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Modeling the Dynamics of Credit Spreads with Stochastic Volatility

Listed author(s):
  • Kris Jacobs
  • Xiaofei Li
Registered author(s):

    The paper investigates a two-factor affine model for the credit spreads on corporate bonds. The first factor can be interpreted as the level of the spread, and the second factor is the volatility of the spread. The riskless interest rate is modeled using a standard two-factor affine model, thus leading to a four-factor model for corporate yields. This approach allows us to model the volatility of corporate credit spreads as stochastic, and also allows us to capture higher moments of credit spreads. We use an extended Kalman filter approach to estimate our model on corporate bond prices for 108 firms. The model is found to be successful at fitting actual corporate bond credit spreads, resulting in a significantly lower root mean square error than a standard alternative model in both in-sample and out-of-sample analyses. In addition, key properties of actual credit spreads are better captured by the model. Dans cet article, nous modélisons l'écart de crédit sur obligations d'entreprise avec un modèle affin à deux facteurs. Le premier facteur s'interprète comme le niveau de l'écart et le deuxième comme sa volatilité. Le taux d'intérêt sans risque est modélisé selon un modèle affin à deux facteurs standard, ce qui conduit à un modèle à quatre facteurs pour les rendements d'obligations d'entreprise. Cette approche nous permet de modéliser la volatilité des écarts de crédit de manière stochastique et également de capter des moments des écarts de crédit d'ordres plus élevés. Nous utilisons une approche de filtre de Kalman étendu pour estimer notre modèle à partir des prix des obligations de 108 entreprises. Le modèle s'avère performant dans sa reproduction des écarts de crédit empiriques des obligations d'entreprise et mène à une racine des erreurs moyennes quadratiques significativement plus petite que celle d'un modèle alternatif standard, et ce aussi bien dans l'échantillon que lors d'analyses hors échantillon. De plus, le modèle capte également mieux certaines caractéristiques empiriques importantes des écarts de crédit sur obligations d'entreprise.

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    Paper provided by CIRANO in its series CIRANO Working Papers with number 2003s-51.

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    Length: 55 pages
    Date of creation: 01 Aug 2003
    Handle: RePEc:cir:cirwor:2003s-51
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