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Assessment of the Russian stock market volatility impact on credit spreads of Russian corporate bonds

Author

Listed:
  • Patlasov, Dmitry

    (Perm State University, Perm, Russian Federation)

Abstract

This study evaluates the impact of stock market volatility in the Russian Federation on the size and dynamics of credit spreads for Russian corporate bonds. Credit spreads on corporate bonds represent a measure of the risk premium in the public lending market, while stock market indicates stock market instability. Analyzing the relationship between the bond market risk premium and the instability of the stock market is a pertinent task today because these processes may exhibit both direct and inverse correlations. Additionally, formulating hypotheses about whether stock market volatility positively or negatively affects credit spreads of corporate bonds, and vice versa, poses challenges. The study utilizes data on the Moscow Exchange index (MOEX), Russia’s volatility index (RVI), yields of Russian corporate bonds, and values of Russia’s zero-coupon yield curve (KBD). The research aims to identify patterns in the dynamics of the risk premium in the bond market in response to shocks in MOEX volatility. It also seeks to characterize the actions of investors and holders of Russian corporate bonds during periods of heightened volatility in the Russian stock market.

Suggested Citation

  • Patlasov, Dmitry, 2024. "Assessment of the Russian stock market volatility impact on credit spreads of Russian corporate bonds," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 76, pages 29-50.
    • Handle: RePEc:ris:apltrx:0508
    as

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    References listed on IDEAS

    as
    1. Daniel Jubinski & Amy F. Lipton, 2012. "Equity volatility, bond yields, and yield spreads," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(5), pages 480-503, May.
    2. Doron Avramov & Gergana Jostova & Alexander Philipov, 2007. "Understanding Changes in Corporate Credit Spreads," Financial Analysts Journal, Taylor & Francis Journals, vol. 63(2), pages 90-105, March.
    3. Ann Marie Hibbert & Ivelina Pavlova & Joel Barber & Krishnan Dandapani, 2011. "Credit Spread Changes and Equity Volatility: Evidence from Daily Data," The Financial Review, Eastern Finance Association, vol. 46(3), pages 357-383, August.
    4. Bansal, Naresh & Connolly, Robert A. & Stivers, Chris, 2014. "The Stock-Bond Return Relation, the Term Structure’s Slope, and Asset-Class Risk Dynamics," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(3), pages 699-724, June.
    5. Lee, Hwang Hee & Hyun, Jung-Soon, 2019. "The asymmetric effect of equity volatility on credit default swap spreads," Journal of Banking & Finance, Elsevier, vol. 98(C), pages 125-136.
    6. Li, Xiao-Lin & Li, Xin & Si, Deng-Kui, 2020. "Asymmetric determinants of corporate bond credit spreads in China: Evidence from a nonlinear ARDL model," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    7. Bewley, Ronald & Rees, David & Berg, Paul, 2004. "The impact of stock market volatility on corporate bond credit spreads," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 64(3), pages 363-372.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    credit spreads; volatility; corporate bonds; coupon-free yield curve; imputed volatility; EGARCH; VAR;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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