Nonlinear bidirectional multiscale volatility transmission effect between stocks and exchange rate markets in the selected African countries

References

• Abounoori, E., Elmi, Z., & Nademi, Y. (2016). Forecasting Tehran stock exchange volatility; Markov switching GARCH approach. Physica A: Statistical Mechanics and Its Applications, 445, 264–282. doi: https://doi.org/10.1016/j.physa.2015.10.024
   Web of Science ®Google Scholar
• Adi, A. A. (2017). Returns effect, shocks and volatility transmission between foreign exchange-stock markets in Nigeria. Academic Journal of Economic Studies, 3(1), 29–38.
   Google Scholar
• Adjasi, C., Harvey, S. K., & Agyapong, D. (2008). Effect of exchange rate volatility on the Ghana stock exchange. African Journal of Accounting, Economics, Finance and Banking Research, 3(3), 29–47.
   Google Scholar
• Andrikopoulos, A., Samitas, A., & Kougepsakis, K. (2014). Volatility transmission across currencies and stock markets: GIIPS in crisis. Applied Financial Economics, 24(19), 1261–1283. doi: https://doi.org/10.1080/09603107.2014.925054
   Google Scholar
• Apergis, N., & Rezitis, A. (2001). Asymmetric cross-market volatility spillovers: Evidence from daily data on equity and foreign exchange markets. The Manchester School, 69(s1), 81–96. doi: https://doi.org/10.1111/1467-9957.69.s1.5
   Web of Science ®Google Scholar
• Asamoah, M. E., Adjasi, C. K. D., & Alhassan, A. L. (2016). Macroeconomic uncertainty, foreign direct investment and institutional quality: Evidence from Sub-Saharan Africa. Economic Systems, 40(4), 612–621. doi: https://doi.org/10.1016/j.ecosys.2016.02.010
   Web of Science ®Google Scholar
• Atenga, E. M. E., & Mougoue, M. (2020). Return and volatility spillovers to African equity markets and their determinants. Empirical Economics. https://doi.org/https://doi.org/10.1007/s00181-020-01881-9
   Google Scholar
• Babecky, J., Komarek, L., & Komarkova, Z. (2013). Financial integration at times of financial instability. Finance a úvěr: Czech Journal of Economics and Finance, 63(1), 25–45.
   Web of Science ®Google Scholar
• Boako, G., Omane-Adjepong, M., & Frimpong, J. M. (2016). Stock returns and exchange rate nexus in Ghana: A Bayesian quantile regression approach. South African Journal of Economics, 84(1), 149–179. doi: https://doi.org/10.1111/saje.12096
   Web of Science ®Google Scholar
• Bonga-Bonga, L., & Hoveni, J. (2013). Volatility spillovers between the equity market and foreign exchange market in South Africa in the 1995–2010 period. South African Journal of Economics, 81(2), 260–274. doi: https://doi.org/10.1111/saje.12001
   Web of Science ®Google Scholar
• Borojo, D. G., & Yushi, J. (2020). The impacts of institutional quality and business environment on Chinese foreign direct investment flow to African countries. Economic Research-Ekonomska Istraživanja, 33(1), 26–45. doi: https://doi.org/10.1080/1331677x.2019.1696691
   Web of Science ®Google Scholar
• Cai, J. (1994). A Markov model of switching-regime ARCH. Journal of Business and Economic Statistics, 12(3), 309–316. doi: https://doi.org/10.2307/1392087
   Web of Science ®Google Scholar
• Caglayan, M., Kocaaslan, O. K., & Mouratidis, K. (2016). Regime dependent effects of inflation uncertainty on real growth: A Markov switching approach. Scottish Journal of Political Economy, 63(2), 135–155. doi: https://doi.org/10.1111/sjpe.12087
   Web of Science ®Google Scholar
• Cevik, N. K., Dibooglu, S., & Kutan, A. M. (2016). Real and financial sector studies in Central and Eastern Europe: A review. Finance a úvěr: Czech Journal of Economics and Finance, 66(1), 2–31.
   Web of Science ®Google Scholar
• Conlon, T., &Cotter, J. (2012). An empirical analysis of dynamic multiscale hedging using wavelet decomposition. Journal of Futures Markets, 32(3), 272–299. https://doi.org/https://doi.org/10.1002/fut.20519
   Web of Science ®Google Scholar
• David, O. O., & Grobler, W. (2020). Information and communication technology penetration level as an impetus for economic growth and development in Africa. Economic Research-Ekonomska Istraživanja, 33(1), 1394–1418. doi: https://doi.org/10.1080/1331677x.2020.1745661
   Web of Science ®Google Scholar
• Delgado, F. J., Fernandez-Rodriguez, E., & Martinez-Arias, A. (2018). Corporation effective tax rates and company size: Evidence from Germany. Economic Research-Ekonomska Istraživanja, 31(1), 2081–2099. doi: https://doi.org/10.1080/1331677x.2018.1543056
   Web of Science ®Google Scholar
• Dewandaru, G., Rizvi, S. A. R., Masih, R., Masih, M., & Alhabshi, S. O. (2014). Stock market co-movements: Islamic versus conventional equity indices with multi-timescales analysis. Economic Systems, 38(4), 553–571. doi: https://doi.org/10.1016/j.ecosys.2014.05.003
   Web of Science ®Google Scholar
• Dybczak, K., & Galuščak, K. (2013). Changes in the Czech wage structure: does immigration matter? Finance a úvěr: Czech Journal of Economics and Finance, 63(2), 108–128.
