Taking advantage of recently augmented corporate bond transaction data, we examine the pricing implications of informed trading in corporate bonds and its ability to predict corporate defaults. We find that microstructure measures of information asymmetry seem to capture adverse selection in...

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...

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...

This paper introduces the quantile regression- based Distance-to-Default to Probability of Default (DD-PD) mapping, which links individual firms' DD to their real world PD. Since changes in the DD depend on a handful of parameters, the mapping easily accommodates shocks arising from quantitative...

Using a structural model of default, we construct a measure of systemic default defined as the probability that many firms default at the same time. We account for correlations in defaults between firms through exposures to common shocks. The systemic default measure spikes during recession...