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Endogenizing exogenous default barrier models: The MM algorithm

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  • Forte, Santiago
  • Lovreta, Lidija

Abstract

In this paper, we propose a Maximization–Maximization (MM) algorithm for the assessment of hidden parameters in structural credit risk models. Step M1 updates the value, volatility, and expected return on the firm’s assets by maximizing the log-likelihood function for the time series of equity prices; Step M2 updates the default barrier by maximizing the equity holders’ participation in the firm’s asset value. The main contribution of the method lies in the M2 step, which allows for ‘endogenizing’ the default barrier in light of actual data on equity prices. Using a large international sample of companies, we demonstrate that theoretical credit spreads based on the MM algorithm offer the lowest CDS pricing errors when compared to other, traditional default barrier specifications: smooth-pasting condition value, maximum likelihood estimate, KMV’s default point, and nominal debt.

Suggested Citation

  • Forte, Santiago & Lovreta, Lidija, 2012. "Endogenizing exogenous default barrier models: The MM algorithm," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1639-1652.
  • Handle: RePEc:eee:jbfina:v:36:y:2012:i:6:p:1639-1652
    DOI: 10.1016/j.jbankfin.2012.01.010
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    References listed on IDEAS

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    Cited by:

    1. Han-Hsing Lee & Kuanyu Shih & Kehluh Wang, 2016. "Measuring sovereign credit risk using a structural model approach," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1097-1128, November.

    More about this item

    Keywords

    Structural credit risk models; Hidden parameters; Iterative algorithm;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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