Efficient simulation of tail probabilities of sums of correlated lognormals

DOI10.1007/s10479-009-0658-5zbMath1279.60027OpenAlexW2154700532MaRDI QIDQ666348

Leonardo Rojas-Nandayapa, Sandeep Juneja, Jose H. Blanchet, Soren Asmussen

Publication date: 8 March 2012

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://pure.au.dk/ws/files/41924800/imf_thiele_2008_11.pdf

zbMATH Keywords

importance samplingefficiencyBlack-Scholes modelrare-event simulationcross-entropy methodcorrelated lognormalsvanishing relative error

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Sampling theory, sample surveys (62D05) Extreme value theory; extremal stochastic processes (60G70) Probability distributions: general theory (60E05) Large deviations (60F10) Portfolio theory (91G10)

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Uses Software

• QRM

Cites Work

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• The transform likelihood ratio method for rare event simulation with heavy tails
• Efficient rare-event simulation for the maximum of heavy-tailed random walks
• Asymptotics of sums of lognormal random variables with Gaussian copula
• Introduction to rare event simulation.
• Fluid heuristics, Lyapunov bounds and efficient importance sampling for a heavy-tailed \(G/G/1\) queue
• Estimating tail probabilities of heavy tailed distributions with asymptotically zero relative error
• Stochastic simulation: Algorithms and analysis
• Importance sampling for sums of random variables with regularly varying tails
• Improved algorithms for rare event simulation with heavy tails

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