Geometric BSDEs

Roger J. A. Laeven, Emanuela Rosazza Gianin, Marco Zullino
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引用次数: 0

Abstract

We introduce and develop the concepts of Geometric Backward Stochastic Differential Equations (GBSDEs, for short) and two-driver BSDEs. We demonstrate their natural suitability for modeling dynamic return risk measures. We characterize a broad spectrum of associated BSDEs with drivers exhibiting growth rates involving terms of the form $y|\ln(y)|+|z|^2/y$. We investigate the existence, regularity, uniqueness, and stability of solutions for these BSDEs and related two-driver BSDEs, considering both bounded and unbounded coefficients and terminal conditions. Furthermore, we present a GBSDE framework for representing the dynamics of (robust) $L^{p}$-norms and related risk measures.
几何 BSDE
我们介绍并发展了几何后向随机微分方程(简称 GBSDE)和双驱动 BSDE 的概念。我们证明了它们对动态回报风险度量建模的天然适用性。我们描述了一系列相关的 BSDE,其驱动因素的增长率涉及 $y|\ln(y)|+|z|^2/y$ 形式的项。我们研究了这些 BSDE 和相关双驱动 BSDE 的解的存在性、正则性、唯一性和稳定性,同时考虑了有界和无界系数及终点条件。此外,我们还提出了一个 GBSDE 框架,用于表示(鲁棒性)$L^{p}$ 准则和相关风险度量的动态。
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