This paper discusses identification problems in the fractionally cointegrated system of Johansen (2008) and Johansen and Nielsen (2012). The identification problem arises when the lag structure is over-specified, such that there exist several equivalent reparametrization of the model associated...

The paper introduces the model confidence set (MCS) and applies it to the selection of models. A MCS is a set of models that is constructed such that it will contain the best model with a given level of confidence. The MCS is in this sense analogous to a confidence interval for a parameter. The...

We examine the quantification of operational risk for banks. We adopt a financial-economics approach and interpret operational risk management as a means of optimizing the profitability of an institution along its value chain. We start by defining operational risk and then propose a...

We propose a simple and implementable model of credit contagion where we in-clude macro- and microstructural dependencies among the debtors within a creditportfolio. We show that, even for diversified portfolios, moderate microstructuraldependencies have already a significant impact on the tails...

We present a multi-period mean-variance optimization program which allows for a joint optimization of the balance and off-balance sheet. Our first finding is the proof of a conjecture of Li and Ng (cf. [LN00]), Leippold, Trojani and Vanini (cf. [LTV04], [LTV03]) about the equivalence of the...

In this paper operational risk are considered from a purely business or profitability point of view. We show for quantifiable operational risk that the three basic figures for profitability management - value, costs and risks - can be modelled such that an integrative point of view on...

The Basel Committee on Banking Supervision ("the Committee") released a consultative document that included a regulatory capital charge for operational risk. Since the release of the document, the complexity of the concept of "operational risk" has led to vigorous and recurring discussions. We...

This paper studies vector autoregressive models with parsimoniously time-varying parameters. The parameters are assumed to follow parsimonious random walks, where parsimony stems from the assumption that increments to the parameters have a non-zero probability of being exactly equal to zero.We...

We propose a nonparametric approach to the estimation and testing of structural change in time series regression models. Under the null of a given set of the coefficients being constant, we develop estimators of both the nonparametric and parametric components. Given the estimators under null...

We analyze and compare the properties of various methods for bias-correcting parameter estimates in vector autoregressions. First, we show that two analytical bias formulas from the existing literature are in fact identical. Next, based on a detailed simulation study, we show that this simple...