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Recovering Posterior Beliefs in Credit Risk: A Latent-State EM Extension of the Information-Geometric Framework
This paper develops a latent-state framework for recovering borrower-level posterior beliefs in credit-risk analysis. Creditworthiness and financial fragility are represented as latent dimensions, while observed borrower scores follow a finite Gaussian mixture model and default depends on the latent
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