The purpose of this paper is to present a comprehensive Monte Carlo simulation study on the performance of minimum …

This paper develops a simulation estimation algorithm that is particularly useful for estimating dynamic panel data …

We propose a novel Monte Carlo simulation method for two-dimensional stochastic differential equation (SDE) systems … based on approximation through continuous-time Markov chains (CTMCs). Specifically, we propose an efficient simulation … and the stochastic alpha beta rho (SABR) models as special cases. Our simulation algorithm is constructed based on …

VaR calculation that will be developed in the form of High-order kernel estimator of VaR with historical simulation method … with Historical Simulation estimation methods and the combination of high order kernels increase with increasing order … kernel estimates and tend to be larger than the Historical Simulation estimation methods. Statistical properties indicates …

This paper builds on the Empirical Monte Carlo simulation approach developed by Huber et al. (2013) to study the …

exhaustive simulation study with thousands of randomly generated scenarios to make general statements about over-adjusting in …

in latent-variable and other models estimated through simulation-based methods. In both re-parameterizations the …, and discusses the potential comparative advantages of using them in the context of regression modeling and simulation …

We report a simulation study where we want to consider a fairly simple data generating process (DGP) used in Nordman …

period from 1985-2006, so the sample is small, a bootstrap simulation is applied, to improve the estimations …