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

Listed author(s):
  • Musshoff, Oliver
  • Hirschauer, Norbert
  • Palmer, Ken

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".

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File URL: http://purl.umn.edu/18823
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Paper provided by Humboldt University Berlin, Department Agricultural Economics in its series Working Paper Series with number 18823.

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Date of creation: 2002
Handle: RePEc:ags:huiawp:18823
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  1. Odening, Martin & Hinrichs, Jan, 2003. "Die Quantifizierung von Marktrisiken in der Tierproduktion mittels Value-at-Risk und Extreme-Value-Theory," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 52(2).
  2. Odening, Martin, 2000. "Der Optionswert von Sachinvestitionen - Theoretischer Hintergrund und Bewertungsmethoden," Working Paper Series 18828, Humboldt University Berlin, Department Agricultural Economics.
  3. Lissitsa, Alexej & Odening, Martin, 2001. "Effizienz und totale Faktor-produktivitat in der ukrainischen Landwirtschaft im Transformationsprozess," Working Paper Series 7391, Humboldt University Berlin, Department Agricultural Economics.
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