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English(EN) Deep numerical schemes for systems of Ergodic BSDEs with applications to regime-switching forward utilities

新的深度学习方案解决了金融建模中复杂的Ergodic BSDEs问题

作者 PulseAugur 编辑部 · [3 个来源] ·

研究人员开发了新颖的基于神经网络的数值方案，用于求解复杂的Ergodic Backward Stochastic Differential Equations (eBSDEs)系统。这些方法旨在逼近状态切换随机因子模型中前向效用的最优策略。提出的技术包括一种局部加性深度学习方案和一种受Deep Galerkin Method (DGM)启发的算法，两者在数值实验中均显示出有希望的性能。 AI

影响 这些方法有望提升AI在复杂金融建模和策略逼近方面的能力。

排序理由 该集群包含一篇详细介绍求解复杂数学方程新数值方法的学术论文。

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 3 个来源。 我们如何撰写摘要 →

新的深度学习方案解决了金融建模中复杂的Ergodic BSDEs问题

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该集群包含一篇详细介绍求解复杂数学方程新数值方法的学术论文。
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报道来源 [3]

  1. arXiv cs.LG TIER_1 English(EN) · Guillaume Broux-Quemerais (LMM), Sarah Kaakai (LAGA), Anis Matoussi (LMM), Wissal Sabbagh (LMM) ·

    Ergodic BSDEs系统深度数值方案及其在择时前向效用中的应用

    arXiv:2606.24271v1 Announce Type: cross Abstract: 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 fra…

  2. arXiv cs.LG TIER_1 English(EN) · Wissal Sabbagh ·

    Ergodic BSDEs系统深度数值格式及其在择时前向效用中的应用

    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 …

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    Ergodic BSDEs系统深度数值格式及其在区间切换前向效用中的应用

    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 …

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