Examining contagion effects between global crude oil prices and the Southeast Asian stock markets during the COVID-19 pandemic
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Author(s)Mien Thi Ngoc NguyenLink to ORCID Index: https://orcid.org/0000-0002-0792-1836
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DOIhttp://dx.doi.org/10.21511/imfi.20(1).2023.08
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Article InfoVolume 20 2023, Issue #1, pp. 77-87
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Creative Commons Attribution 4.0 International License
Many previous studies identify the contagion effect among various types of assets, defined as the increase in correlation of these assets during a financial or economic crisis. During the COVID-19 outbreak, a historic fall in global fuel demand and oil prices has been witnessed. Because crude oil has a strategic position among the export products of the Southeast Asian economies, even a tiny global oil price change leads to a plunge in these stock markets. This study addresses the spillovers of the volatility between the West Texas Intermediate crude oil prices and stock indices across six ASEAN emerging economies. Besides, the study examines whether a contagion connecting the global energy prices and these stock markets exists during the coronavirus pandemic. The empirical results are acquired by applying the Bayesian test for equality of means on the dynamic conditional correlations computed from DCC-GARCH models. The findings present positive volatility transmission from crude oil prices toward these emerging equity markets. During the health crisis, co-movements intensify, indicating the occurrence of contagion effects. The empirical results provide valid implications for policymakers and international investors because a precise volatility forecast is vital for managing portfolio risk.
Acknowledgment
This research is funded by University of Economics Ho Chi Minh City, Vietnam.
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JEL Classification (Paper profile tab)G01, G15, Q49
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References44
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Tables3
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Figures2
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- Figure 1. Plots of returns of ASEAN stock indices and oil prices
- Figure 2. Rolling correlation (30 days)
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- Table 1. Descriptive statistics summary, unit root tests, and correlation coefficients
- Table 2. DCC-GARCH models
- Table 3. Bayesian t-test results for the equality of DCC conditional correlation in the period prior to and within the coronavirus outbreak
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- Adekoya, O. B., & Oliyide, J. A. (2021). How COVID-19 drives connectedness among commodity and financial markets: Evidence from TVP-VAR and causality-in-quantiles techniques. Resources Policy, 70, 101898.
- Akhtaruzzaman, M., Boubaker, S., & Sensoy, A. (2021). Financial contagion during COVID-19 crisis. Finance Research Letters, 38, 101604.
- Arouri, M. E. H., Lahiani, A., & Nguyen, D. K. (2011). Return and volatility transmission between world oil prices and stock markets of the GCC countries. Economic Modelling, 28(4), 1815-1825.
- Ashraf, B. N. (2020). Economic impact of government interventions during the COVID-19 pandemic: International evidence from financial markets. Journal of Behavioral and Experimental Finance, 27, 100371.
- Baek, S., Mohanty, S. K., & Glambosky, M. (2020). COVID-19 and stock market volatility: An industry level analysis. Finance Research Letters, 37, 101748.
- Białkowski, J. D., & Serwa, D. (2005). Financial contagion, spillovers and causality in the Markov switching framework. Quantitative Finance, 5(1), 123-131.
- Boubaker, S., Jouini, J., & Lahiani, A. (2016). Financial contagion between the US and selected developed and emerging countries: The case of the subprime crisis. The Quarterly Review of Economics and Finance, 61, 14-28.
- Büyükşahin, B., & Robe, M. A. (2014). Speculators, commodities and cross-market linkages. Journal of International Money, 42, 38-70.
- Chen, Q., & Lv, X. (2015). The extreme-value dependence between the crude oil price and Chinese stock markets. International Review of Economics & Finance, 39, 121-132.
- Choi, D. F., Fang, V., & Fu, T. Y. (2009). Volatility spillover between New Zealand stock market returns and exchange rate changes before and after the 1997 Asian financial crisis. Asian journal of Finance and Accounting, 1(2), 106-117.
- Cong, R.-G., Wei, Y.-M., Jiao, J.-L., & Fan, Y. (2008). Relationships between oil price shocks and stock market: An empirical analysis from China. Energy Policy, 36(9), 3544-3553.
- Corbet, S., Larkin, C., & Lucey, B. (2020). The contagion effects of the COVID-19 pandemic: Evidence from gold and cryptocurrencies. Finance Research Letters, 35, 101554.
- Diaz, E. M., Molero, J. C., & De Gracia, F. P. (2016). Oil price volatility and stock returns in the G7 economies. Energy Economics, 54, 417-430.
- Davidovic, M. (2021). From pandemic to financial contagion: High-frequency risk metrics and Bayesian volatility analysis. Finance Research Letters, 42, 101913.
- Farid, S., Kayani, G. M., Naeem, M. A., & Shahzad, S. J. H. (2021). Intraday volatility transmission among precious metals, energy and stocks during the COVID-19 pandemic. Resources Policy, 72, 102101.
- Forbes, K. J., & Rigobon, R. (2002). No contagion, only interdependence: measuring stock market comovements. The Journal of Finance, 57(5), 2223-2261.
- Ghalanos, A. (2019). The rmgarch models: Background and properties (Version 1.3-0).
- Ghorbel, A., & Boujelbene, Y. (2013). Contagion effect of the oil shock and US financial crisis on the GCC and BRIC countries. International Journal of Energy Sector Management, 7(4), 430-447.
