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Bidirectional volatility transmission between stocks and bond in East Asia – The quantile estimates based on wavelets

  • Dejan Živkov EMAIL logo , Jelena Kovačević , Biljana Stankov and Zoran Stefanović
Published/Copyright: February 7, 2022

Abstract

This paper investigates the volatility spillover effect between the national stock and bond markets in the five East Asian emerging countries. We use wavelet signal decomposing technique, GARCH models with different distribution functions and quantile regression. We find that the spillover effect is much higher in more turbulent times, than in calm periods, whereby this effect is stronger from stocks to 10Y bonds, than vice-versa, and it applies for all the countries. Using wavelet signals, we determine that, in most cases, the volatility transmission is higher in short-term horizon, than in midterm and long-term. The effect is stronger in countries with the less developed financial markets (Thailand, Indonesia and Malaysia) than in countries with more developed financial markets (China and Korea), and this is particularly evident in direction from stock to bond markets. Wavelet coherence indicates low volatility correlation in short time-horizons and relatively high correlation in midterm and long-term, which applies for all selected countries. Wavelet cross-correlation indicates that volatility spillover shocks predominantly transmit from bond markets to stock market in more developed China and Korea, whereas volatility shocks from stock market spill over towards bond market in less developed Thailand and Indonesia in very short-time horizon (2–4 days).

JEL Classification: C21; C63; D53

Corresponding author: Dejan Živkov, Novi Sad Business School, University of Novi Sad, Vladimira Perića Valtera 4, 21000, Novi Sad, Serbia, E-mail:

  1. Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

References

Abbas, Q., S. Khan, and S. Z. Ali Shah. 2013. “Volatility Transmission in Regional Asian Stock Markets.” Emerging Markets Review 16: 66–77. https://doi.org/10.1016/j.ememar.2013.04.004.Search in Google Scholar

Aboura, S., and J. Chevallier. 2014. “Cross-Market Spillovers with ‘Volatility Surprise’.” Review of Financial Economics 23: 194–207. https://doi.org/10.1016/j.rfe.2014.08.002.Search in Google Scholar

Akca, K., and S. S. Ozturk. 2016. “The Effect of 2008 Crisis on the Volatility Spillovers Among Six Major Markets.” International Review of Finance 16 (1): 169–78. https://doi.org/10.1111/irfi.12071.Search in Google Scholar

Bhattacharyay, B. N. 2013. “Determinants of Bond Market Development in Asia.” Journal of Asian Economics 24: 124–37. https://doi.org/10.1016/j.asieco.2012.11.002.Search in Google Scholar

Caglayan, M., O. K. Kocaaslan, and K. Mouratidis. 2016. “Regime Dependent Effects of Inflation Uncertainty on Real Growth: A Markov Switching Approach.” Scottish Journal of Political Economy 63 (2): 135–55.10.1111/sjpe.12087Search in Google Scholar

Cai, Y. X., Y. L. Gong, and G. Y. Sheng. 2021. “The Gold Price and the Economic Policy Uncertainty Dynamics Relationship: The Continuous Wavelet Analysis.” Economic Computation & Economic Cybernetics Studies & Research 55 (1): 105–16.10.24818/18423264/55.1.21.07Search in Google Scholar

Chen, S.-W., C.-H. Shen, and Z. Xie. 2008. “Evidence of a Nonlinear Relationship between Inflation and Inflation Uncertainty: The Case of the Four Little Dragons.” Journal of Policy Modeling 30 (2): 363–76. https://doi.org/10.1016/j.jpolmod.2007.01.007.Search in Google Scholar

Christiansen, C. 2010. “Decomposing European Bond and Equity Volatility.” International Journal of Finance & Economics 15 (2): 15–122.10.1002/ijfe.385Search in Google Scholar

Chuliá, H., and H. Torro. 2008. “The Economic Value of Volatility Transmission between the Stock and Bond Markets.” Journal of Futures Markets 28 (11): 1066–94.10.1002/fut.20342Search in Google Scholar

Cupák, A., J. Pokrivčák, and M. Rizov. 2016. “Diversity of Food Consumption in Slovakia.” Politicka Ekonomie 64 (5): 608–26.10.18267/j.polek.1082Search in Google Scholar

Dajčman, S. 2013. “Interdependence between Some Major European Stock Markets – A Wavelet Led/Lag Analysis.” Prague Economic Papers 22 (1): 28–49.10.18267/j.pep.439Search in Google Scholar

