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How should financial institutions hedge their balance sheets against interest rate risk when managing long-term assets and liabilities? We address this question by proposing a bond portfolio solution based on ambiguity-averse preferences,…

Risk Management · Quantitative Finance 2026-01-01 Tjeerd de Vries , Alexis Akira Toda

In this paper we propose a new methodology for solving an uncertain stochastic Markovian control problem in discrete time. We call the proposed methodology the adaptive robust control. We demonstrate that the uncertain control problem under…

Optimization and Control · Mathematics 2017-06-08 Tomasz R. Bielecki , Tao Chen , Igor Cialenco , Areski Cousin , Monique Jeanblanc

We consider a utility maximization problem for an investment-consumption portfolio when the current utility depends also on the wealth process. Such kind of problems arise, e.g., in portfolio optimization with random horizon or with random…

Portfolio Management · Quantitative Finance 2015-02-10 Salvatore Federico , Paul Gassiat , Fausto Gozzi

In this paper, we consider the asset-liability management under the mean-variance criterion. The financial market consists of a risk-free bond and a stock whose price process is modeled by a geometric Brownian motion. The liability of the…

Risk Management · Quantitative Finance 2013-05-01 Qian Zhao , Jiaqin Wei , Rongming Wang

We present a continuous-time portfolio selection framework that reflects goal-based investment principles and mental accounting behavior. In this framework, an investor with multiple investment goals constructs separate portfolios, each…

Portfolio Management · Quantitative Finance 2026-05-12 Erhan Bayraktar , Bingyan Han

We consider the problem of portfolio optimization in a simple incomplete market and under a general utility function. By working with the associated Hamilton-Jacobi-Bellman partial differential equation (HJB PDE), we obtain a closed-form…

Probability · Mathematics 2018-02-22 Rohini Kumar , Hussein Nasralah

Keeping risk under control is often more crucial than maximizing expected rewards in real-world decision-making situations, such as finance, robotics, autonomous driving, etc. The most natural choice of risk measures is variance, which…

Machine Learning · Computer Science 2023-03-09 Xiaoteng Ma , Shuai Ma , Li Xia , Qianchuan Zhao

We study the design of portfolios under a minimum risk criterion. The performance of the optimized portfolio relies on the accuracy of the estimated covariance matrix of the portfolio asset returns. For large portfolios, the number of…

Portfolio Management · Quantitative Finance 2016-01-20 Liusha Yang , Romain Couillet , Matthew R. McKay

In this paper we derive a novel characterization result for time-consistent stochastic control problems with higher-order moments, originally formulated by Wang et al. [SIAM J. Control. Optim., 63 (2025), 1560--1589], and newly explore many…

Optimization and Control · Mathematics 2026-03-19 Yike Wang , Jingzhen Liu , Jiaqin Wei

We study a robust portfolio optimization problem under model uncertainty for an investor with logarithmic or power utility. The uncertainty is specified by a set of possible L\'evy triplets; that is, possible instantaneous drift, volatility…

Mathematical Finance · Quantitative Finance 2016-03-23 Ariel Neufeld , Marcel Nutz

This paper studies the mean-variance optimal portfolio choice of an investor pre-committed to a deterministic investment policy in continuous time in a market with mean-reversion in the risk-free rate and the equity risk-premium. In the…

Mathematical Finance · Quantitative Finance 2024-03-07 Michael Preisel

We address the problem of combined stochastic and impulse control for a market maker operating in a limit order book. The problem is formulated as a Hamilton-Jacobi-Bellman quasi-variational inequality (HJBQVI). We propose an implicit…

Mathematical Finance · Quantitative Finance 2025-12-25 Alexey Meteykin

In this paper, we study the mean-variance portfolio selection problem under partial information with drift uncertainty. First we show that the market model is complete even in this case while the information is not complete and the drift is…

Portfolio Management · Quantitative Finance 2020-10-27 Jie Xiong , Zuo quan Xu , Jiayu Zheng

In this paper, we study a class of risk-sensitive mean-field stochastic differential games. We show that under appropriate regularity conditions, the mean-field value of the stochastic differential game with exponentiated integral cost…

Optimization and Control · Mathematics 2012-10-11 Hamidou Tembine , Quanyan Zhu , Tamer Basar

In this paper, we study the robust optimal investment and risk control problem for an insurer who owns the insider information about the financial market and the insurance market under model uncertainty. Both financial risky asset process…

Numerical Analysis · Mathematics 2022-07-15 Chao Yu , Yuhan Cheng , Yilun Song

To investigate a time-consistent optimal strategy for the continuous time mean-variance model, we develop a new method to establish the Bellman principle. Based on this new method, we obtain a time-consistent dynamic optimal strategy that…

Portfolio Management · Quantitative Finance 2020-07-24 Shuzhen Yang

We consider continuous-time mean-variance portfolio selection with bankruptcy prohibition under convex cone portfolio constraints. This is a long-standing and difficult problem not only because of its theoretical significance, but also for…

Portfolio Management · Quantitative Finance 2015-07-27 Xun Li , Zuo Quan Xu

We develop a robust linear-quadratic mean-field control framework for systemic risk under model uncertainty, in which a central bank jointly optimizes interest rate policy and supervisory monitoring intensity against adversarial…

Optimization and Control · Mathematics 2025-12-05 Toshiaki Yamanaka

This paper compares the optimal investment problems based on monotone mean-variance (MMV) and mean-variance (MV) preferences in the L\'{e}vy market with an untradable stochastic factor. It is an open question proposed by Trybu{\l}a and…

Optimization and Control · Mathematics 2023-11-08 Yuchen Li , Zongxia Liang , Shunzhi Pang

We consider a distributionally robust formulation of stochastic optimization problems arising in statistical learning, where robustness is with respect to uncertainty in the underlying data distribution. Our formulation builds on…

Optimization and Control · Mathematics 2021-06-09 Mert Gürbüzbalaban , Andrzej Ruszczyński , Landi Zhu