Do decreases in Distance-to-Default predict rating downgrades?

Abstract

Credit rating agencies have long been criticized for being slow to downgrade ratings, when the financial health of the firm deteriorates. This stands out in sharp contrast to how security market prices of the firm respond more rapidly, during the same time. In this paper, we ask whether this disparity between the two indicators can be bridged. We estimate a logit model for the probability of a rating downgrade, using a large dataset of firms in India which combines both high frequency market price data and lower frequency accounting data. We find that changes in measures such as the Distance to Default, in combination with firm characteristics such as ownership structure, can predict a higher probability of ratings downgrades, before they are announced. This will be particularly useful for regulated financial firms, which have to re-weight their portfolios to satisfy micro-prudential requirements, based on downgrades in credit ratings.