Since the advent of Markov chain Monte Carlo (MCMC) methods in the early 1990s, Bayesian methods have been proposed for a large and growing number of applications. One of the main advantages of Bayesian inference is the ability to deal with many different sources of uncertainty, including data,...

We show that the news is a rich source of data on distressed firm links that drive firm- level and aggregate risks. The news tends to report about links in which a less popular firm is distressed and may contaminate a more popular firm. This constitutes a contagion channel that yields...

We measure the economic risk of COVID-19 at a geo-spatially detailed resolution. In addition to data about the current prevalence of confirmed cases, we use data from 2014-2018 and a conceptual disaster risk model to compute measures for exposure, vulnerability, and resilience of the local...

This paper captures and measures the longevity risk generated by an annuity product. The longevity risk is materialized by the uncertain level of the future liability compared to the initially foretasted or expected value. Herein we compute the solvency capital (SC) of an insurer selling such a...

We measure the economic risk of epidemics at a geo-spatially detailed resolution. In addition to data about the epidemic hazard prediction, we use data from 2014-2019 to compute measures for exposure, vulnerability, and resilience of the local economy to the shock of an epidemic. Using a battery...