tails of standardized GARCH residuals. Monte Carlo simulation shows that our method consistently provides lower VaR forecast … estimation risk of robust VaR forecasts implies VaR prediction intervals that can be nearly 20% narrower and 50% less volatile …

Simulation, and classical Filtered Historical Simulation methods. We show empirically that robust estimation reduces tail …. The method is based on a robust estimation of parametric GARCH models and a robustified resampling scheme for GARCH … residuals that controls bootstrap instability due to outlying observations. A Monte Carlo simulation shows that our robust …

distribution specifications or historical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation … assumptions on the underlying statistical distributions, a variety of analytical methods and simulation-based methods are … simulation context.<BR> This paper tries to fill this gap by investigating these VaR concepts in a general distribution …

orhistorical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation have receivedsubstantial … the underlying statistical distributions, a variety of analyticalmethods and simulation-based methods are available. Aside … and incremental VaR in either a non-normal analytical setting or a MonteCarlo / historical simulation context.This paper …

The paper compares two approaches to the estimation of panel probit models: the Generalized Method of Moments (GMM) and …. Particular attention is paid to a three-stage GMM estimator based on nonparametric estimation of optimal instruments. A Monte …

In this paper, we introduce a new Poisson mixture model for count panel data where the underlying Poisson process … Gibbs sampling scheme. We apply our model to a recent household panel of supermarket visit counts. We estimate the …

In panel data the interest is often in slope estimation while taking account of the unobserved cross sectional … heterogeneity. This paper proposes two nonparametric slope estimation where the unobserved effect is treated as fixed across cross … variable. Simulation results suggest that the new nonparametric estimators perform better than the parametric counterparts. We …

estimation of the panel probit model. Both techniques circumvent multiple integration of joint density functions without the need … paid to a three-stage GMM estimator based on nonparametric estimation of the optimal instruments for given conditional …

Economic theory commonly distinguishes between different time horizons such as the short run and the long run, each …. This paper proposes a new estimator for non-stationary panel data models, a bandspectrum cointegration estimator. The … efficient than estimates from a model with non-stationary data. Still, simulation results in the paper show that the …