Dewandaru, G., S. A. R. Rizvi, R. Masih, M. Masih, and S. O. Alhabshi. 2014. “Stock Market Co-Movements: Islamic versus Conventional Equity Indices with Multi-Timescales Analysis.” Economic Systems 38 (4): 553–71. https://doi.org/10.1016/j.ecosys.2014.05.003.Search in Google Scholar

Diebold, F. X., and L. Yilmaz. 2012. “Better to Give Than to Receive: Predictive Directional Measurement of Volatility Spillovers.” International Journal of Forecasting 28 (1): 57–66. https://doi.org/10.1016/j.ijforecast.2011.02.006.Search in Google Scholar

Engle, R. F., T. Ito, and W. Lin. 1990. “Meteor Showers or Heat Waves? Heteroskedastic Intra-Daily Volatility in the Foreign Exchange Market.” Econometrica 58 (3): 525–42. https://doi.org/10.2307/2938189.Search in Google Scholar

Fleming, J., C. Kirby, and B. Ostdiek. 1998. “Information and Volatility Linkages in the Stock, Bond and Money Markets.” Journal of Financial Economics 49 (1): 111–37. https://doi.org/10.1016/s0304-405x(98)00019-1.Search in 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.Search in 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. https://doi.org/10.1016/0304-405x(96)00875-6.Search in Google Scholar

Jensen, M. J. 2016. “Robust Estimation of Nonstationary, Fractionally Integrated, Autoregressive, Stochastic Volatility.” Studies in Nonlinear Dynamics and Econometrics 20 (4): 455–75. https://doi.org/10.1515/snde-2014-0116.Search in Google Scholar

Kamal, M. A., A. Ullah, J. Zheng, B. Zheng, and H. Xia. 2019. “Natural Resource or Market Seeking Motive of China’s FDI in Asia? New Evidence at Income and Sub-Regional Level.” Economic Research 32 (1): 3869–94. https://doi.org/10.1080/1331677x.2019.1674679.Search in Google Scholar

Koenker, R. 2005. Quantile Regression In Econometric Society Monograph Series. New York: Cambridge University Press.10.1017/CBO9780511754098Search in Google Scholar

Koenker, R., and G. Bassett. 1978. “Regression Quantiles.” Econometrica 46 (1): 33–50. https://doi.org/10.2307/1913643.Search in Google Scholar

Lee, H. S., and S. I. Kim. 2013. “Common Features in East Asian Stock Markets: Long-Term and Short-Term Comovements between China and Korea.” Singapore Economic Review 58 (3): 1350018. https://doi.org/10.1142/s0217590813500185.Search in Google Scholar

Leung, H., D. Schiereck, and F. Schroeder. 2017. “Volatility Spillovers and Determinants of Contagion: Exchange Rate and Equity Markets during Crises.” Economic Modelling 61: 169–80. https://doi.org/10.1016/j.econmod.2016.12.011.Search in Google Scholar

Li, Y., and D. E. Giles. 2015. “Modelling Volatility Spillover Effects between Developed Stock Markets and Asian Emerging Stock Markets.” International Journal of Finance & Economics 20 (2): 155–77. https://doi.org/10.1002/ijfe.1506.Search in Google Scholar

Liow, K. H. 2015. “Conditional Volatility Spillover Effects across Emerging Financial Markets.” Asia-Pacific Journal of Financial Studies 44 (2): 215–45. https://doi.org/10.1111/ajfs.12087.Search in Google Scholar

Lyu, Y., P. Wang, Y. Wei, and R. Ke. 2017. “Forecasting the VaR of Crude Oil Market: Do Alternative Distributions Help?” Energy Economics 66: 523–34. https://doi.org/10.1016/j.eneco.2017.06.015.Search in Google Scholar

Ma, X., Z. Yang, X. Xu, and C. Wang. 2018. “The Impact of Chinese Financial Markets on Commodity Currency Exchange Rates.” Global Finance Journal 37: 186–98. https://doi.org/10.1016/j.gfj.2018.05.003.Search in Google Scholar

Mi, L., and A. Hodgson. 2018. “Real Estate’s Information and Volatility Links with Stock, Bond and Money Markets.” Accounting and Finance 58: 465–91. https://doi.org/10.1111/acfi.12375.Search in Google Scholar

