Optimal Liquidation with Signals: the General Propagator Case, December 2022#
2. Affiliation:#
The first author’s affiliation is Ecole Polytechnique, CMAP.
3. Keywords:#
optimal portfolio liquidation, price impact, propagator models, predictive signals, Volterra stochastic control
4. Urls:#
arXiv:2211.00447v1 [q-fin.TR] 1 Nov 2022; Github:None
5. Summary:#
(1): The article aims to solve optimal liquidation problems in which the agent’s transactions create transient price impact driven by a Volterra-type propagator along with temporary price impact.
(2): The paper uses the infinite dimensional stochastic control approach to characterize the value function and derive analytic solutions to these equations which yields an explicit expression for the optimal trading strategy. The methods used in previous research are not comprehensive enough to balance transient price impact and temporary price impact. This article uses a new method to solve such issues. The approach is well motivated and well grounded in mathematical theory.
(3): The paper uses an infinite dimensional stochastic control approach to characterize the value function and derive analytic solutions to these equations which yields an explicit expression for the optimal trading strategy.
(4): The method can be used for a large class of price impact kernels with possible singularities, such as the power-law kernel, and the formulas derived can be implemented in a straightforward and efficient way. The performance supports their goals, and the methods are practical and useful for solving similar problems.
6. Conclusion:#
(1): The article provides a new method for solving optimal liquidation problems with price impact driven by Volterra-type propagators and temporary price impact. This work has significant theoretical and practical implications for solving similar problems in the field of finance.
(2): Innovation point: The paper proposes a new method to balance transient price impact and temporary price impact, which is well motivated and well grounded in mathematical theory. (3): Performance: The method can be used for a large class of price impact kernels with possible singularities, such as the power-law kernel, and the derived formulas can be implemented in a straightforward and efficient way. (4): Workload: The paper uses an infinite dimensional stochastic control approach to characterize the value function and derive analytic solutions to these equations, which may require a higher workload for those who are not familiar with this method.