Particle MCMC in forecasting frailty correlated default models with expert opinion

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.