Monte Carlo estimation of a joint density using Malliavin calculus, and application to American options
DOI10.1007/S10614-005-9005-3zbMath1137.91466OpenAlexW1963704621MaRDI QIDQ853652
Nizar Touzi, Amina Zeghal, Moez Mrad
Publication date: 17 November 2006
Published in: Computational Economics (Search for Journal in Brave)
Full work available at URL: https://basepub.dauphine.fr/handle/123456789/13602
Numerical methods (including Monte Carlo methods) (91G60) Monte Carlo methods (65C05) Stopping times; optimal stopping problems; gambling theory (60G40) Derivative securities (option pricing, hedging, etc.) (91G20) Stochastic calculus of variations and the Malliavin calculus (60H07)
Related Items (2)
Cites Work
- Unnamed Item
- Nonparametric statistics for stochastic processes. Estimation and prediction.
- Valuation of the early-exercise price for options using simulations and nonparametric regression
- Pricing American-style securities using simulation
- A quantization algorithm for solving multidimensional discrete-time optimal stopping problems
- On the Malliavin approach to Monte Carlo approximation of conditional expectations
- Applications of Malliavin calculus to Monte Carlo methods in finance
- Discrete-time approximation and Monte-Carlo simulation of backward stochastic differential equations
- Optimal stopping of Markov processes: Hilbert space theory, approximation algorithms, and an application to pricing high-dimensional financial derivatives
- Variance Reduction Methods for Simulation of Densities on Wiener Space
- A QUANTIZATION TREE METHOD FOR PRICING AND HEDGING MULTIDIMENSIONAL AMERICAN OPTIONS
- Applications of Malliavin calculus to Monte-Carlo methods in finance. II
This page was built for publication: Monte Carlo estimation of a joint density using Malliavin calculus, and application to American options
