This paper proposes a prediction method based on an ordered semiparametric probit model
for credit risk forecast. The proposed prediction model is constructed by replacing the linear …

The usual bankruptcy prediction models are based on single-period data from firms. These
models ignore the fact that the characteristics of firms change through time, and thus they …

For multiple-class prediction, a frequently used approach is based on ordered probit model.
We show that this approach is not optimal in the sense that it is not designed to minimize the …

Bankruptcy prediction methods based on a semiparametric logit model are proposed for
simple random (prospective) and case–control (choice‐based; retrospective) data. The …

Logistic quantile regression (LQR) is used for studying recovery rates. It is developed using
monotone transformations. Using Moody’s Ultimate Recovery Database, we show that the …

Presented is a study in which 6 types of MCC that differ in particle size, particle density, and
silicification were systematically evaluated using design of experiments and statistical …

We examine the evolution of the mechanism behind subjective well-being (SWB) across the
lifespan using data from the 1972–2010 waves of the US General Social Survey. By …

We use a stochastic frontier model with firm-specific technical inefficiency effects in a panel
framework (Battese and Coelli in Empir Econ 20:325–332, 1995 ) to assess two popular …

The dynamic ordered varying-coefficient probit model (DOVPM) is proposed as a model for
studying credit ratings. It is constructed by replacing the constant coefficients of firm-specific …

The dynamic logit model (DLM) with autocorrelation structure (Liang and Zeger Biometrika
73:13–22, 1986 ) is proposed as a model for predicting recurrent financial distresses. This …