The stochastic collocation Monte Carlo sampler: highly efficient sampling from ‘expensive’ distributions

DOI10.1080/14697688.2018.1459807zbMath1428.62048OpenAlexW3123528665MaRDI QIDQ5234297

Lech A. Grzelak, María Suárez-Taboada, Cornelis W. Oosterlee, Jeroen A. S. Witteveen

Publication date: 26 September 2019

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/14697688.2018.1459807

zbMATH Keywords

Monte CarloLagrange interpolationexact samplingstochastic collocationHestonsquared Bessel

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to actuarial sciences and financial mathematics (62P05) Monte Carlo methods (65C05) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35)

Related Items (7)

The collocating local volatility framework – a fresh look at efficient pricing with smile ⋮ BENCHOP – SLV: the BENCHmarking project in Option Pricing – Stochastic and Local Volatility problems ⋮ Monte Carlo Methods for Radiative Transfer with Singular Kernels ⋮ Sparse grid method for highly efficient computation of exposures for xVA ⋮ A Monte Carlo method for 3D radiative transfer equations with multifractional singular kernels ⋮ Analytical solvability and exact simulation in models with affine stochastic volatility and Lévy jumps ⋮ COLLOCATING VOLATILITY: A COMPETITIVE ALTERNATIVE TO STOCHASTIC LOCAL VOLATILITY MODELS

Uses Software

• pchip

Cites Work

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