Assessment of mortgage default risk via Bayesian state space models. (English) Zbl 1283.62211

Summary: Managing risk at the aggregate level is crucial for banks and financial institutions as required by the Basel III framework. we introduce discrete time Bayesian state space models with Poisson measurements to model aggregate mortgage default rates. We discuss parameter updating, filtering, smoothing, forecasting and estimation using Markov chain Monte Carlo methods. In addition, we investigate the dynamic behavior of the default rates and the effects of macroeconomic variables. We illustrate the use of the proposed models using actual U.S. residential mortgage data and discuss insights gained from Bayesian analysis.


62P05 Applications of statistics to actuarial sciences and financial mathematics
62F15 Bayesian inference
65C40 Numerical analysis or methods applied to Markov chains
91B30 Risk theory, insurance (MSC2010)
65C60 Computational problems in statistics (MSC2010)


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