distribution specifications or historical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation …, component VaR and incremental VaR readily follow. The proposed estimation approach pairs intuitive appeal with computational … efficiency. We evaluate various alternative estimation methods in an application example and conclude that the proposed approach …

orhistorical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation have receivedsubstantial … proposed estimation approach pairs intuitiveappeal with computational efficiency. We evaluate various alternative estimation …

Estimation in nonlinear time series models has mainly been performed by least squares or maximum likelihood (ML … respect. On the other hand, the three estimation techniques lead to fairly similar power functions for a linearity test. …

estimation of the volatility in the market plays a key role in quantifying market risk exposure correctly. This paper presents … time-varying volatility. In this paper, the estimation of conditional volatility is applied to Value at Risk measurement …. Univariate as well as multivariate concepts are presented for the estimation of the conditional volatility. …

in the current paper, it turns out that using the Bartlett kernel in the long-run variance estimation renders the most …

Most existing semi-parametric estimation procedures for binary choice models are based on the maximum score, maximum … method offer good potential for practical applications of semi-parametric estimation of binary choice models. …