The GARCH(1,1) model and its extensions have become a standard econometric tool for modeling volatility dynamics of financial returns and port-folio risk. In this paper, we propose an adjustment of GARCH implied conditional value-at-risk and expected shortfall forecasts that exploits the...

In models that have a representation of the form       ) , ( x g y the Wald test for ˆBeta has systematically wrong size in finite samples when the indentifying parameter Gamma is small relative to its estimation error. An alternative test based on linearization of...

Estimation of multivariate volatility models is usually carried out by quasi maximum likelihood (QMLE), for which consistency and asymptotic normality have been proven under quite general conditions. However, there may be a substantial efficiency loss of QMLE if the true innovation distribution...

In this paper we compare the price of an option with one year maturity of the German stock index DAX for several volatility models including long memory and leverage effects. We compute the price by applying a present value scheme as well as the Black-Scholes and Hull-White formulas which...

The paper considers the Markov-Switching GARCH(1,1)-model with time-varying transition probabilities. It derives su?cient conditions for the square of the process to display long memory and provides some additional intuition for the empirical observation that estimated GARCH-parameters often sum...

The convergence of estimators, e.g. maximum likelihood estimators, for increasing sample size is well understood in many cases. However, even when the rate of convergence of the estimator is known, practical application is hampered by the fact, that the estimator cannot always be obtained at...

Using unobservable conditional variance as measure, latent-variable approaches, such as GARCH and stochastic-volatility models, have traditionally been dominating the empirical finance literature. In recent years, with the availability of high-frequency financial market data modeling realized...

A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal-GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast, easy to implement, numerically reliable, and,...

Während direkte Immobilieninvestments lang Zeit als renditeträchtig bei gleichzeitig begrenztem Risiko galten, führte den Anlegern insbesondere die gegenwärtige Finanzmarktkrise vor Augen, dass auch Immobilienanlagen insbesondere in den USamerikanischen Häusermarkt mit hohen Risiken...

We use an information-theoretic approach to interpret Engle's (1982) and Bollerslev's (1986) GARCH model as a model for the motion in time of the expected conditional second power moment. This interpretation is used to show how these models may be generalized, if we use alternative measures of...