Trading with propagators and constraints: applications to optimal execution and battery storage
Eduardo Abi Jaber, Nathan De Carvalho, Huy\^en Pham

TL;DR
This paper develops a comprehensive framework for optimal trading and storage management using propagator models, linear constraints, and stochastic algorithms, with applications to financial markets and battery storage systems.
Contribution
It introduces explicit solutions for optimal controls under constraints and proposes a stochastic Uzawa algorithm for numerical approximation, applicable to real-world trading and storage problems.
Findings
Explicit optimal control formulas derived for constrained trading.
Stochastic Uzawa algorithm effectively computes Lagrange multipliers.
Applications demonstrate practical effectiveness in finance and energy storage.
Abstract
Motivated by optimal execution with stochastic signals, market impact and constraints in financial markets, and optimal storage management in commodity markets, we formulate and solve an optimal trading problem with a general propagator model under linear functional inequality constraints. The optimal control is given explicitly in terms of the corresponding Lagrange multipliers and their conditional expectations, as a solution to a linear stochastic Fredholm equation. We propose a stochastic version of the Uzawa algorithm on the dual problem to construct the stochastic Lagrange multipliers numerically via a stochastic projected gradient ascent, combined with a least-squares Monte Carlo regression step to approximate their conditional expectations. We illustrate our findings on two different practical applications with stochastic signals: (i) an optimal execution problem with an…
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Taxonomy
TopicsOptimization and Search Problems
