Most banks employ historical simulation for Value-at-Risk (VaR) calculations, where VaR is computed from a lower … faster than MC simulation and which avoids the single-sample bias of historical simulation. Ran- dom orthogonal matrix (ROM …) simulation is a fast matrix-based simulation method that applies directly to an historical sample, or to a parametric …

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 …

Most banks employ historical simulation for Value-at-Risk (VaR) calculations, where VaR is computed from a lower … faster than MC simulation and which avoids the single-sample bias of historical simulation. Random orthogonal matrix (ROM …) simulation is a fast matrix-based simulation method that applies directly to an historical sample, or to a parametric …

This paper explores the properties of random orthogonal matrix (ROM) simulation when the random matrix is drawn from …

Large scale, computationally expensive simulation models pose a particular challenge when it comes to estimating their … parameters from empirical data. Most simulation models do not possess closed form expressions for their likelihood function …, requiring the use of simulation-based inference, such as simulated method of moments, indirect inference or approximate Bayesian …

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 …