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Sharp asymptotic lower bounds of the expected quadratic variation of discretization error in stochastic integration are given. The theory relies on inequalities for the kurtosis and skewness of a general random variable which are themselves…

Probability · Mathematics 2012-04-04 Masaaki Fukasawa

Submodularity is one of the most well-studied properties of problem classes in combinatorial optimization and many applications of machine learning and data mining, with strong implications for guaranteed optimization. In this thesis, we…

Machine Learning · Computer Science 2019-12-19 Yatao An Bian

This paper is concerned with the relationship between maximum principle and dynamic programming principle for risk-sensitive stochastic optimal control problems. Under the smooth assumption of the value function, relations among the adjoint…

Optimization and Control · Mathematics 2025-07-10 Huanqing Dong , Jingtao Shi

We consider a general formulation of the Principal-Agent problem with a lump-sum payment on a finite horizon, providing a systematic method for solving such problems. Our approach is the following: we first find the contract that is optimal…

Optimization and Control · Mathematics 2017-01-10 Jakša Cvitanić , Dylan Possamaï , Nizar Touzi

In this paper, we study the relationship between general maximum principle and dynamic programming principle for risk-sensitive stochastic optimal control problems, where the control domain is not necessarily convex. The original problem is…

Optimization and Control · Mathematics 2026-02-06 Huanqing Dong , Jingtao Shi

We consider the dynamic inventory problem with non-stationary demands. It has long been known that non-stationary (s, S) policies are optimal for this problem. However, finding optimal policy parameters remains a computational challenge as…

Optimization and Control · Mathematics 2020-07-20 Onur A. Kilic , S. Armagan Tarim

The dynamic portfolio optimization problem in finance frequently requires learning policies that adhere to various constraints, driven by investor preferences and risk. We motivate this problem of finding an allocation policy within a…

Artificial Intelligence · Computer Science 2020-12-23 Nymisha Bandi , Theja Tulabandhula

We consider the problem of maximizing the asymptotic growth rate of an investor under drift uncertainty in the setting of stochastic portfolio theory (SPT). As in the work of Kardaras and Robertson we take as inputs (i) a Markovian…

Mathematical Finance · Quantitative Finance 2021-08-12 David Itkin , Martin Larsson

We consider the problem of minimizing a convex function that is evolving according to unknown and possibly stochastic dynamics, which may depend jointly on time and on the decision variable itself. Such problems abound in the machine…

Optimization and Control · Mathematics 2023-05-30 Joshua Cutler , Dmitriy Drusvyatskiy , Zaid Harchaoui

In the portfolio multiobjective optimization framework, we propose to compare and choose, among all feasible asset portfolios of a given market, the one that maximizes the product of the distances between its values of risk and gain and…

Optimization and Control · Mathematics 2018-01-16 Francesco Cesarone , Lorenzo Lampariello , Simone Sagratella

We treat uncertain linear programming problems by utilizing the notion of weighted analytic centers and notions from the area of multi-criteria decision making. After introducing our approach, we develop interactive cutting-plane algorithms…

Optimization and Control · Mathematics 2018-05-21 Mehdi Karimi , Somayeh Moazeni , Levent Tuncel

This paper settles the existence question for a rather general class of convex optimal design problems with a volume constraint. In low dimensions, we prove the existence of an optimal configuration for general convex minimization problems…

Analysis of PDEs · Mathematics 2008-03-19 Eduardo V. Teixeira

In this paper we study a continuous-time stochastic linear quadratic control problem arising from mathematical finance. We model the asset dynamics with random market coefficients and portfolio strategies with convex constraints. Following…

Portfolio Management · Quantitative Finance 2017-05-24 Yusong Li , Harry Zheng

We study the portfolio selection problem of a long-run investor who is maximising the asymptotic growth rate of her expected utility. We show that, somewhat surprisingly, it is essentially not affected by introduction of a floor constraint…

Portfolio Management · Quantitative Finance 2013-05-30 Vladimir Cherny , Jan Obloj

We study the problem of optimal long term portfolio selection with a view to beat a benchmark. Two kinds of objectives are considered. One concerns the probability of outperforming the benchmark and seeks either to minimise the decay rate…

Probability · Mathematics 2017-12-04 Anatolii A. Puhalskii

We prove existence of radially symmetric solutions and validity of Euler-Lagrange necessary conditions for a class of variational problems such that neither direct methods nor indirect methods of Calculus of Variations apply. We obtain…

Optimization and Control · Mathematics 2019-07-25 Graziano Crasta , Annalisa Malusa

When the planning horizon is long, and the safe asset grows indefinitely, isoelastic portfolios are nearly optimal for investors who are close to isoelastic for high wealth, and not too risk averse for low wealth. We prove this result in a…

Portfolio Management · Quantitative Finance 2014-08-19 Paolo Guasoni , Johannes Muhle-Karbe , Hao Xing

We consider an optimal control problem arising in the context of economic theory of growth, on the lines of the works by Skiba (1978) and Askenazy - Le Van (1999). The economic framework of the model is intertemporal infinite horizon…

Optimization and Control · Mathematics 2014-09-05 Francesco Bartaloni

The effectiveness of utility-maximization techniques for portfolio management relies on our ability to estimate correctly the parameters of the dynamics of the underlying financial assets. In the setting of complete or incomplete financial…

Portfolio Management · Quantitative Finance 2008-12-10 Kasper Larsen , Gordan Zitkovic

Efficient methods to provide sub-optimal solutions to non-convex optimization problems with knowledge of the solution's sub-optimality would facilitate the widespread application of nonlinear optimal control algorithms. To that end,…

Optimization and Control · Mathematics 2023-04-10 Prithvi Akella , Aaron D. Ames