Miao, Hong, authorRamchander, Sanjay, authorRyan, Patricia, authorWang, Tianyang, authorJournal of Empirical Finance, publisher2020-05-122020-05-122017-07-29Miao, H., Ramchander, S., Ryan, P., & Wang, T. (2018). Default prediction models: The role of forward-looking measures of returns and volatility. Journal of Empirical Finance, 46, 146–162. https://doi.org/10.1016/j.jempfin.2018.01.001https://hdl.handle.net/10217/206712Includes bibliographical references (pages 24-26).Published as: Journal of Empirical Finance, vol. 46, March 2018, pp. 146-162, https://doi.org/10.1016/j.jempfin.2018.01.001.This paper proposes a variant application of the Merton distance-to-default model by employing implied volatility and implied cost of capital to predict 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 forward-looking proxies of returns and volatility outperform other models, carries a default prediction accuracy rate of 89%. Additional analysis using a discrete-time hazard model indicates the pseudo-R² values from regression models that include the two forward-looking measures are as high as 51%. Overall, our results establish the informational relevance of implied cost of capital and implied volatility in predicting defaults.born digitalarticleseng©2018 Elsevier. Author can archive pre-print and post-print.Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.distance to defaultdefault predictionimplied cost of capitalimplied volatilityText