This paper presents a new model for term risk, yield curve, and credit risk in spreads in a unified approach. The originality lies in the structuring of the Poisson stochastic of risk in a form suitable for finding the differential equation for the yield curve and its spreads as the Poisson...

We propose a novel systemic risk measurement model based on stochastic processes, correlation networks and conditional probabilities of default.For each country we consider three different economic sectors (sovereigns, corporates, banks) and we model each of them as a linear combination of two...

We propose a new Stochastic Dominance (SD) criterion based on standard risk aversion, which assumes decreasing absolute risk aversion and decreasing absolute prudence. To implement the proposed criterion, we develop linear systems of optimality conditions for a given prospect relative to a...

This paper extends quantile factor analysis to a probabilistic variant that incorporates regularization and computationally efficient variational approximations. By means of synthetic and real data experiments it is established that the proposed estimator can achieve, in many cases, better...

This paper proposes Pearson-type statistics based on implied probabilities to detect structural change. The class of generalized empirical likelihood estimators (see Smith (1997)) assigns a set of probabilities to each observation such that moment conditions are satisfied. These restricted...

We present a continuous-time maximum likelihood estimation methodology for credit rating transition probabilities, taking into account the presence of censored data. We perform rolling estimates of the transition matrices with exponential time weighting with varying horizons and discuss the...

When impulse responses in dynamic multivariate models such as identified VARs are given economic interpretations, it is important that reliable statistical inferences be provided. Before probability assessments are provided, however, the model must be normalized. Contrary to the conventional...

We propose a nonparametric Bayesian approach for conducting inference on probabilistic surveys. We use this approach to study whether U.S. Survey of Professional Forecasters density projections for output growth and inflation are consistent with the noisy rational expectations hypothesis. We...

In this paper we provide probability forecasts of key Turkish macro economic variables such as inflation and output growth. Some probabilistic forecasts of different scenarios associated to those variables are also calculated. The probability forecasts take different types of uncertainties...

We propose a new Markov switching model with time varying probabilities for the transitions. The novelty of our model is that the transition probabilities evolve over time by means of an observation driven model. The innovation of the time varying probability is generated by the score of the...