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".
|Date of creation:||2002|
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- 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).
- Odening, Martin & Hinrichs, Jan, 2002. "Die Quantifizierung von Marktrisiken in der Tierproduktion mittels Value-at-Risk und Extreme-Value-Theory," Working Paper Series 18826, Humboldt University Berlin, Department Agricultural Economics.
- Odening, Martin, 2000. "Der Optionswert von Sachinvestitionen - Theoretischer Hintergrund und Bewertungsmethoden," Working Paper Series 18828, Humboldt University Berlin, Department Agricultural Economics.
- 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. Full references (including those not matched with items on IDEAS)
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