Convergence of the deep BSDE method for stochastic control problems formulated through the stochastic maximum principle
By Zhipeng Huang, Balint Negyesi, Cornelis W. Oosterlee
Rating
1460
Battle Count: 43
Relevance
8/10
The method can potentially be applied to various quantitative trading problems involving stochastic control, such as portfolio optimization and risk management.
Implementation Complexity
7/10
Requires understanding of stochastic control theory and implementation of deep learning algorithms for FBSDEs.
Reproducibility
4/5
The paper provides detailed algorithm descriptions and theoretical proofs. Code is mentioned to be available on GitHub.
About this paper
Methodology: Deep SMP-BSDE. Problem types: Stochastic Control, Optimization.
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