We estimate time series of option implied Probabilities of Default (PoDs) for 19 major US financial institutions from 2002 to 2012. These PoDs are estimated as mass points of entropy based risk neutral densities and subsequently corrected for maturity dependence. The obtained time series are...

In this paper we 'update' the option implied probability of default (option iPoD) approach recently suggested in the literature. First, a numerically more stable objective function for the estimation of the risk neutral density is derived whose integrals can be solved analytically. Second, it is...

This paper analyzes the evolution of the degree of global cyclical interdependence over the period 1960-2005. We categorize the 106 countries in our sample into three groups: industrial countries, emerging markets, and other developing economies. Using a dynamic factor model, we then decompose...

Distinguishing pure supply effects from other determinants of price and quantity in the market for loans is a notoriously difficult problem. Using German data, we employ Bayesian vector autoregressive models with sign restrictions on the impulse response functions in order to enquire the role of...

Elements of an econometric examination of benchmark revisions in real-time data are suggested. Structural break tests may be applied to detect heterogeneities within vintages. Systems cointegration tests are helpful to reveal inconsistencies across vintages. Differencing and rebasing, often used...

Default probabilities (PDs) and correlations play a crucial role in the New Basel Capital Accord. In commercial credit risk models they are an important constituent. Yet, modeling and estimation of PDs and correlations is still under active discussion. We show how the Basel II one factor model...

In this paper we focus on the analysis of the effect of prediction and estimation risk on the loss distribution, risk measures and economic capital. When variables for the determination of probability of default and loss distribution have to be predicted because they are not available at the...

Group-specific estimations can significantly improve the predictive power of accountingbased rating models. This is shown using a binary logistic regression model applied to the Deutsche Bundesbank's USTAN dataset, which contains 300,000 financial statements provided by German companies for the...

This paper considers factor estimation from heterogenous data, where some of the variables are noisy and only weakly informative for the factors. To identify the irrelevant variables, we search for zero rows in the loadings matrix of the factor model. To sharply separate these irrelevant...

This paper presents a novel Bayesian method for estimating dynamic stochastic general equilibrium (DSGE) models subject to a constrained posterior distribution of the implied Sharpe ratio. We apply our methodology to a DSGE model with habit formation in consumption and leisure, using an estimate...