Miyajima, K., M. S. Mohanty, and T. Chan. 2015. “Emerging Market Local Currency Bonds: Diversification and Stability.” Emerging Markets Review 22: 126–39. https://doi.org/10.1016/j.ememar.2014.09.006.Search in Google Scholar

Mun, K. C. 2007. “Volatility and Correlation in International Stock Markets and the Role of Exchange Rate Fluctuations.” Journal of International Financial Markets, Institutions and Money 17: 25–41. https://doi.org/10.1016/j.intfin.2005.08.006.Search in Google Scholar

Ordu-Akkaya, B. M., and U. Soytas. 2020. “Does Foreign Portfolio Investment Strengthen Stock-Commodity Markets Connection?” Resources Policy 65: 101536. https://doi.org/10.1016/j.resourpol.2019.101536.Search in Google Scholar

Ozcelebi, O. 2021. “Assessing the Impacts of Global Economic Policy Uncertainty and the Long-Term Bond Yields on Oil Prices.” Applied Economic Analysis 29 (87): 226–44. https://doi.org/10.1108/aea-05-2020-0046.Search in Google Scholar

Ross, S. A. 1989. “Information and Volatility. The No Arbitrage and Martingale Approach to Timing and Resolution Irrelevancy.” The Journal of Finance 44: 1–17. https://doi.org/10.1111/j.1540-6261.1989.tb02401.x.Search in Google Scholar

Sclip, A., A. Dreassi, S. Miani, and A. Paltrinieri. 2016. “Dynamic Correlations and Volatility Linkages between Stocks and Sukuk: Evidence from International Markets.” Review of Financial Economics 31: 34–44. https://doi.org/10.1016/j.rfe.2016.06.005.Search in Google Scholar

Si, D. K., X. L. Li, and X. Ge. 2020. “On the Link between the Exchange Rates and Interest Rate Differentials in China: Evidence from an Asymmetric Wavelet Analysis.” Empirical Economics 59: 2925–46. https://doi.org/10.1007/s00181-019-01803-4.Search in Google Scholar

Skevas, T., and J. Grashuis. 2019. “Technical Efficiency and Spatial Spillovers: Evidence from Grain Marketing Cooperatives in the US Midwest.” Agribusiness: International Journal 36 (1): 111–26. https://doi.org/10.1002/agr.21617.Search in Google Scholar

Tsai, S.-L., and T. Chang. 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.Search in Google Scholar

Wang, Y., Z. Pan, and C. Wu. 2018. “Volatility Spillover from the US to International Stock Markets: A Heterogeneous Volatility Spillover GARCH Model.” Journal of Forecasting 37 (3): 385–400. https://doi.org/10.1002/for.2509.Search in Google Scholar

Wong, H. T. 2019. “Volatility Spillovers between Real Exchange Rate Returns and Real Stock Price Returns in Malaysia.” International Journal of Finance & Economics 24 (1): 131–49. https://doi.org/10.1002/ijfe.1653.Search in Google Scholar

Xiao, J., C. Hu, G. Ouyang, and F. Wen. 2019. “Impacts of Oil Implied Volatility Shocks on Stock Implied Volatility in China: Empirical Evidence from a Quantile Regression Approach.” Energy Economics 80: 297–309. https://doi.org/10.1016/j.eneco.2019.01.016.Search in Google Scholar

Zhang, H., and A. Urquhart. 2019. “Pairs Trading across Mainland China and Hong Kong Stock Markets.” International Journal of Finance & Economics 24 (2): 698–726. https://doi.org/10.1002/ijfe.1687.Search in Google Scholar

Zhu, D. M., and J. W. Galbraith. 2010. “A Generalized Asymmetric Student-T Distribution with Application to Financial Econometrics.” Journal of Econometrics 157 (2): 297–305. https://doi.org/10.1016/j.jeconom.2010.01.013.Search in Google Scholar

Živkov, D., J. Njegić, and M. Stanković. 2019a. “What Wavelet-Based Quantiles Can Suggest about the Stocks–Bond Interaction in the Emerging East Asian Economies?” Finance a úvěr – Czech Journal of Economics and Finance 69 (1): 95–119.Search in Google Scholar

Živkov, D., J. Njegić, and M. Pećanac. 2019b. “Multiscale Interdependence between the Major Agricultural Commodities.” Agricultural Economics 65 (2): 82–92.10.17221/147/2018-AGRICECONSearch in Google Scholar

Received: 2020-09-30
Revised: 2022-01-08
Accepted: 2022-01-24
Published Online: 2022-02-07

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