Dependence among defaults both across assets and over time has proven to be an important characteristic of financial risk. A Bayesian approach to default rate estimation is proposed and illustrated using a prior distributions assessed from an experienced industry expert. Two extensions of the...

A Bayesian approach to default rate estimation is proposed and illustrated using a prior distribution assessed from an experienced industry expert. The principle advantage of the Bayesian approach is the potential for coherent incorporation of expert information--crucial when data are scarce or...

Incorporation of expert information in inference or decision settings is often important, especially in cases where data are unavailable, costly or unreliable. One approach is to elicit prior quantiles from an expert and then to fit these to a statistical distribution and proceed according to...

Capital allocation decisions are made on the basis of an assessment of creditworthiness. Default is a rare event for most segments of a bank's portfolio and data information can be minimal. Inference about default rates is essential for efficient capital allocation, for risk management and for...

Kernel smoothing techniques have attracted much attention and some notoriety in recent years. The attention is well deserved as kernel methods free researchers from having to impose rigid parametric structure on their data. The notoriety arises from the fact that the amount of smoothing (i.e.,...

Accurate credit-granting decisions are crucial to the efficiency of the decentralized capital allocation mechanisms in modern market economies. Credit bureaus and many .nancial institutions have developed and used credit-scoring models to standardize and automate, to the extent possible, credit...

Lenders use rating and scoring models to rank credit applicants on their expected performance. The models and approaches are numerous. We explore the possibility that estimates generated by models developed with data drawn solely from extended loans are less valuable than they should be because...

In this paper we analyze heteroskedasticity-autocorrelation (HAC) robust tests constructed using the Bartlett kernel without truncation. We show that while such an HAC estimator is not consistent, asymptotically valid testing is still possible. We show that tests using the Bartlett kernel...

Banks using either the Foundation or Advanced option of the Internal Ratings Based approach to credit risk under Basel II must estimate long-run annual average default probabilities for buckets of homogeneous assets. The one-factor model underlying the capital calculations in Basel II has...

A model selection procedure based on a general criterion function, with an example of the Kullback-Leibler Information Criterion (KLIC) using quasi-likelihood functions, is considered for dynamic non-nested models. We propose a robust test which generalizes Lien and Vuong's (1987) test with a...