Banks allocate capital across business units while facing multiple constraints that may bind contemporaneously or only in future states. When risks rise or risk management strengthens, a bank reallocates capital to the more efficient unit. This unit would have generated higher constraint- and...

We use tools of extreme value theory to extract information about rare events from market prices. We find that such information contributes materially to measures of banks' systemic importance. These measures exhibit strong and intuitive relationships with simple characteristics of banks'...

We identify three business models using balance sheet characteristics of 222 international banks and a data-driven procedure. We find that institutions engaging mainly in commercial banking activities have lower costs and more stable profits than those more heavily involved in capital market...

Even when securitised assets are simple, transparent and of high quality, risk assessments will be uncertain. This will call for safeguards against potential undercapitalisation. Since the uncertainty concentrates mainly in securitisation tranches of intermediate seniority, the safeguards...

This paper evaluates empirically the performance of six structural credit risk models by comparing the probabilities of default (PDs) they deliver to ex post default rates. In contrast to previous studies pursuing similar objectives, the paper employs firm-level data and finds that theory-based...

While corporate credit losses have been low since the start of the Covid-19 pandemic, their future evolution is quite uncertain. Using a forecasting model with a solid track record, we find that the baseline scenario ("expected losses") is benign up to 2024. This is due to policy support...

A parsimonious extension of a well-known portfolio credit-risk model allows us to study a salient stylized fact - abrupt switches between high- and low-loss phases - from a risk-management perspective. As uncertainty about phase switches increases, expected losses decouple from unexpected...

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...