A Neural Network Monte Carlo Approximation for Expected Utility Theory
This paper proposes an approximation method to create an optimal continuous-time portfolio strategy based on a combination of neural networks and Monte Carlo, named NNMC. This work is motivated by the increasing complexity of continuous-time models and stylized facts reported in the literature. We w...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-07-01
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| Series: | Journal of Risk and Financial Management |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1911-8074/14/7/322 |