   Web of Science ®Google Scholar
• Engle, R. F., Ito, T., & Lin, W.-L. (1990). Meteor showers or heat waves? Heteroskedastic intra-daily volatility in the foreign exchange market. Econometrica, 58(3), 525–542. doi: https://doi.org/10.2307/2938189
   Web of Science ®Google Scholar
• Frommel, M. (2010). Volatility regimes in Central and Eastern European countries’ exchange rates. Finance a úver-Czech Journal of Economics and Finance, 60(1), 2–21.
   Web of Science ®Google Scholar
• Fu, T. Y., Holmes, M. J., & Choi, D. F. S. (2011). Volatility transmission and asymmetric linkages between the stock and foreign exchange markets - A sectoral analysis. Studies in Economics and Finance, 28(1), 36–50. doi: https://doi.org/10.1108/10867371111110543
   Google Scholar
• Golosnoy, V., Gribisch, B., & Liesenfeld, R. (2015). Intra-daily volatility spillovers in international stock markets. Journal of International Money and Finance, 53, 95–114. doi: https://doi.org/10.1016/j.jimonfin.2015.01.002
   Web of Science ®Google Scholar
• Gray, S. F. (1996). Modelling the conditional distribution of interest rates as a regime-switching process. Journal of Financial Economics, 42(1), 27–62. doi: https://doi.org/10.1016/0304-405x(96)00875-6
   Web of Science ®Google Scholar
• Hamilton, J. D., & Susmel, R. (1994). Autoregressive conditional heteroskedasticity and changes in regime. Journal of Econometrics, 64(1–2), 307–333. doi: https://doi.org/10.1016/0304-4076(94)90067-1
   Web of Science ®Google Scholar
• 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. doi: https://doi.org/10.1016/s0939-3625(03)00017-7
   Google Scholar
• He, Q., Xu, L., & Men, Y. (2020). Composition effect matters: Decomposing the gender pay gap in Chinese university graduates. Economic Research-Ekonomska Istraživanja, 33(1), 847–864. doi: https://doi.org/10.1080/1331677X.2020.1734850
   Web of Science ®Google Scholar
• Kanas, A. (2000). Volatility spillovers between stock returns and exchange rate changes: International evidence. Journal of Business, Finance and Accounting, 27(3–4), 447–467. doi: https://doi.org/10.1111/1468-5957.00320
   Google Scholar
• Klaassen, F. (2002). Improving GARCH volatility forecasts with regime-switching GARCH. Empirical Economics, 27(2), 363–394. doi: https://doi.org/10.1007/s001810100100
   Web of Science ®Google Scholar
• Koenker, R., & Bassett, G. (1978). Regression quantiles. Econometrica, 46(1), 33–50. doi: https://doi.org/10.2307/1913643
   Web of Science ®Google Scholar
• Koenker, R. (2005). Quantile regression. Econometric society monograph series. Cambridge University Press.
   Google Scholar
• Koutmos, G., & Booth, G. G. (1995). Asymmetric volatility transmission in international stock markets. Journal of International Money and Finance, 14(6), 747–762. doi: https://doi.org/10.1016/0261-5606(95)00031-3
   Web of Science ®Google Scholar
• Lee, C. M., & Lee, H. S. (2016). Improving the predictive power of spreads for economic activity: A wavelet method. Romanian Journal of Economic Forecasting, 19(4), 65–78.
