An importance sampling method based on the density transformation of Lévy processes

DOI10.1515/156939606777488833zbMath1099.65005OpenAlexW2055249544MaRDI QIDQ5487896

Reiichiro Kawai

Publication date: 13 September 2006

Published in: Monte Carlo Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/156939606777488833

zbMATH Keywords

subordinationimportance samplingconvergence accelerationMonte Carlo simulationsvariance reductionLévy measureseries representationEsscher transformNumerical examplesMeixner processCGMY processGamma processfinancial derivatives pricing

Mathematics Subject Classification ID

Infinitely divisible distributions; stable distributions (60E07) Processes with independent increments; Lévy processes (60G51) Numerical methods (including Monte Carlo methods) (91G60) Monte Carlo methods (65C05) Derivative securities (option pricing, hedging, etc.) (91G20) Analysis of variance and covariance (ANOVA) (62J10)

Related Items (8)

On Monte Carlo and Quasi-Monte Carlo Methods for Series Representation of Infinitely Divisible Laws ⋮ Optimizing Adaptive Importance Sampling by Stochastic Approximation ⋮ Numerical inverse Lévy measure method for infinite shot noise series representation ⋮ Numerical aspects of shot noise representation of infinitely divisible laws and related processes ⋮ On sample average approximation algorithms for determining the optimal importance sampling parameters in pricing financial derivatives on Lévy processes ⋮ A general control variate method for option pricing under Lévy processes ⋮ Optimal importance sampling for Lévy processes ⋮ Iterative Path Integral Approach to Nonlinear Stochastic Optimal Control Under Compound Poisson Noise

Cites Work

• Approximations of small jumps of Lévy processes with a view towards simulation
• Financial Modelling with Jump Processes
• Unnamed Item

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