & Hirayama, K. (2016, September). The Chinese stock mar-ket does not react to the Japanese market: Using intraday data to analyzed return and volatility spillover effects. Japanese Economic Review, 67(3), 280-294. https://doi.org/10.1111/jere.12086
  • Nelson, D. B. (1991, March). Conditional heteroscedasticity in asset returns: A new approach. Econometrical, 59(2), 347-370. https://doi.org/10.2307/2938260
  • Onay, C., & Ünal, G. (2012). Cointegration and extreme value analyses of Bovespa and Istanbul stock exchanges. https://doi.org/10.2139/ssrn.1636183
  • Osabuohien-Irabor, O. (2015). Impact of oil price shock on foreign currency and stock markets: The Nigeria perspective. Journal of Applied Science, Engineering and Technology, 15(1), 34-42.
  • Osabuohien-Irabor, O. (2020). Investors’ attention: Does it impact the Nigerian stock market activities. Journal of Economics and Development, 23(1), 59-76. https:// doi.org/10.1108/JED-02-2020-0015
  • Phume, M. P., & Bonga-Bonga, L. (2018). Return and volatility spillovers between South African and Nigerian equity market (Munich Personal RePEc Archive, No._87638). Retrieved from https://mpra.ub.unimuenchen.de/87638/1/MPRA_ paper_87638.pdf
  • Qiao, Z., Li, Y., & Wong, W. K. (2011). Regime-dependent relationships among the stock markets of the US, Australia and New Zealand: A Markov switching VAR approach. Applied Financial Economics, 21(24), 1831-1841. Retrieved from http:// hdl.handle.net/10.1080/09603107.2011.595678
  • Ross, S. A. (1989, March). Information and volatility: The no-arbitrage martingale ap-proach to timing and resolution irrelevancy. Journal of Finance, 44(1), 1-17. https://doi.org/10.2307/2328272
  • Ratanapakorn, O., & Sharma, S. C. (2002). Interrelationships among regional stock indices. Review of Financial Economics, 11, 91-108, https://doi.org/10.1016/ S1059-0560(02)00103-X
  • Rashid, A. (2007, August). Stock prices and trading volume: An assessment for linear and nonlinear Granger causality. Journal of Asian Economics, 18(4), 595-612. https://doi.org/10.1016/j.asieco.2007.03.003
  • Sabkha, S., de Peretti, C., & Mezzez Hmaied, D. (2019). International risk spill over in sovereign credit markets: An empirical analysis. Managerial Finance, 45(8), 1020-1040. https://doi.org/10.1108/MF-11-2017-0490

Document Type

Publication order reference

Identifiers

ISSN
1732-1948

YADDA identifier

bwmeta1.element.cejsh-9ccad087-1194-40e4-b8dd-7324d519346b
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.