perspectives. The treatment in both cases is based on simulation using importance sampling and antithetic variables; Monte Carlo … conditional and posterior densities and distribution functions. Choice of importance sampling densities and antithetic variables …

special interest is efficient importance sampling which allows a substantial reduction of the computational burden. Efficiency … of importance sampling has been proved (see Sadowsky and Bucklew [19]) under rather strong assumptions, which often … cannot be verified for particular test statistics and estimators. In this paper we show that efficient importance sampling …

volatility model. For both methods, the likelihood function is estimated using importance sampling techniques. Based on a Monte … Carlo study, we assess which method is more effective. Further, we validate the two methods using diagnostic importance … sampling test procedures. Stochastic volatility models with Gaussian and Student-t distributed disturbances are considered. …

technique adopting the efficient importance sampling approach of Richard & Zhang (2005). We provide an application to a trading …

In this article we describe and discuss implementation of a weighted simulation procedure, importance sampling, in the …

approaches, efficient simulation methods based on importance sampling have been developed for the Monte Carlo maximum likelihood … estimation of univariate SV models. This paper shows that importance sampling methods can be used in a general multivariate SV …, are used to show the effectiveness of the importance sampling methods. …