Journal of Risk

Distance to default based on the CEV–KMV model

Wen Su

  • We find a linear relationship between asset volatility and asset value.
  • We apply the CEV process into the KMV model, which enhances the forecasting ability.
  • We use the use the equivalent volatility method to estimate the CEV parameters.
  • We find the local volatility structures of ST and non ST companies may differ.

This paper presents a new method with which to assess default risk based on applying the constant elasticity of variance (CEV) process to the Kealhofer-McQuown-Vasicek (KMV) model. We find that the volatility of the firm’s asset value may not be a constant, so we assume that the firm’s asset value dynamics are given by the CEV process dVA/VAAdt+δ VAβ−1dB and use the equivalent volatility method to estimate the parameters. In terms of distance to default, our CEV-KMV model fits the market better when forecasting credit risk compared with the classical KMV model. Moreover, the estimation results show that β>1 for non-special treatment (non-ST) companies and that β<1 for special treatment (ST) companies, which shows their difference with respect to the firm’s assets in the local volatility structure: ST volatility decreases while non-ST volatility increases.

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