Enhanced policy iteration for American options via scenario selection
Please always quote using this URN:urn:nbn:de:0296-matheon-3017
- In Kolodko & Schoenmakers (2004) and Bender & Schoenmakers (2004) a policy iteration was introduced which allows to achieve tight lower approximations of the price for early exercise options via a nested Monte-Carlo simulation in a Markovian setting. In this paper we enhance the algorithm by a scenario selection method. It is demonstrated by numerical examples that the scenario selection can significantly reduce the number of actually performed inner simulations, and thus can heavily speed up the method (up to factor 10 in some examples). Moreover, it is shown that the modified algorithm retains the desirable properties of the original one such as the monotone improvement property, termination after a finite number of iteration steps, and numerical stability.
Author: | Christian Bender, Anastasia Kolodko, John Schoenmakers |
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URN: | urn:nbn:de:0296-matheon-3017 |
Referee: | Peter Imkeller |
Document Type: | Preprint, Research Center Matheon |
Language: | English |
Date of first Publication: | 2005/02/12 |
Release Date: | 2005/01/12 |
Tag: | |
Institute: | Weierstraß-Institut für Angewandte Analysis und Stochastik (WIAS) |
MSC-Classification: | 60-XX PROBABILITY THEORY AND STOCHASTIC PROCESSES (For additional applications, see 11Kxx, 62-XX, 90-XX, 91-XX, 92-XX, 93-XX, 94-XX) / 60Gxx Stochastic processes / 60G40 Stopping times; optimal stopping problems; gambling theory [See also 62L15, 91A60] |
62-XX STATISTICS / 62Lxx Sequential methods / 62L15 Optimal stopping [See also 60G40, 91A60] | |
Preprint Number: | 293 |