All sorts of physical processes in this analog world exhibit some degree of randomness. Think of noise, for example. Many noisy processes are described by Gaussian probability distributions. We should ...

Gaussian processes offer a versatile framework to model and analyse continuous random phenomena, making them particularly useful in quantifying the probability of ruin in financial and insurance ...

The generation of synthetic market data is widely seen as one of the most promising applications of sophisticated artificial intelligence models, such as generative adversarial networks (GANs) and ...

Although the literature about measuring probability of default (PD) in retail credit portfolios is vast, the same thing cannot be said about measuring exposure at default (EAD). This paper aims to ...

In this paper we investigate operators that map one or more probability distributions on the positive real line into another via their Laplace-Stieltjes transforms. Our goal is to make it easier to ...

ABSTRACT Linear stochastically forced models have been found to be competitive with comprehensive nonlinear weather and climate models at representing many features of the observed covariance ...