Spillovers across global stock markets before and after the declaration of Russia’s invasion of Ukraine

  • 332 Views
  • 52 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

Since the financial meltdown, studies on systemic risk and financial contagion have gained currency. Events like the COVID pandemic and the Russian invasion of Ukraine have fueled such an importance. This study examines the impact of the invasion on volatility transmissions across major stock markets worldwide. The stock indices considered in this study are ASX 200, ESTOXX 40, FTSE 100, HNGSNG, NIFTY 50, NIKKIE, and S&P 500. The work uses Vector Auto Regression (VAR) to study the transmission of returns. Later, the work performs Dynamic Conditional Covariance-Generalized Auto Regression Conditional Heteroskedasticity (DCC-GARCH) on the residuals where the transmission of returns was significant. The DCC-GARCH (E-GARCH) shows that all the asymmetric transmissions are negative. The study finds that co-movements of stock returns for the following pairs: ESTOXX 50-S&P 500, NIFTY 50-FTSE100, NIFTY 50-NIKKIE, NIKKIE-ESTOXX 50, S&P 500-NIFTY 50, and SP500-HNGSNG significantly intensified after the declaration of invasion. Such intensification of co-movements does establish the contagion effect triggered by invasion. The study shows that ESTOXX 50, which has the closest geographical proximity to the war zone, happens to be the highest generator of spillovers.

view full abstract hide full abstract
    • Figure 1. VAR residuals of stock market returns
    • Figure 2. Dynamic conditional correlations for significant transmission
    • Table 1. Descriptive statistics
    • Table 2. Vector Auto Regression results on stock returns
    • Table 3. Autocorrelation and GARCH test results of spillovers
    • Table 4. Spillover results of DCC-GARCH (S-GARCH)
    • Table 5. Spillover results of DCC-GARCH (E-GARCH)
    • Table 6. Spillover results of DCC-GARCH (S-GARCH)
    • Conceptualization
      Satya Krishna Sharma Raavinuthala, Girish Jain
    • Data curation
      Satya Krishna Sharma Raavinuthala, Gokulananda Patel
    • Formal Analysis
      Satya Krishna Sharma Raavinuthala, Girish Jain
    • Methodology
      Satya Krishna Sharma Raavinuthala, Gokulananda Patel
    • Writing – original draft
      Satya Krishna Sharma Raavinuthala
    • Validation
      Girish Jain, Gokulananda Patel
    • Writing – review & editing
      Girish Jain, Gokulananda Patel
    • Supervision
      Gokulananda Patel