   Web of Science ®Google Scholar
• Leung, H., Schiereck, D., & Schroeder, F. (2017). Volatility spillovers and determinants of contagion: Exchange rate and equity markets during crises. Economic Modelling, 61, 169–180. doi: https://doi.org/10.1016/j.econmod.2016.12.011
   Web of Science ®Google Scholar
• Lin, L., & Lin, W. (2013). Exchange rate reversion under regimes other than free float? International Journal of Finance and Economics, 18(3), 239–306. https://doi.org/https://doi.org/10.1002/ijfe.1465
   Web of Science ®Google Scholar
• Maestri, V. (2013). Imputed rent and distributional effect of housing-related policies in Estonia, Italy and the United Kingdom. Baltic Journal of Economics, 13(2), 37–60. doi: https://doi.org/10.1080/1406099x.2013.10840532
   Web of Science ®Google Scholar
• Madaleno, M., & Pinho, C. (2012). International stock market indices comovements: A new look. International Journal of Finance & Economics, 17(1), 89–102. doi: https://doi.org/10.1002/ijfe.448
   Web of Science ®Google Scholar
• Monfared, S. A., & Enke, D. (2014). Volatility forecasting using a Hybrid GJR-GARCH neural network model. Procedia Computer Science, 36, 246–253. doi: https://doi.org/10.1016/j.procs.2014.09.087
   Google Scholar
• Njegić, J., Živkov, D., & Damnjanović, J. (2017). Business cycles synchronization between EU15 and the selected Eastern European countries – The wavelet coherence approach. Acta Oeconomica, 67(4), 539–556. doi: https://doi.org/10.1556/032.2017.67.4.3
   Web of Science ®Google Scholar
• Nikkinen, J., Pynnönen, S., Ranta, M., & Vähämaa, S. (2011). Cross-dynamics of exchange rate expectations: A wavelet analysis. International Journal of Finance & Economics, 16(3), 205–217. doi: https://doi.org/10.1002/ijfe.423
   Web of Science ®Google Scholar
• Sare, Y. A., Aboagye, A. Q. Q., & Mensah, L. (2019). Financial development, sectoral effects, and international trade in Africa: An application of pooled mean group (PMG) estimation approach. International Journal of Finance & Economics, 24(1), 328–347. doi: https://doi.org/10.1002/ijfe.1665
   Web of Science ®Google Scholar
• Sikhosana, A., & Aye, G. C. (2018). Asymmetric volatility transmission between the real exchange rate and stock returns in South Africa. Economic Analysis and Policy, 60, 1–8. doi: https://doi.org/10.1016/j.eap.2018.08.002
   Web of Science ®Google Scholar
• Torrence, C., & Webster, P. J. (1999). Interdecadal changes in the ENSO-monsoon system. Journal of Climate, 12(8), 2679–2690. doi: https://doi.org/10.1175/1520-0442(1999)012 < 2679:icitem>2.0.co;2
   Web of Science ®Google Scholar
• Tsai, S.-L., & Chang, T. (2018). The comovement between money and economic growth in 15 Asia-pacific countries: wavelet coherency analysis in time-frequency domain. Romanian Journal of Economic Forecasting, 21(2), 63–79.
   Web of Science ®Google Scholar
• Tule, M., Dogo, M., & Uzonwanne, G. (2018). Volatility of stock market returns and the naira exchange rate. Global Finance Journal, 35, 97–105. doi: https://doi.org/10.1016/j.gfj.2017.08.001
   Web of Science ®Google Scholar
• Vilerts, K. (2018). The public-private sector wage gap in Latvia. Baltic Journal of Economics, 18(1), 25–50. doi: https://doi.org/10.1080/1406099x.2018.1457356
   Web of Science ®Google Scholar
• Vo, X. V., & Tran, T. T. A. (2020). Modelling volatility spillovers from the US equity market to ASEAN stock markets. Pacific-Basin Finance Journal, 59, 101246. doi: https://doi.org/10.1016/j.pacfin.2019.101246
   Web of Science ®Google Scholar
• Yang, S.-Y., & Doong, S.-C. (2004). Price and volatility spillovers between stock prices and exchange rates: Empirical evidence from the G-7 countries. International Journal of Business and Economics, 382, 139–153.
   Google Scholar
• Yip, P. S., Brooks, R., Do, H. X., & Nguyen, D. K. (2020). Dynamic volatility spillover effects between oil and agricultural products. International Review of Financial Analysis, 69, 101465. doi: https://doi.org/10.1016/j.irfa.2020.101465
   Web of Science ®Google Scholar
• Živkov, D., Njegić, J., & Pećanac, M. (2014). Bidirectional linkage between inflation and inflation uncertainty – the case of Eastern European countries. Baltic Journal of Economics, 14(1–2), 124–139. doi: https://doi.org/10.1080/1406099x.2014.993831
   Web of Science ®Google Scholar
• Živkov, D., Njegić, J., & Milenković, I. (2015). Bidirectional volatility spillover effect between the exchange rate and stocks in the presence of structural breaks in selected Eastern European economies. Czech Journal of Economics and Finance - Finance a Uver, 65(6), 477–498.
   Web of Science ®Google Scholar
• Živkov, D., Manić, S., & Đurašković, J. (2019). Multiscale volatility transmission and portfolio construction between the Baltic stock markets. Finance a Úvěr – Czech Journal of Economics and Finance, 69(2), 211–236.
   Web of Science ®Google Scholar
• Živkov, D., Kuzman, B., & Subić, J. (2019). How do oil price changes impact the major agricultural commodities in different market conditions and in different time-horizons? Economic Computation and Economic Cybernetics Studies and Research, 53(4), 159–175. https://doi.org/https://doi.org/10.24818/18423264/53.4.19.10
   Web of Science ®Google Scholar
• Živkov, D., Pećanac, M., & Ercegovac, D. (2019). Interdependence between stocks and exchange rate in East Asia – A wavelet-based approach. Singapore Economic Review. https://doi.org/https://doi.org/10.1142/S0217590819500450
   Google Scholar