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

Simulation estimators, such as indirect inference or simulated maximum likelihood, are successfully employed for … variance suffers from an additional component, which depends on the stochastic simulation involved in the estimation procedure …. To reduce this undesirable effect, one could increase the number of simulations (or the length of each simulation) and …

methodology is thus termed "ROM simulation''. We discuss certain classes of random orthogonal matrices and show how each class … produces samples with different characteristics. ROM simulation has applications to many problems that are resolved using … illustration, we apply ROM simulation to determine the value-at-risk of a stock portfolio …

In this paper we use Monte Carlo simulation to investigate the impact of effect size heterogeneity on the results of a …

. This approach is compared with several alternative methods using real data. The paper also develops simulation …