Introduction to Credit Risk and Capital Management Frameworks -- Credit Data and Processing -- Credit Modeling Techniques -- Allowance for Credit Loss and CECL -- Capital Management and Risk Weighted Asset -- Stress Test and CCAR -- Underwriting and Credit Scoring.

Why should risk management systems account for parameter uncertainty? In order to answer this question, this paper lets an investor in a credit portfolio face non-diversifiable estimation-driven uncertainty about two parameters: probability of default and asset-return correlation. Bayesian...

We describe a method to improve credit portfolio models based on the Merton model by adding to the underlying distributions forward-looking tails deducted through the Bayesian Networks technology. Given the forward-looking stance of the approach, its results give a better quanti ed picture of...

We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted...

Using a Bayesian time‐varying beta model, we explore how the systematic risk exposures of hedge funds vary over time conditional on some exogenous variables that managers are assumed to use in changing their trading strategies. In such a setting, we impose a structure on fund returns, betas...

In this article, we extend the Black-Litterman approach to a continuous time setting. We model analyst views jointly with asset prices to estimate the unobservable factors driving asset returns. The key in our approach is that the filtering problem and the stochastic control problem are...