Default Prediction Models: The Role of Forward-Looking Measures of Returns and Volatility
39 Pages Posted: 30 May 2017 Last revised: 11 Feb 2018
Date Written: July 27, 2017
This paper proposes a variant application of the Merton distance-to-default model by employing implied volatility and implied a cost of capital to forecast defaults. The proposed model's results are compared with predictions obtained from three popular models in different setups. We find that our "best" model, which contains both forward-looking proxies does outperform other models with a default prediction accuracy rate of 89%. Additional analysis using a discrete-time hazard model indicates that the psuedo-R2 values from regression models that include the two implied measures are as high as 51%. Overall, our results establish the informational relevance of implied cost of capital and implied volatility in predicting defaults.
Keywords: Default Prediction, Distance to Default, Implied Cost of Capital, Implied Volatility
JEL Classification: G130
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