Bounded Recursive Stochastic Simulation - A Simple and Efficient Method for Pricing Complex American Type Options

This paper gives an overview of simulation based procedures, which have proved to be efficient in valuing American options and therefore real options. Many of them integrate sequential stochastic simulations in the backward recursive programming approach to determine the early-exercise frontier. They subsequently value the option by initiating a Monte-Carlo simulation from the valuation date of the option. It turns out that one approach (Grant et al., 1997) is especially simple. We are able to enhance its efficiency by stripping it of some time consuming but unnecessary simulation steps. Our simplified approach could be called "Bounded Recursive Stochastic Simulation".


Issue Date:
2002
Publication Type:
Working or Discussion Paper
PURL Identifier:
http://purl.umn.edu/18823
Total Pages:
30
Series Statement:
Working Paper
65




 Record created 2017-04-01, last modified 2017-08-24

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