Mathematics – Probability
Scientific paper
2007-10-19
Annals of Applied Probability 2007, Vol. 17, No. 4, 1138-1171
Mathematics
Probability
Published in at http://dx.doi.org/10.1214/105051607000000249 the Annals of Applied Probability (http://www.imstat.org/aap/) by
Scientific paper
10.1214/105051607000000249
Under the assumption of no-arbitrage, the pricing of American and Bermudan options can be casted into optimal stopping problems. We propose a new adaptive simulation based algorithm for the numerical solution of optimal stopping problems in discrete time. Our approach is to recursively compute the so-called continuation values. They are defined as regression functions of the cash flow, which would occur over a series of subsequent time periods, if the approximated optimal exercise strategy is applied. We use nonparametric least squares regression estimates to approximate the continuation values from a set of sample paths which we simulate from the underlying stochastic process. The parameters of the regression estimates and the regression problems are chosen in a data-dependent manner. We present results concerning the consistency and rate of convergence of the new algorithm. Finally, we illustrate its performance by pricing high-dimensional Bermudan basket options with strangle-spread payoff based on the average of the underlying assets.
Egloff Daniel
Kohler Michael
Todorovic Nebojsa
No associations
LandOfFree
A dynamic look-ahead Monte Carlo algorithm for pricing Bermudan options 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 A dynamic look-ahead Monte Carlo algorithm for pricing Bermudan options, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A dynamic look-ahead Monte Carlo algorithm for pricing Bermudan options will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-708398