On the rates of convergence of simulation based optimization algorithms for optimal stopping problems

Details On the rates of convergence of simulation based optimization algorithms for optimal stopping problems On the rates of convergence of simulation based optimization algorithms for optimal stopping problems

2009-09-19

arxiv.org/abs/0909.3570v1

Mathematics

Optimization and Control

Scientific paper

In this paper we study simulation based optimization algorithms for solving discrete time optimal stopping problems. This type of algorithms became popular among practioneers working in the area of quantitative finance. Using large deviation theory for the increments of empirical processes, we derive optimal convergence rates and show that they can not be improved in general. The rates derived provide a guide to the choice of the number of simulated paths needed in optimization step, which is crucial for the good performance of any simulation based optimization algorithm. Finally, we present a numerical example of solving optimal stopping problem arising in option pricing that illustrates our theoretical findings.

Affiliated with

Also associated with

No associations

Rating

On the rates of convergence of simulation based optimization algorithms for optimal stopping problems does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with On the rates of convergence of simulation based optimization algorithms for optimal stopping problems, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and On the rates of convergence of simulation based optimization algorithms for optimal stopping problems will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-485966