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What Economic Factors Underlie Connectedness in Corporate Credit Default Swaps: News vs. Macroeconomic Factors?

Author

Listed:
  • Andrew Castro

    (Michigan State University)

  • Neville Francis

    (UNC Chapel Hill)

Abstract

We examine the economic factors that underlie return and price volatility networks for corporate credit default swaps. After examining company-level networks we aggregate the data to study sector-level net connectedness. By introducing company news measures and macroeconomic covariates, we explore their effects on net connectedness. We find that no one factor explains connectedness across all sectors. Additionally, while returns networks are mainly influenced by news releases and macroeconomic factors are the main impetus behind price volatility networks, neither explain the general changes to net connectedness over time.

Suggested Citation

  • Andrew Castro & Neville Francis, 2018. "What Economic Factors Underlie Connectedness in Corporate Credit Default Swaps: News vs. Macroeconomic Factors?," 2018 Meeting Papers 586, Society for Economic Dynamics.
    • Handle: RePEc:red:sed018:586
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    References listed on IDEAS

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    1. Duffie, Darrell & Saita, Leandro & Wang, Ke, 2007. "Multi-period corporate default prediction with stochastic covariates," Journal of Financial Economics, Elsevier, vol. 83(3), pages 635-665, March.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. Stefan Klößner & Sven Wagner, 2014. "Exploring All Var Orderings For Calculating Spillovers? Yes, We Can!—A Note On Diebold And Yilmaz (2009)," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 172-179, January.
    4. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.
    5. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2016. "Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers," Journal of Financial Markets, Elsevier, vol. 27(C), pages 55-78.
    6. Jun Pan & Kenneth J. Singleton, 2008. "Default and Recovery Implicit in the Term Structure of Sovereign CDS Spreads," Journal of Finance, American Finance Association, vol. 63(5), pages 2345-2384, October.
    7. Klößner, Stefan & Sekkel, Rodrigo, 2014. "International spillovers of policy uncertainty," Economics Letters, Elsevier, vol. 124(3), pages 508-512.
    8. Francis A. Longstaff & Arvind Rajan, 2008. "An Empirical Analysis of the Pricing of Collateralized Debt Obligations," Journal of Finance, American Finance Association, vol. 63(2), pages 529-563, April.
    9. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    10. Yang, Dennis & Zhang, Qiang, 2000. "Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices," The Journal of Business, University of Chicago Press, vol. 73(3), pages 477-491, July.
    11. Francis A. Longstaff & Jun Pan & Lasse H. Pedersen & Kenneth J. Singleton, 2011. "How Sovereign Is Sovereign Credit Risk?," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(2), pages 75-103, April.
    12. Bostanci, Gorkem & Yilmaz, Kamil, 2020. "How connected is the global sovereign credit risk network?," Journal of Banking & Finance, Elsevier, vol. 113(C).
    13. José Da Fonseca & Katrin Gottschalk, 2020. "The Co‐Movement of Credit Default Swap Spreads, Equity Returns and Volatility: Evidence from Asia‐Pacific Markets," International Review of Finance, International Review of Finance Ltd., vol. 20(3), pages 551-579, September.
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