simulation.Obtaining accurate estimates of such loss probabilities is essential to calculating value-at-risk, which is a quantile …

rates remain fixed. We first consider the case when the quantities are estimated using naive simulation; i.e., when no …, the result only holds for certain partial derivatives of the performance measure when using naive simulation. More … situation that arose when using naive simulation, we prove that in the limit, all derivatives can be estimated as accurately as …

In this paper, we propose a fast adaptive importance sampling method for the efficient simulation of buffer overflow …

algorithms for estimating integrals. The basic idea is to replace the original random mechanism in the simulation by a new one … simulation of stochastic systems. Discrete-time Markov chains, continuous-time Markov chains, and generalized semi …

In this paper we investigate importance sampling techniques for the simulation of Markovian systems with highly … reliable components. The need for simulation arises because the state space of such systems is typically huge, making numerical … computation inefficient. Naive simulation is inefficient due to the rarity of the system failure events. Failure biasing is a …

based upon Monte Carlo simulation for pricing European contingent claims depending on an arbitrary number of risk sources … Carlo simulation. Quadratic resampling can be efficiently combined with classical variance reduction methods such as …

Monte Carlo simulation is widely used to measure the credit risk in portfolios of loans, corporate bonds, and other … instruments subject to possible default. The accurate measurement of credit risk is often a rare-event simulation problem because …

We show how, from a single simulation run, to estimate the ruin probabilities and their sensitivities (derivatives) in …