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Euro Corporate Bond Risk Factors

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  • Carolina Castagnetti
  • Eduardo Rossi

Abstract

This paper investigates the determinants of credit spread changes in Euro-denominated bonds. Because credit spread changes can be easily viewed as an excess return on corporate bonds over treasury bonds, we adopt a factor model framework, inspired by the credit risk structural approach. We try to assess the relative importance of market and idiosyncratic factors in explaining the movements in credit spreads. We adopt a heterogeneous panel with a multifactor error model and propose a two-step estimation procedure which yields consistent estimates of unobserved factors. The analysis is carried out with a panel of monthly redemption yields on a set of corporate bonds for a time span of three years. Our results suggest that the Euro corporate market is driven by observable and unobservable factors. Where the latter are identified through a consistent estimation of individual and common observable effects. We observe that the factors predicted by the structural model are not as relevant as in the case of the US market. The empirical results also suggest that an unobserved common factor has a significant role in explaining the systematic changes in credit spreads. However, contrary to the American evidence, it cannot be identified as a market factor.
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Suggested Citation

  • Carolina Castagnetti & Eduardo Rossi, 2013. "Euro Corporate Bond Risk Factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(3), pages 372-391, April.
  • Handle: RePEc:wly:japmet:v:28:y:2013:i:3:p:372-391
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    Citations

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    Cited by:

    1. Gündüz, Yalin & Ottonello, Giorgio & Pelizzon, Loriana & Schneider, Michael & Subrahmanyam, Marti G., 2018. "Lighting up the dark: Liquidity in the German corporate bond market," SAFE Working Paper Series 230, Leibniz Institute for Financial Research SAFE.
    2. Castagnetti, Carolina & Rossi, Eduardo & Trapani, Lorenzo, 2019. "A two-stage estimator for heterogeneous panel models with common factors," Econometrics and Statistics, Elsevier, vol. 11(C), pages 63-82.
    3. Tu, Anthony H. & Chen, Cathy Yi-Hsuan, 2018. "A factor-based approach of bond portfolio value-at-risk: The informational roles of macroeconomic and financial stress factors," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 243-268.
    4. Castagnetti, Carolina & Rossi, Eduardo & Trapani, Lorenzo, 2015. "Inference on factor structures in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 184(1), pages 145-157.
    5. Christian Klein & Christoph Stellner, 2014. "The systematic risk of corporate bonds: default risk, term risk, and index choice," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 28(1), pages 29-61, February.
    6. Castagnetti, Carolina, 2018. "A novel approach for testing the parity relationship between CDS and credit spread," Economics Letters, Elsevier, vol. 172(C), pages 115-117.
    7. Jaskowski, Marcin & McAleer, Michael, 2021. "Spurious cross-sectional dependence in credit spread changes," Econometrics and Statistics, Elsevier, vol. 18(C), pages 12-27.
    8. Hou, Lei & Li, Kunpeng & Li, Qi & Ouyang, Min, 2021. "Revisiting the location of FDI in China: A panel data approach with heterogeneous shocks," Journal of Econometrics, Elsevier, vol. 221(2), pages 483-509.
    9. Goldstein, Michael A. & Namin, Elmira Shekari, 2023. "Corporate bond liquidity and yield spreads: A review," Research in International Business and Finance, Elsevier, vol. 65(C).
    10. Mehdi Mili, 2018. "Systemic risk spillovers in sovereign credit default swaps in Europe: a spatial approach," Journal of Asset Management, Palgrave Macmillan, vol. 19(2), pages 133-143, March.
    11. Castagnetti, Carolina & Rossi, Eduardo, 2008. "Estimation methods in panel data models with observed and unobserved components: a Monte Carlo study," MPRA Paper 26196, University Library of Munich, Germany.
    12. Anthony H. Tu & Cathy Yi-Hsuan Chen, 2016. "What Derives the Bond Portfolio Value-at-Risk: Information Roles of Macroeconomic and Financial Stress Factors," SFB 649 Discussion Papers SFB649DP2016-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Ephraim Clark & Selima Baccar, 2018. "Modelling credit spreads with time volatility, skewness, and kurtosis," Annals of Operations Research, Springer, vol. 262(2), pages 431-461, March.
    14. Bada, Oualid & Kneip, Alois, 2014. "Parameter cascading for panel models with unknown number of unobserved factors: An application to the credit spread puzzle," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 95-115.

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