An intensive and still growing body of research focuses on estimating a portfolio’s Value-at-Risk.Depending on both the degree of non-linearity of the instruments comprised in the portfolio and thewillingness to make restrictive assumptions on the underlying statistical distributions, a...

We define a dynamic and self-adjusting mixture of Gaussian Graphical Models to cluster financial returns, and provide a new method for extraction of nonparametric estimates of dynamic alphas (excess return) and betas (to a choice set of explanatory factors) in a multivariate setting. This...

Dynamic portfolio choice has been a central and essential objective for institutional investors in active asset management. In this paper, we study the dynamic portfolio choice with multiple conditioning variables, where the number of the conditioning variables can be either fixed or di- verging...

The catastrophic failures of risk management systems in 2008 bring to the forefront the need for accurate and flexible estimators of market risk. Despite advances in the theory and practice of evaluating risk, existing measures are notoriously poor predictors of loss in high-quantile events. To...

From a banking supervisory perspective, this paper analyses aspects of market risk of an aggregated trading portfolio comprised of the trading books of 11 German banks with a regulatory approved internal market risk model. Based on real, clean profit and loss data and Value-at-Risk estimates of...

Normal distribution of the residuals is the traditional assumption in the classical multivariate time series models. Nevertheless it is not very often consistent with the real data. Copulae allows for an extension of the classical time series models to nonelliptically distributed residuals. In...

We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted...

We forecast portfolio risk for managing dynamic tail risk protection strategies, based on extreme value theory, expectile regression, Copula-GARCH and dynamic GAS models. Utilizing a loss function that overcomes the lack of elicitability for Expected Shortfall, we propose a novel Expected...

Financial experts assume that measures the risk of financial asset returns generally have a normal distribution. Reality often shows asset returns are not normally distributed, so that the constraints and make it difficult to estimate the risk of taking the measurements. For it is necessary to...