Bei der Kreditrisikobewertung müssen die Parameter Ausfallwahrscheinlichkeit und korrelation geschätzt werden. Diese Schätzung erfolgt unter Unsicherheit. In der Literatur werden asymptotische Konfidenzregionen diskutiert, um diese Unsicherheit bei der simultanen Schätzung beider Parameter...

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...

The use of probability of default estimates to assess the risks of a credit portfolio should not ignore estimation uncertainty. The latter can be quantified by confidence intervals. But assumptions about dependencies of these intervals are inconsistent with assumptions of conventional credit...

For the popular mean-variance portfolio choice problem in the case without a risk-free asset, we develop a new portfolio strategy to mitigate estimation risk. We show that in both calibrations and real datasets, optimally combining the sample global minimum variance portfolio with a sample...

This study employs L-comoments introduced by Serfling and Xiao (2007) into portfolio Value-at-Risk estimation through two models: the Cornish-Fisher expansion (Draper and Tierney 1973) and modified VaR (Zangari 1996). Backtesting outcomes indicate that modified VaR outperforms and L-comoments...

Many financial decisions such as portfolio allocation, risk management, option pricing and hedge strategies are based on the forecast of the conditional variances, covariances and correlations of financial returns. Although the decisions are based on forecasts covariance matrix little is known...

We evaluate the impact of extreme market shifts on equity portfolios and study the difference in negative and positive reactions to market jumps with implications for portfolio risk management. Employing high-frequency data for the constituents of the S&P500 index over the period 2 January 2003...

Value-at-Risk (VaR) forecasting generally relies on a parametric density function of portfolio returns that ignores higher moments or assumes them constant. In this paper, we propose a new simple approach to estimation of a portfolio VaR. We employ the Gram-Charlier expansion (GCE) augmenting...

The VaR (Value at Risk) concept has emerged back in 1994 when JP Morgan started routinely using it in its daily reporting. Simply said, it represents a lower bound of large rare losses. The VaR metric became an industry standard for measuring market risk because it is intuitive and easy to...