The globalisation on financial markets and the development of financial derivatives has increased not only chances but also potential risk within the banking industry. Especially market risk has gained major significance since market price variation of interest rates, stocks or exchange rates...

We introduce a new hybrid approach to joint estimation of Value at Risk (VaR) and Expected Shortfall (ES) for high quantiles of return distributions. We investigate the relative performance of VaR and ES models using daily returns for sixteen stock market indices (eight from developed and eight...

Market risk management is one of the key factors to success in managing financial institutions. Underestimated risk can have desastrous consequences for individual companies and even whole economies, not least as could be seen during the recent crises. Overestimated risk, on the other side, may...

Weekly, quarterly and yearly risk measures are crucial for risk reporting according to Basel III and Solvency II. For the respective data frequencies, the authors show in a simulation and backtest study that available data series are not sufficient in order to estimate Value at Risk and Expected...

In this paper, we characterize explicitly the first derivative of the Value at Risk and the Expected Shortfall with respect to portfolio allocation when netting between positions exists. As a particular case, we examine a simple Gaussian example in order to illustrate the impact of netting...

We propose a general robust semiparametric bootstrap method to estimate conditional predictive distributions of GARCH-type models. Our approach is based on a robust estimator for the parameters in GARCH-type models and a robustified resampling method for standardized GARCH residuals, which...

Empirical studies have shown that a large number of financial asset returns exhibit fat tails and are often characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in market volatility, with significant impact on pricing and...

We consider the problem of estimating the conditional quantile of a time series at time t given observations of the same and perhaps other time series availableat time t − 1. We discuss sieve estimates which are a nonparametric versions ofthe Koenker-Bassett regression quantiles and do not...