The paper proves existence and uniqueness of optimal controls for indefinite LQ problems in jump-diffusion systems with random coefficients by constructing a generalized stochastic Riccati equation with jumps from an algebraic inverse flow, under uniform convexity.
and Peng, S.-G and Quenez, M
3 Pith papers cite this work. Polarity classification is still indexing.
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2026 3representative citing papers
Defines resilience evaluation D^ρ π as the L1-limit of scaled dynamic risk measure applied to process increments, and derives its dual representation as worst-case conditional expectation of an effective drift when ρ arises from BSDEs with Lipschitz or quadratic drivers.
Derives computable a posteriori error bounds for decoupled neural approximations of fully coupled FBSDEs that depend on terminal defect, pathwise residual, and control mismatch, backed by continuous-time stability estimates and numerical tests.
citing papers explorer
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Indefinite Stochastic LQ Optimal Control for Jump-Diffusion Systems with Random Coefficients
The paper proves existence and uniqueness of optimal controls for indefinite LQ problems in jump-diffusion systems with random coefficients by constructing a generalized stochastic Riccati equation with jumps from an algebraic inverse flow, under uniform convexity.
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Financial Resilience Evaluation: From Conditional Expectations to Dynamic Convex Risk Measures
Defines resilience evaluation D^ρ π as the L1-limit of scaled dynamic risk measure applied to process increments, and derives its dual representation as worst-case conditional expectation of an effective drift when ρ arises from BSDEs with Lipschitz or quadratic drivers.
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A Posteriori Error Analysis for Decoupled Neural Approximations of Fully Coupled FBSDEs with Control Mismatch
Derives computable a posteriori error bounds for decoupled neural approximations of fully coupled FBSDEs that depend on terminal defect, pathwise residual, and control mismatch, backed by continuous-time stability estimates and numerical tests.