Examining contagion effects between global crude oil prices and the Southeast Asian stock markets during the COVID-19 pandemic

  • Received November 18, 2022;
    Accepted January 17, 2023;
    Published January 24, 2023
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.20(1).2023.08
  • Article Info
    Volume 20 2023, Issue #1, pp. 77-87
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This work is licensed under a 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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    • Figure 1. Plots of returns of ASEAN stock indices and oil prices
    • Figure 2. Rolling correlation (30 days)
    • 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
    • Conceptualization
      Mien Thi Ngoc Nguyen
    • Data curation
      Mien Thi Ngoc Nguyen
    • Formal Analysis
      Mien Thi Ngoc Nguyen
    • Investigation
      Mien Thi Ngoc Nguyen
    • Methodology
      Mien Thi Ngoc Nguyen
    • Project administration
      Mien Thi Ngoc Nguyen
    • Supervision
      Mien Thi Ngoc Nguyen
    • Validation
      Mien Thi Ngoc Nguyen
    • Visualization
      Mien Thi Ngoc Nguyen
    • Writing – original draft
      Mien Thi Ngoc Nguyen
    • Writing – review & editing
      Mien Thi Ngoc Nguyen