Arbeitspapier
Importance sampling for backward SDEs
In this paper we explain how the importance sampling technique can be generalized from simulating expectations to computing the initial value of backward SDEs with Lipschitz continuous driver. By means of a measure transformation we introduce a variance reduced version of the forward approximation scheme by Bender and Denk [4] for simulating backward SDEs. A fully implementable algorithm using the least-squares Monte Carlo approach is developed and its convergence is proved. The success of the generalized importance sampling is illustrated by numerical examples in the context of Asian option pricing under different interest rates for borrowing and lending.
- Language
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Englisch
- Bibliographic citation
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Series: CoFE Discussion Paper ; No. 08/11
- Classification
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Wirtschaft
- Subject
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BSDE
Numerics
Monte Carlo simulation
Variance reduction
- Event
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Geistige Schöpfung
- (who)
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Bendera, Christian
Moseler, Thilo
- Event
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Veröffentlichung
- (who)
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University of Konstanz, Center of Finance and Econometrics (CoFE)
- (where)
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Konstanz
- (when)
-
2008
- Handle
- Last update
-
10.03.2025, 11:46 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
- Bendera, Christian
- Moseler, Thilo
- University of Konstanz, Center of Finance and Econometrics (CoFE)
Time of origin
- 2008
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