This paper focuses on predicting #corporate #default #risk using frailty correlated default #models with subjective judgments. The study uses a #bayesian approach with the Particle Markov Chain #montecarlo algorithm to analyze data from #us public non-financial firms between 1980 and 2019. The findings suggest that the volatility and mean reversion of the hidden factor have a significant impact on the default intensities of the firms.
“... this article provides anchorage to scholarly audiences when scrutinizing the extent to which privacy and security measures qualify as ‘appropriate’ in the context of liability claims and actions
“Our results have implications for insurance contract design, particularly in the realm of long-term contracting.” LIRE
“This paper provides a comprehensive analysis of the recent EU AI Act, the regulatory framework surrounding Artificial Intelligence (AI), focusing on foundation models, open-source exemptions, remote