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Safety constraints and optimality are important, but sometimes conflicting criteria for controllers. Although these criteria are often solved separately with different tools to maintain formal guarantees, it is also common practice in…

Systems and Control · Electrical Eng. & Systems 2024-06-10 Pierre-François Massiani , Steve Heim , Friedrich Solowjow , Sebastian Trimpe

De Finetti's optimal reinsurance is a set of contracts, one for each risk in a portfolio, that caps the retained aggregate variance to a pre-specified level while minimizing total expected loss. The premiums are determined using the…

Optimization and Control · Mathematics 2026-03-03 N. D. Shyamalkumar , Tianrun Wang

We consider stopping problems in which a decision maker (DM) faces an unknown state of nature and decides sequentially whether to stop and take an irreversible action; pay a fee and obtain additional information; or wait without acquiring…

Theoretical Economics · Economics 2022-05-16 Ehud Lehrer , Tao Wang

The problem of reinforcement learning is considered where the environment or the model undergoes a change. An algorithm is proposed that an agent can apply in such a problem to achieve the optimal long-time discounted reward. The algorithm…

Systems and Control · Electrical Eng. & Systems 2023-04-25 Wuxia Chen , Taposh Banerjee , Jemin George , Carl Busart

Price-based revenue management is an important problem in operations management with many practical applications. The problem considers a retailer who sells a product (or multiple products) over $T$ consecutive time periods and is subject…

Optimization and Control · Mathematics 2021-01-01 Yining Wang , He Wang

This paper demonstrates a practical method for computing the solution of an expectation-constrained robust maximization problem with immediate applications to model-free no-arbitrage bounds and super-replication values for many financial…

Mathematical Finance · Quantitative Finance 2016-10-06 Christopher W. Miller

This paper studies a one-sector optimal growth model with i.i.d. productivity shocks that are allowed to be unbounded. The utility function is assumed to be non-negative and unbounded from above. The novel feature in our framework is that…

Economics · Quantitative Finance 2021-07-21 Nicole Bäuerle , Anna Jaśkiewicz

We consider the classical question of predicting binary sequences and study the {\em optimal} algorithms for obtaining the best possible regret and payoff functions for this problem. The question turns out to be also equivalent to the…

Machine Learning · Computer Science 2013-05-08 Alexandr Andoni , Rina Panigrahy

We study the optimal stopping problem of maximizing the variance of an unkilled linear diffusion. Especially, we demonstrate how the problem can be solved as a convex two-player zero-sum game, and reveal quite surprising application of game…

Probability · Mathematics 2020-03-25 Kamille Sofie Tågholt Gad , Pekka Matomäki

In this work, we address the optimal retirement problem in the presence of a stochastic wage, formulated as a free boundary problem. Specifically, we explore an incomplete market setting where the wage cannot be perfectly hedged through…

Mathematical Finance · Quantitative Finance 2025-03-04 Daniele Marazzina

A purely state-dependent cost function can be modified by introducing a control-dependent term rewarding submaximal control utilization. A moderation incentive is identically zero on the boundary of the admissible control region and…

Optimization and Control · Mathematics 2010-01-05 Debra Lewis

Considering a general nonlinear dissipative finite dimensional optimal control problem in fixed time horizon T , we establish a two-term asymptotic expansion of the value function as $T\rightarrow+\infty$. The dominating term is T times the…

Optimization and Control · Mathematics 2023-12-18 Veljko Askovic , Emmanuel Trélat , Hasnaa Zidani

This paper extends the classical dividend problem by incorporating a novel, path-dependent mechanism of firm default. In the traditional framework, ruin occurs when the surplus process first reaches zero. In contrast, default in our model…

Optimization and Control · Mathematics 2026-01-30 Andi Bodnariu , Nils Engler , Neofytos Rodosthenous

We study a robust utility maximization problem in the unbounded case with a general penalty term and information including jumps. We focus on time consistent penalties and we prove that there exists an optimal probability measure solution…

Optimization and Control · Mathematics 2022-12-07 Sarah Kaakai , Anis Matoussi , Achraf Tamtalini

We address the problem of making a managerial decision when the investment project is subsidized, which results in the resolution of an infinite-horizon optimal stopping problem of a switching diffusion driven by either an homogeneous or an…

Probability · Mathematics 2018-02-28 Carlos Oliveira , Nicolas Perkowski

In this paper, we study the portfolio optimization problem with general utility functions and when the return and volatility of underlying asset are slowly varying. An asymptotic optimal strategy is provided within a specific class of…

Mathematical Finance · Quantitative Finance 2016-11-08 Jean-Pierre Fouque , Ruimeng Hu

We introduce a new approach for the numerical pricing of American options. The main idea is to choose a finite number of suitable excessive functions (randomly) and to find the smallest majorant of the gain function in the span of these…

Computational Finance · Quantitative Finance 2013-10-17 Sören Christensen

The optimal stopping problem for the risk process with interests rates and when claims are covered immediately is considered. An insurance company receives premiums and pays out claims which have occured according to a renewal process and…

Probability · Mathematics 2008-12-23 Bogdan K. Muciek , Krzysztof J. Szajowski

We provide a characterization of an optimal stopping time for a class of finite horizon time-inconsistent optimal stopping problems (OSPs) of mean-field type, adapted to the Brownian filtration, including those related to mean-field…

Probability · Mathematics 2023-07-20 Boualem Djehiche , Mattia Martini

We develop a neural-network framework for multi-period risk--reward stochastic control problems with constrained two-step feedback policies that may be discontinuous in the state. We allow a broad class of objectives built on a…

Computational Finance · Quantitative Finance 2026-03-09 Chang Chen , Duy-Minh Dang
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