We compare six modeling methods for Loss Given Default (LGD). We find that non-parametric methods (regression tree and neural network) perform better than parametric methods both in and out of sample when over-fitting is properly controlled. Among the parametric methods, fractional response...

Inspired by the linear predictability and nonlinearity found in the finance literature, this article examines the nonlinear predictability of the excess returns. The relationship between the excess returns and the predicting variables is recursively modeled by a neural-network model, which is...

Recent research in finance has indicated that the institutional structure in which financial asset prices are determined can have a nontrivial impact on pricing. This report examines transaction level data for Treasury Note futures contracts traded at the Chicago Board of Trade (CBOT) to...

This study examines the distribution of extreme values in daily currency changes for nine Asian countries. Using an improved estimator, extreme changes in Asian currencies can generally be represented by Frechet distributions. Our results are robust to the choice of the numeraire currency, the...

This paper studies loss given default using a large set of historical loan-level default and recovery data of high loan-to-value residential mortgages from several private mortgage insurance companies. We show that loss given default can largely be explained by various characteristics associated...