Optimal control of stochastic Volterra integral equations with completely monotone kernels and stochastic differential equations on Hilbert spaces with unbounded control and diffusion operators
Gabriele Bolli, Filippo de Feo

TL;DR
This paper develops a novel framework for optimal control of stochastic Volterra integral equations with monotone kernels by reformulating them as SDEs on Hilbert spaces, enabling new regularity and control results.
Contribution
It introduces a Markovian lift approach to handle SVIEs with monotone kernels, analyzing their control via infinite-dimensional SDEs with unbounded operators, and establishes new smoothing properties.
Findings
Proves $BGamma$-smoothing property of the Ornstein-Uhlenbeck semigroup.
Establishes existence and uniqueness of solutions to the HJB equation.
Constructs optimal feedback controls for SVIEs with monotone kernels.
Abstract
The dynamic programming approach is one of the most powerful ones in optimal control. However, when dealing with optimal control problems of stochastic Volterra integral equations (SVIEs) with completely monotone kernels, deep mathematical difficulties arise and it is still not understood. These very classical problems have applications in most fields and have now become even more popular due to their applications in mathematical finance under rough volatility. In this article, we consider a class of optimal control problems of SVIEs with completely monotone kernels. Via a recent Markovian lift \cite{FGW2024}, the problem can be reformulated as an optimal control problem of stochastic differential equations (SDEs) on suitable Hilbert spaces, which due to the roughness of the kernel, presents a generator of an analytic semigroup and unbounded control and diffusion operators. This…
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Taxonomy
TopicsStochastic processes and financial applications · Stability and Controllability of Differential Equations · Risk and Portfolio Optimization
