We introduce the Quantum Alarm System, a novel framework that combines the informational advantages of quantum majorization applied to tail pseudo-correlation matrices with the learning capabilities of a reinforced urn process, to predict financial turmoil and market crashes. This integration...

We propose a new jump-diffusion process, the Heston-Queue-Hawkes (HQH) model, combining the well-known Heston model and the recently introduced Queue-Hawkes (Q-Hawkes) jump process. Like the Hawkes process, the HQH model can capture the effects of self-excitation and contagion. However, since...

We provide a generalisation of the loss of memory property using pseudo-analysis.We show how particular pseudo-sums have direct probabilistic interpretations as an arbitrage-free contingent-claim values. As a side result, we also provide new connections among well-known probability distributions

We propose an alarm system for stock market crashes, combining the informational power of quantum majorization on tail correlation matrices with the predictive performance of a reinforced urn process. The model is tested on the daily log-returns of 30 Dow Jones Industrial Average constituents...

The goal of this note is to introduce a new way of representing and characterizing the Pickands dependence function in the bivariate framework, using the Lorenz curve, a well-know tool in wealth inequality studies.We first notice that the Pickands dependence function is nothing but a Lorenz...

We propose an alternative approach to the modeling of the positive dependence between the probability of default and the loss given default in a portfolio of exposures, using a bivariate urn process. The model combines the power of Bayesian nonparametrics and statistical learning, allowing for...

We propose Quantum Majorization as a way of comparing and ranking correlation matrices, with the aim of assessing portfolio risk in a unified framework. Quantum majorization is a partial order in the space of correlation matrices, which are evaluated through their spectra. We discuss the...

An alternative generating mechanism for non-strict bivariate Archimedean copulas via the Lorenz curve of a positive random variable is proposed. Lorenz curves have been extensively studied in economics and statistics to characterize wealth inequality and tail risk. In this paper, these curves...

Reinforced Urn Processes (RUPs) represent a flexible class of Bayesian nonparametric models suitable for dealing with possibly right-censored and left-truncated observations. A reliable estimation of their hyper-parameters is however missing in the literature. We therefore propose an extension...

Using a Bi-variate Reinforced Urn Process (B-RUP), a novel way of modeling the dependence of coupled lifetimes is introduced, with application to the pricing of joint and survivor annuities. In line with the machine learning paradigm, the model is able to improve its performances over time, but...