Multilevel and Unbiased Monte Carlo Methods for Option Pricing


Project Description

This project will focus on the numerical estimation of financial options. The latter are contracts associated to financial objects such as stocks, which can be mathematically expressed as expectations with respect to a diffusion process. In this project, we will develop Monte Carlo methods which can provide numerical estimates of these option prices, which are not available in closed forms. In particular, the diffusion processes will have to be time-discretized and we will use advanced multilevel and unbiased techniques to provide estimates sometimes with no time-discretization error.​
Program - Applied Mathematics and Computer Science
Division - Computer, Electrical and Mathematical Sciences and Engineering
Field of Study - ​Computational and Numerical Methods

About the

Ajay Jasra

Professor, Applied Mathematics and Computational Science

Ajay Jasra
Professor Jasra's research interests are in the development, analysis and application of Monte Carlo algorithms for problems in Bayesian Statistics, uncertainty quantification and computational finance. He has several interests in applied probability, including Markov chains and interacting particle systems. He has also worked on stochastic control problems and filtering (data assimilation). 

Desired Project Deliverables

​Implementation and development of algorithms​