Deep numerical schemes for systems of Ergodic BSDEs with applications to regime-switching forward utilities
In this paper, we introduce two neural-network-based numerical schemes for solving systems of coupled ergodic Backward Stochastic Differential Equations (eBSDEs), motivated by the approximation of optimal strategies within the framework of forward utilities in a regime-switching stochastic factor model. Our approach builds on the representation of such models through systems of eBSDEs introduced in [HLT20]. We first establish a link between the solution of the system of ergodic BSDEs and that of an associated multidimensional BSDE with random terminal time, given by the hitting time of the positive recurrent stochastic factor. Building on this representation, we introduce a locally additi...
| Authors | Guillaume Broux-Quemerais, Sarah Kaakai, Anis Matoussi et al. |
|---|---|
| Primary category | math.NA |
| Published | 23 June 2026 |
| Last updated at source | 23 June 2026 |
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