An Actor-Critic Framework for Continuous-Time Jump-Diffusion Controls with Normalizing Flows

• URL: http://arxiv.org/abs/2604.05398v1
• Date: Tue, 07 Apr 2026 03:49:08 GMT
• Title: An Actor-Critic Framework for Continuous-Time Jump-Diffusion Controls with Normalizing Flows
• Abstract summary: Continuous-time control with time-inhomogeneous jump-diffusion dynamics is central in finance and economics.<n>We propose an actor-critic framework that serves as a mesh-free solver for entropy-regularized control problems and games with jumps.<n>We validate the method on time-inhomogeneous linear-quadratic control, Merton portfolio optimization, and a multi-agent portfolio game.
• Score: 10.996737071400004
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Continuous-time stochastic control with time-inhomogeneous jump-diffusion dynamics is central in finance and economics, but computing optimal policies is difficult under explicit time dependence, discontinuous shocks, and high dimensionality. We propose an actor-critic framework that serves as a mesh-free solver for entropy-regularized control problems and stochastic games with jumps. The approach is built on a time-inhomogeneous little q-function and an appropriate occupation measure, yielding a policy-gradient representation that accommodates time-dependent drift, volatility, and jump terms. To represent expressive stochastic policies in continuous-action spaces, we parameterize the actor using conditional normalizing flows, enabling flexible non-Gaussian policies while retaining exact likelihood evaluation for entropy regularization and policy optimization. We validate the method on time-inhomogeneous linear-quadratic control, Merton portfolio optimization, and a multi-agent portfolio game, using explicit solutions or high-accuracy benchmarks. Numerical results demonstrate stable learning under jump discontinuities, accurate approximation of optimal stochastic policies, and favorable scaling with respect to dimension and number of agents.

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