Non-parametric partial importance sampling for financial derivative pricing

DOI10.1080/14697680903496485zbMath1266.91107arXiv0806.0539OpenAlexW2108925153MaRDI QIDQ5300444

Jan C. Neddermeyer

Publication date: 27 June 2013

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

Full work available at URL: https://arxiv.org/abs/0806.0539

zbMATH Keywords

Monte Carlo methodsfinancial engineeringpath-dependent optionsoption pricing via simulationpricing of derivatives securities

Mathematics Subject Classification ID

Numerical methods (including Monte Carlo methods) (91G60) Monte Carlo methods (65C05) Derivative securities (option pricing, hedging, etc.) (91G20)

Related Items (3)

On accelerating Monte Carlo integration using orthogonal projections ⋮ On an automatic and optimal importance sampling approach with applications in finance ⋮ Single-index importance sampling with stratification

Cites Work

• Randomized quasi-Monte Carlo methods in pricing securities
• On the \(L_2\)-discrepancy for anchored boxes
• The effective dimension and quasi-Monte Carlo integration
• Asymptotically Optimal Importance Sampling and Stratification for Pricing Path-Dependent Options
• A Theory of the Term Structure of Interest Rates
• Local Adaptive Importance Sampling for Multivariate Densities With Strong Nonlinear Relationships
• Least-squares Importance Sampling for Monte Carlo security pricing
• Mersenne twister
• Nonparametric Importance Sampling
• Toward real-time pricing of complex financial derivatives
• Computationally Efficient Nonparametric Importance Sampling

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