Does COVID-19 drive the US corporate-government bonds yield correlations? Local and global reporting

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This paper investigates whether the COVID-19 cases and death rates affect the dynamic correlation of corporate-government bond yields. Therefore, this study uses the daily corporate bond data with different ratings of bonds along with the COVID-19 data at both the US and global levels. Using the quantile regression approach, it produces the following results. First, the impact of daily cases differs from that of death rates both locally and globally. Second, the impact of local cases and death cases on the government-AAA yields correlation at a given quantile tends to reverse when the BBB bonds are used in the analysis. Third, global death rates significantly affect the correlation series the most at the higher quantiles. Lastly, AAA-rated bonds show higher sensitivity to COVID-19 cases and death rates than BBB-rated bonds. This finding indicates that relatively high-quality bonds are more susceptible to the pandemic period and thus calls for careful evaluation of assets included in investors’ portfolios. This study assumes that local COVID-19 data provide a better implication for constructing bond portfolios than global data. That is, their economic impact depends on the rating of the bond and tends to vary more across correlation quantiles.

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    • Figure 1. Bond yields, correlations series, and COVID-19 variables
    • Figure 2. QR estimates
    • Figure A1. COVID-19 and bond yields
    • Table 1. Descriptive statistics for the bond yield and the COVID-19 data
    • Table 2. Summary of QR estimates
    • Table 3. Symmetric test for the coefficients
    • Table A1. Estimating the DCC-GARCH model
    • Conceptualization
      Ahmad Alkhataybeh, Mobeen Ur Rehman, Abedalrazaq Alrababa’a, Mohammad Alomari
    • Data curation
      Ahmad Alkhataybeh
    • Formal Analysis
      Ahmad Alkhataybeh, Mobeen Ur Rehman, Ghaith El-Nader, Abedalrazaq Alrababa’a, Mohammad Alomari
    • Writing – original draft
      Ahmad Alkhataybeh, Mobeen Ur Rehman, Ghaith El-Nader, Abedalrazaq Alrababa’a, Mohammad Alomari
    • Writing – review & editing
      Ahmad Alkhataybeh, Mobeen Ur Rehman, Ghaith El-Nader, Abedalrazaq Alrababa’a, Mohammad Alomari
    • Methodology
      Mobeen Ur Rehman, Ghaith El-Nader, Abedalrazaq Alrababa’a, Mohammad Alomari
    • Investigation
      Ghaith El-Nader, Mohammad Alomari