This paper addresses whether credit rating downgrades feed back on the asset value of the downgraded companies, causing real losses. To investigate this issue we construct a structural credit risk model incorporating ratings and the feedback loss. To estimate the parameters of the model we develop a maximum likelihood estimator using time series of equity prices and credit ratings. Implementing the model on a sample of US public firms downgraded from investment grade to junk, we find strong support for the existence of feedback losses. First, estimated feedback losses are significant for a third of our sample with the cross-sectional averages of the feedback loss around 7 %. Second, the behavior of estimated asset volatilities around downgrades in real data is consistent with the predictions of our model. We observe a hump-shaped pattern of estimated asset volatilities when feedback is ignored. Using the feedback model, the hump-shaped pattern disappears. These findings suggest that ignoring feedback can lead to the appearance of changing asset volatility even when the real volatility is constant. Last, accounting for feedback helps in asset volatility prediction.
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Paper provided by ESSEC Research Center, ESSEC Business School in its series ESSEC Working Papers with number
DR 06016.
Find related papers by JEL classification: C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models G00 - Financial Economics - - General - - - General
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