Journal article | Zeitschriftenartikel
Regression methods in pricing American and Bermudan options using consumption processes
Numerical algorithms for efficient pricing multidimensional discrete-time American and Bermudan options are constructed using regression methods and a new approach for computing upper bounds of the options' price. Using the sample space with payoffs at the optimal stopping times, we propose sequential estimates for continuation values, values of the consumption process, and stopping times on the sample paths. The approach allows constructing both lower and upper bounds for the price by Monte Carlo simulations. The algorithms are tested by pricing Bermudan max-calls and swaptions in the Libor market model.
- Extent
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Seite(n): 315-327
- Language
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Englisch
- Notes
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Status: Postprint; begutachtet (peer reviewed)
- Bibliographic citation
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Quantitative Finance, 9(3)
- Subject
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Wirtschaft
Wirtschaftsstatistik, Ökonometrie, Wirtschaftsinformatik
Finanzwirtschaft, Rechnungswesen
Theorieanwendung
- Event
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Geistige Schöpfung
- (who)
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Belomestny, Denis
Spokoiny, Vladimir
Milstein, Grigori
- Event
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Veröffentlichung
- (where)
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Vereinigtes Königreich
- (when)
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2009
- DOI
- URN
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urn:nbn:de:0168-ssoar-221242
- Rights
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GESIS - Leibniz-Institut für Sozialwissenschaften. Bibliothek Köln
- Last update
-
21.06.2024, 4:26 PM CEST
Data provider
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GESIS - Leibniz-Institut für Sozialwissenschaften. Bibliothek Köln. If you have any questions about the object, please contact the data provider.
Object type
- Zeitschriftenartikel
Associated
- Belomestny, Denis
- Spokoiny, Vladimir
- Milstein, Grigori
Time of origin
- 2009
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Pricing Bermudan options using regression
Self-similar Gaussian processes and the pricing of options
Pricing Bermudan options using regression: optimal rates of convergence for lower estimates
Pricing vulnerable options with variable default boundary under jump-diffusion processes
Strategic pricing of financial options
Pricing American options with Mellin transforms
Worst Case Pricing of Rainbow Options
Options-pricing formula with disaster risk