. Issues of parametrization and estimation are discussed. Conditions for covariance stationarity and the existence of the … model provides substantial intuition. Moreover, the model exhibits a strong performance in calculating out-of-sample Value-at-Risk …

We study the implications of the value at risk concept for the bank's optimum amount of equity capital under credit … risk. The market value of loans is risky and lognormally distributed. We show that the required equity capital depends upon …

In this paper we provide a review of copula theory with applications to finance. We illustrate the idea on the … general setup we discuss and provide an intensive literature review of estimation and simulation techniques. Separate section … allocation problems, Value-at-Risk and time series models. The paper is complemented with an extensive simulation study and an …

A strategically minded CFO will realize that strategic corporate risk management is about finding the right balance … between risk prevention and proactive value generation. Efficient risk and performance management requires adequate assessment … of risk and risk exposures on the one hand and performance on the other. Properly designed, a risk measure should provide …

We propose a measure for systemic risk: CoVaR, the value at risk (VaR) of financial institutions conditional on other … institutions being in distress. We define an institution's (marginal) contribution to systemic risk as the difference between CoVaR … systemic risk contribution. We argue for macro-prudential regulation based on the degree to which such characteristics forecast …

the failure of financial modeling. More specifically, current risk models have failed to properly assess the risks … over prevailing models for evaluating stock market risk exposure during distressed market periods. …

In this paper we focus on the analysis of the effect of prediction and estimation risk on the loss distribution, risk … using historical data. The incorporation of prediction and estimation risk generally leads to broader loss distributions and … required may be strongly underestimated if prediction and estimation risk are ignored. …

prefiltration of the data, which certainly impacts the estimation. We make use of the proposed model to obtain an improved estimate … for the Value at Risk. The model is then applied and illustrated to transactions data from Bayer AG, a blue chip stock …

What do academics have to offer market risk management practitioners in financial institutions? Current industry … assessments of market risk. Clearly, the demands of real-world risk management in financial institutions - in particular, real …-time risk tracking in very high-dimensional situations - impose strict limits on model complexity. Hence we stress parsimonious …