Least-squares Importance Sampling for Monte Carlo security pricing

DOI10.1080/14697680701762435zbMath1154.91433arXivphysics/0703181OpenAlexW3125877414MaRDI QIDQ3605223

Luca Capriotti

Publication date: 23 February 2009

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

Full work available at URL: https://arxiv.org/abs/physics/0703181

zbMATH Keywords

Monte Carlo methodsderivatives pricingfinancial engineeringfinancial derivatives

Mathematics Subject Classification ID

Numerical methods (including Monte Carlo methods) (91G60) Approximation methods and heuristics in mathematical programming (90C59) Microeconomic theory (price theory and economic markets) (91B24)

Related Items (6)

Non-parametric partial importance sampling for financial derivative pricing ⋮ On an automatic and optimal importance sampling approach with applications in finance ⋮ Improved initial sampling for the ensemble Kalman filter ⋮ Targeting Kollo skewness with random orthogonal matrix simulation ⋮ Efficient Importance Sampling in Quasi-Monte Carlo Methods for Computational Finance ⋮ An efficient exponential twisting importance sampling technique for pricing financial derivatives

Cites Work

• Martingales and arbitrage in multiperiod securities markets
• Monte Carlo methods for security pricing
• Asymptotically Optimal Importance Sampling and Stratification for Pricing Path-Dependent Options
• The Sample Average Approximation Method for Stochastic Discrete Optimization
• Importance Sampling for Portfolio Credit Risk
• Adaptative Monte Carlo Method, A Variance Reduction Technique
• Simulation-based optimization—convergence analysis and statistical inference

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