Fast simulation of rare events in queueing and reliability models
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Modelling extremal events: for insurance and finance
Modelling extremal events: for insurance and finance
Simulating GI/GI/1 queues and insurance risk processes with subexponential distributions
Proceedings of the 32nd conference on Winter simulation
Simulating heavy tailed processes using delayed hazard rate twisting
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Variance Reduction Techniques for Estimating Value-at-Risk
Management Science
The Transform Likelihood Ratio Method for Rare Event Simulation with Heavy Tails
Queueing Systems: Theory and Applications
Proceedings of the 35th conference on Winter simulation: driving innovation
Perwez Shahabuddin, 1962--2005: A professional appreciation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Asymptotics and fast simulation for tail probabilities of maximum of sums of few random variables
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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We consider the problem of estimating the small probability that a function of a finite number of random variables exceeds a large threshold. Each input random variable may be light-tailed or heavy-tailed. Such problems arise in financial engineering and other areas of operations research. Specific problems in this class have been considered earlier in the literature, using different methods that depend on the special properties of the particular problem. Using the Laplace principle (in a restricted finite-dimensional setting), this paper presents a unified approach for deriving the log-asymptotics, and developing provably efficient fast simulation techniques using the importance sampling framework of hazard rate twisting.