Arbeitspapier
Using chebyshev polynomials to approximate partial differential equations
This paper suggests a simple method based on a Chebyshev approximation at Chebyshev nodes to approximate partial differential equations. It consists in determining the value function by using a set of nodes and basis functions. We provide two examples: pricing a European option and determining the best policy for shutting down a machine. The suggested method is flexible, easy to programme and efficient. It is also applicable in other fields, providing efficient solutions to complex systems of partial differential equations.
- Language
-
Englisch
- Bibliographic citation
-
Series: CESifo Working Paper ; No. 2308
- Classification
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Wirtschaft
Computational Techniques; Simulation Modeling
Asset Pricing; Trading Volume; Bond Interest Rates
- Subject
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European options
Chebyshev polynomial approximation
Chebyshev nodes
Analysis
Optionspreistheorie
Theorie
- Event
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Geistige Schöpfung
- (who)
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Caporale, Guglielmo Maria
Cerrato, Mario
- Event
-
Veröffentlichung
- (who)
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Center for Economic Studies and ifo Institute (CESifo)
- (where)
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Munich
- (when)
-
2008
- Handle
- Last update
-
10.03.2025, 11:44 AM CET
Data provider
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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Caporale, Guglielmo Maria
- Cerrato, Mario
- Center for Economic Studies and ifo Institute (CESifo)
Time of origin
- 2008
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On Chebyshev polynomials of matrices
Operational matrices of Chebyshev polynomials for solving singular Volterra integral equations
An Extension of the Chebyshev Polynomials
On Chebyshev polynomials and their applications
Multivariate Chebyshev polynomials and FFT-like algorithms
Chebyshev polynomials and their some interesting applications
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Bivariate Chebyshev polynomials of the fifth kind for variable-order time-fractional partial integro-differential equations with weakly singular kernel
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