Antje Berndt

Measuring Default Risk Premia from Default Swap Rates and EDFs

This paper estimates recent default risk premia for U.S. corporate debt, based on a close relationship between default probabilities, as estimated by Moodys KMV EDFs, and default swap (CDS) market rates. The default-swap data, obtained through CIBC from 22 banks and specialty dealers, allow us to establish a strong link between actual and risk-neutral default probabilities for the 69 firms in the three sectors that we analyze: broadcasting and entertainment, healthcare, and oil and gas. We find dramatic variation over time in risk premia, from peaks in the third quarter of 2002, dropping by roughly 50% to late 2003.

On Correlation and Default Clustering in Credit Markets

We establish Markovian models in the Heath, Jarrow, and Morton (1992) paradigm that permit an exponential affine representation of riskless and risky bond prices while offering significant flexibility in the choice of volatility structures. Estimating models in our family is typically no more difficult than in the workhorse affine family. Besides diffusive and jump-induced default correlations, defaults can impact the credit spreads of surviving firms, allowing for a greater clustering of defaults. Numerical implementations highlight the importance of incorporating interest rate--credit spread correlations, credit spread impact factors, and the full credit spread curve when building a unified framework for pricing credit derivatives. The Author 2010. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.

What Broker Charges Reveal About Mortgage Credit Risk

Prior to the subprime crisis, mortgage brokers charged higher percentage fees for loans that turned out to be riskier ex post, even when conditioning on other risk characteristics. High conditional fees reveal borrower attributes that are associated with high borrower risk, such as suboptimal shopping behavior, high valuation for the loan or high borrower-specific broker costs. Borrowers who pay high conditional fees are inherently more risky, not just because they pay high fees. We find a stronger association between conditional fees and delinquency risk when lenders have fewer incentives to screen bor- rowers, for purchase rather than refinance loans, and for loans originated by brokers who have less frequent interactions with the lender. Our findings shed light on the pro- posed QRM exemption criteria for risk retention requirements for residential mortgage securitizations.