We study the economic benefits from using credit scoring models. We contribute to the
literature by relating the discriminatory power of a credit scoring model to the optimal credit …

We present a prediction model to forecast corporate defaults. In a theoretical model, under
incomplete information in a market with publicly traded equity, we show that our approach …

Well-performing default predictions show good discrimination and calibration. Discrimination
is the ability to separate defaulters from nondefaulters. Calibration is the ability to make …

Purpose : We prospectively evaluated the value of nuclear matrix protein 22 (NMP22 †) and
cytology in the diagnosis of bladder cancer. Materials and Methods : We analyzed NMP22 in …

We develop a new goodness-of-fit test for validating the performance of probability forecasts.
Our test statistic is particularly powerful under sparseness and dependence in the observed …

I present an analytical valuation framework for the management of fixed-income instruments
traded in imperfectly competitive markets, like demand deposits and credit card loans in the …

Non-maturity deposits like savings accounts or demand deposits contain significant option
risks caused by the bank’s discretionary pricing and the customers’ withdrawal right. Option …

The relation between physical probabilities (rating) and risk-neutral probabilities (pricing) is
derived in a large market with a quasi-factor structure. Factor sensitivities and default …

Corporate credit ratings remove the information asymmetry between lenders and borrowers
to find an equilibrium price. Structured finance ratings, however, are informationally …

A credit rating system in which the number of observed defaults aligns well with the number
of defaults expected by the system demonstrates good calibration. The author derives new …