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Risque de crédit et volatilité des spreads sur le marché de la dette privée en euro

Editor

Listed:
  • Avouyi-Dovi, Sanvi

Author

Listed:
  • Sodjahin, Amos Aristide

Abstract

The credit risk on the bond market is characterized by the possible default of a counterparty, but also by changes in the spread following a perceived deterioration, by the market, of the credit quality of the issuer. This thesis focuses on credit spreads on corporate bond market in euros. Following the introductory chapter that presents some stylized facts that characterize the dynamic of credit spreads in this market, the rest of the thesis is organized in three empirical studies. The first study proposes a model of the conditional variance of spreads in a non-Gaussian setting. Within the GARCH family models, we discuss the choice of the conditional distribution of innovations that is able to account for the asymmetry and excess kurtosis observed. The model associated with skewed generalized error distribution (Skewed-GED) seems to characterize the dynamic of credit spreads and performs well in terms of out-of-sample volatility forecast. From the structural models of risky debt, the second study examines the influence of market conditions on credit spreads. Regardless of the financial situation of the bond issuer, risk premiums seem to depend on interest rates, the state of the stock market, the foreign exchange market and the liquidity of the securities. The third study is devoted to examining the effect of macroeconomic news on credit spreads. Investors seem to attach greater importance to the releases of American’s indicators. The spreads of riskier issuers are more affected, especially in times of crisis.

Suggested Citation

  • Sodjahin, Amos Aristide, 2011. "Risque de crédit et volatilité des spreads sur le marché de la dette privée en euro," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/6316 edited by Avouyi-Dovi, Sanvi.
  • Handle: RePEc:dau:thesis:123456789/6316
    Note: dissertation
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    References listed on IDEAS

    as
    1. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
    2. Landschoot, Astrid Van, 2008. "Determinants of yield spread dynamics: Euro versus US dollar corporate bonds," Journal of Banking & Finance, Elsevier, vol. 32(12), pages 2597-2605, December.
    3. Edwin J. Elton & Martin J. Gruber & Deepak Agrawal & Christopher Mann, 2001. "Explaining the Rate Spread on Corporate Bonds," Journal of Finance, American Finance Association, vol. 56(1), pages 247-277, February.
    4. Gregory R. Duffee, 1998. "The Relation Between Treasury Yields and Corporate Bond Yield Spreads," Journal of Finance, American Finance Association, vol. 53(6), pages 2225-2241, December.
    5. Thomas C. Wilson, 1998. "Portfolio credit risk," Economic Policy Review, Federal Reserve Bank of New York, vol. 4(Oct), pages 71-82.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Credit spread in euro; asymmetric effects; conditional probability distribution; volatility forecast; market factor; macroeconomic news; market expectation; financial crisis; Spread de crédit en euro; effets d’asymétrie; distribution de lois conditionnelles; prévision de volatilité; conditions de marché; annonces macroéconomiques; attentes du marché; crises financières;
    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
    • G01 - Financial Economics - - General - - - Financial Crises
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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