Monte Carlo methods for derivatives of options with discontinuous payoffs

DOI10.1016/j.csda.2006.08.032zbMath1161.62420OpenAlexW1978687634MaRDI QIDQ1019974

Marcel Rindisbacher, Jérôme B. Detemple

Publication date: 29 May 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2006.08.032

zbMATH Keywords

weak convergencesimulationlikelihood ratioderivative estimationcovariationsecond-order biasMalliavin weight

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Monte Carlo methods (65C05)

Related Items

Sequential Monte Carlo Methods for Option Pricing

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Asymptotic properties of Monte Carlo estimators of diffusion processes
• Monte Carlo computation of optimal portfolios in complete markets
• Weak limit theorems for stochastic integrals and stochastic differential equations
• Monte Carlo methods for security pricing
• The law of the Euler scheme for stochastic differential equations. I: Convergence rate of the distribution function
• Efficient Monte Carlo simulation of security prices
• Applications of Malliavin calculus to Monte Carlo methods in finance
• Pricing and Hedging Path-Dependent Options Under the CEV Process
• Asymptotic Properties of Monte Carlo Estimators of Derivatives
• A Unified View of the IPA, SF, and LR Gradient Estimation Techniques
• Estimating Security Price Derivatives Using Simulation
• Efficient Computation of Hedging Portfolios for Options with Discontinuous Payoffs
• Sensitivity Analysis for Simulations via Likelihood Ratios
• Likelihood ratio gradient estimation for stochastic recursions
• Applications of Malliavin calculus to Monte-Carlo methods in finance. II