Various economic theories are available to explain the existence of credit and default cycles. There remains empirical ambiguity, however, as to whether or these cycles coincide. Recent papers_new suggest by their empirical research set-up that they do, or at least that defaults and credit...

We model 1981-2002 annual US default frequencies for a panel of firms in different rating and age classes. The data is decomposed into a systematic and firm-specific risk component, where the systematic component reflects the general economic conditions and default climate. We have to cope with...

We study the relation between the credit cycle and macro-economic fundamentals in an intensity-based framework. Using rating transition and default data of U.S. corporates from Standard and Poor’s over the period 1980-2005 we directly estimate the credit cycle from the micro rating data. We...

This paper considers the problem of forecasting a collection of short time series using cross sectional information in panel data. We construct point predictors using Tweedie's formula for the posterior mean of heterogeneous coeffcients under a correlated random effects distribution. This...

We introduce a smooth transition Generalized Pareto (GP) regression model to study the link between extreme losses and the economic context. The advantage of our approach consists in specifying a time-varying dependence structure between financial factors and the severity distribution of the...

We estimate a large Bayesian time-varying parameter vector autoregressive (TVP-VAR) model of daily stock return volatilities for 35 U.S. and European financial institutions. Based on that model we extract a connectedness index in the spirit of Diebold and Yilmaz (2014) (DYCI). We show that the...

Many forms of the ARIMA (auto-regressive integrated moving average) modeling method are used across risk management and specifically within PPNR (Pre-Provision Net Revenue) for CCAR (Comprehensive Capital Analysis and Review) and DFAST (Dodd-Frank Act Stress Testing). The ARIMA method allows for...

In several recent studies unit root methods have been used in detection of financial bubbles in asset prices. The basic idea is that fundamental changes in the autocorrelation structure of relevant time series imply the presence of a rational price bubble. We provide cross-country evidence for...

This short note is a description of the dataset compiled during the drafting of Cash and Dash: How ATMs and Computers Changed Banking (Oxford University Press, 2018). The full dataset is deposited with the European Association for Banking and Financial History, and is available for download from...

This paper proposes a procedure for the determination of the minimal length of the historical time series of daily deposit variations in accordance with an institution’s specific risk tolerance. In a previously released paper we developed a methodology to ascertain an institutional specific...