This study examines factors predicting participation in study abroad programs using a bivariate probit selection model where the probabilities of attending university and studying abroad are jointly estimated. Given that unobserved variables influencing these two sequential events are likely to...

In this paper, we focus on two-factor lattices for general diffusion processes with state-dependent volatilities. Although it is common knowledge that branching probabilities must be between zero and one in a lattice, few methods can guarantee lattice feasibility, referring to the property that...

The concordance probability, also called the C-index, is a popular measure to capture the discriminatory ability of a predictive model. In this article, the definition of this measure is adapted to the specific needs of the frequency and severity model, typically used during the technical...

This paper studies method of simulated moments (MSM) estimators that are implemented using Bayesian methods, specifically Markov chain Monte Carlo (MCMC). Motivation and theory for the methods is provided by Chernozhukov and Hong (2003). The paper shows, experimentally, that confidence intervals...

In this study, we consider the construction of through-the-cycle ("TTC") PD models designed for credit underwriting uses and point-in-time ("PIT") PD models suitable for early warning uses, considering which validation elements should be emphasized in each case. We build PD models using a long...

This paper proposes an approximation method to create an optimal continuous-time portfolio strategy based on a combination of neural networks and Monte Carlo, named NNMC. This work is motivated by the increasing complexity of continuous-time models and stylized facts reported in the literature....