- Ghorbel, A., & Jeribi, A. (2021). Volatility spillovers and contagion between energy sector and financial assets during COVID-19 crisis period. Eurasian Economic Review, 11(3), 449-467.
- Ghosh, S., & Kanjilal, K. (2016). Co-movement of international crude oil price and Indian stock market: Evidences from nonlinear cointegration tests. Energy Economics, 53, 111-117.
- Guesmi, K., & Fattoum, S. (2014). The relationship between oil price and OECD stock markets: A multivariate approach. Economics Bulletin, 34(1), 510-519.
- Guo, Y., Li, P., & Li, A. (2021). Tail risk contagion between international financial markets during COVID-19 pandemic. International Review of Financial Analysis, 73, 101649.
- Jebabli, I., Kouaissah, N., & Arouri, M. (2022). Volatility spillovers between stock and energy markets during crises: A comparative assessment between the 2008 global financial crisis and the COVID-19 pandemic crisis. Finance Research Letters, 46, 102363.
- John, P. (2021). Global oil price crash leaves ASEAN economies staring down the barrel. ASEAN Today.
- Kilian, L., & Park, C. (2009). The impact of oil price shocks on the US stock market. International Economic Review, 50(4), 1267-1287.
- Kocaarslan, B., Soytas, U., Sari, R., & Ugurlu, E. (2019). The changing role of financial stress, oil price, and gold price in financial contagion among US and BRIC markets. International Review of Finance, 19(3), 541-574.
- Li, W., Chien, F., Kamran, H. W., Aldeehani, T. M., Sadiq, M., Nguyen, V. C., & Taghizadeh-Hesary, F. (2021). The nexus between COVID-19 fear and stock market volatility. Economic Research-Ekonomska Istraživanja, 1-22.
- Lin, L., Kuang, Y., Jiang, Y., & Su, X. (2019). Assessing risk contagion among the Brent crude oil market, London gold market and stock markets: Evidence based on a new wavelet decomposition approach. The North American Journal of Economics and Finance, 50, 101035.
- Liu, B. Y., Fan, Y., Ji, Q., & Hussain, N. (2022). High-dimensional CoVaR network connectedness for measuring conditional financial contagion and risk spillovers from oil markets to the G20 stock system. Energy Economics, 105, 105749.
- Kruschke, J. K. (2013). Bayesian estimation supersedes the t test. Journal of Experimental Psychology: General, 142(2), 573-603.
- Park, J., & Ratti, R. A. (2008). Oil price shocks and stock markets in the US and 13 European countries. Energy Economics, 30(5), 2587-2608.
- Roy, R. P., & Roy, S. S. (2017). Financial contagion and volatility spillover: An exploration into Indian commodity derivative market. Economic Modelling, 67, 368-380.
- Rehman, M. Z., Tiwari, A. K., & Samontaray, D. P. (2022). Directional predictability in foreign exchange rates of emerging markets: new evidence using a cross-quantilogram approach. Borsa Istanbul Review, 22(1), 145-155.
- Sharma, A., Giri, S., Vardhan, H., Surange, S., Shetty, R., & Shetty, V. (2018). Relationship between crude oil prices and stock market: Evidence from India. International Journal of Energy Economics Policy, 8(4), 331-337.
- Uddin, G. S., Yahya, M., Goswami, G. G., Lucey, B., & Ahmed, A. (2022). Stock market contagion during the COVID-19 pandemic in emerging economies. International Review of Economics & Finance, 79, 302-309.
- Uwubanmwen, A., & Omorokunwa, O. (2015). Oil price volatility and stock price volatility: Evidence from Nigeria. Academic Journal of Interdisciplinary Studies, 4(1), 253-253.
- Wang, X., Liu, H., Huang, S., & Lucey, B. (2019). Identifying the multiscale financial contagion in precious metal markets. International Review of Financial Analysis, 63, 209-219.
- Wen, X., Wei, Y., & Huang, D. (2012). Measuring contagion between energy market and stock market during financial crisis: A copula approach. Energy Economics, 34(5), 1435-1446.
- Yousaf, I., & Ali, S. (2020). The COVID-19 outbreak and high frequency information transmission between major cryptocurrencies: Evidence from the VAR-DCC-GARCH approach. Borsa Istanbul Review, 20, S1-S10.
- Yiu, M. S., Alex Ho, W. Y., & Choi, D. F. (2010). Dynamic correlation analysis of financial contagion in Asian markets in global financial turmoil. Applied Financial Economics, 20(4), 345-354.
- Yun, X., & Yoon, S. M. (2019). Impact of oil price change on airline’s stock price and volatility: Evidence from China and South Korea. Energy Economics, 78, 668-679.
- Zaremba, A., Kizys, R., Aharon, D. Y., & Demir, E. (2020). Infected markets: Novel coronavirus, government interventions, and stock return volatility around the globe. Finance Research Letters, 35, 101597.
- Zhang, N., Wang, A., Haq, N. U., & Nosheen, S. (2021). The impact of COVID-19 shocks on the volatility of stock markets in technologically advanced countries. Economic Research, 1-26.
- Zhu, H.-M., Li, R., & Li, S. (2014). Modelling dynamic dependence between crude oil prices and Asia-Pacific stock market returns. International Review of Economics & Finance, 29, 208-223.
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Muhtar Lutfi ,
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