A new deep neural network algorithm for multiple stopping with applications in options pricing
In this paper, we propose a deep learning method to solve high-dimensional optimal multiple stopping problems. We represent the policies of multiple stopping problems by the composition of functions. Using the new representation, we approximate the optimal stopping policy recursively with simulation...
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| Veröffentlicht in: | Communications in nonlinear science & numerical simulation Jg. 117; S. 106881 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Elsevier B.V
01.02.2023
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| Abstract | In this paper, we propose a deep learning method to solve high-dimensional optimal multiple stopping problems. We represent the policies of multiple stopping problems by the composition of functions. Using the new representation, we approximate the optimal stopping policy recursively with simulation samples. We also derive lower and upper bounds and confidence intervals for the values. Finally, we apply the algorithm to the pricing of swing options, and it produces accurate results in high-dimensional problems.
•A deep learning-based algorithm for optimal multiple stopping problems is introduced.•Lower bounds and upper bounds for the optimal value are constructed.•Applications to high-dimensional swing options are considered. |
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| AbstractList | In this paper, we propose a deep learning method to solve high-dimensional optimal multiple stopping problems. We represent the policies of multiple stopping problems by the composition of functions. Using the new representation, we approximate the optimal stopping policy recursively with simulation samples. We also derive lower and upper bounds and confidence intervals for the values. Finally, we apply the algorithm to the pricing of swing options, and it produces accurate results in high-dimensional problems.
•A deep learning-based algorithm for optimal multiple stopping problems is introduced.•Lower bounds and upper bounds for the optimal value are constructed.•Applications to high-dimensional swing options are considered. |
| ArticleNumber | 106881 |
| Author | Li, Nan Han, Yuecai |
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| Keywords | Deep learning Multiple optimal stopping Swing options Monte Carlo |
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| Title | A new deep neural network algorithm for multiple stopping with applications in options pricing |
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