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We study a utility maximization problem in a financial market with a stochastic drift process, combining a worst-case approach with filtering techniques. Drift processes are difficult to estimate from asset prices, and at the same time…

Portfolio Management · Quantitative Finance 2021-11-04 Jörn Sass , Dorothee Westphal

For a long investment time horizon, it is preferable to rebalance the portfolio weights at intermediate times. This necessitates a multi-period market model in which portfolio optimization is usually done through dynamic programming.…

Portfolio Management · Quantitative Finance 2024-05-29 Shubhangi Sikaria , Rituparna Sen , Neelesh S. Upadhye

We develop a dual-control method for approximating investment strategies in incomplete environments that emerge from the presence of trading constraints. Convex duality enables the approximate technology to generate lower and upper bounds…

Mathematical Finance · Quantitative Finance 2019-10-29 Thijs Kamma , Antoon Pelsser

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

Optimization problems with rank constraints arise in many applications, including matrix regression, structured PCA, matrix completion and matrix decomposition problems. An attractive heuristic for solving such problems is to factorize the…

Statistics Theory · Mathematics 2015-09-11 Yudong Chen , Martin J. Wainwright

Turnpike theorems state that if an investor's utility is asymptotically equivalent to a power utility, then the optimal investment strategy converges to the CRRA strategy as the investment horizon tends to infinity. This paper aims to…

Portfolio Management · Quantitative Finance 2025-12-02 Hiroki Yamamichi

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

This study introduces a new analytical framework for quantifying multivariate risk measures. Using the Wishart process, which is a stochastic process with values in the space of positive definite matrices, we derive several conditional tail…

Risk Management · Quantitative Finance 2026-02-09 Jose Da Fonseca , Patrick Wong

The beneficial effects of treatments vary across individuals in most studies. Treatment heterogeneity motivates practitioners to search for the optimal policy based on personal characteristics. A long-standing common practice in policy…

Statistics Theory · Mathematics 2025-01-06 Xuqiao Li , Ying Yan

This article is an extended version of previous work of the authors [40, 41] on low-rank matrix estimation in the presence of constraints on the factors into which the matrix is factorized. Low-rank matrix factorization is one of the basic…

Statistics Theory · Mathematics 2017-08-28 Thibault Lesieur , Florent Krzakala , Lenka Zdeborová

We consider the problem of rational decision making in the presence of nonlinear constraints. By using tools borrowed from spin glass and random matrix theory, we focus on the portfolio optimisation problem. We show that the number of…

Disordered Systems and Neural Networks · Physics 2015-06-25 Stefano Galluccio , Jean-Philippe Bouchaud , Marc Potters

We account for time-varying parameters in the conditional expectile-based value at risk (EVaR) model. The EVaR downside risk is more sensitive to the magnitude of portfolio losses compared to the quantile-based value at risk (QVaR). Rather…

Statistical Finance · Quantitative Finance 2020-09-29 Xiu Xu , Andrija Mihoci , Wolfgang Karl Härdle

Accurate volatility forecasts are vital in modern finance for risk management, portfolio allocation, and strategic decision-making. However, existing methods face key limitations. Fully multivariate models, while comprehensive, are…

Statistical Finance · Quantitative Finance 2025-10-09 Duo Zhang , Jiayu Li , Junyi Mo , Elynn Chen

We consider a problem of optimal investment with intermediate consumption in the framework of an incomplete semimartingale model of a financial market. We show that a necessary and sufficient condition for the validity of key assertions of…

Portfolio Management · Quantitative Finance 2012-07-17 Oleksii Mostovyi

This paper presents a novel factor graph-based approach to solve the discrete-time finite-horizon Linear Quadratic Regulator problem subject to auxiliary linear equality constraints within and across time steps. We represent such optimal…

Robotics · Computer Science 2021-10-27 Shuo Yang , Gerry Chen , Yetong Zhang , Howie Choset , Frank Dellaert

Variable projection solves structured optimization problems by completely minimizing over a subset of the variables while iterating over the remaining variables. Over the last 30 years, the technique has been widely used, with empirical and…

Optimization and Control · Mathematics 2020-11-23 Tristan van Leeuwen , Aleksandr Aravkin

We propose a discrete-time econometric model that combines autoregressive filters with factor regressions to predict stock returns for portfolio optimisation purposes. In particular, we test both robust linear regressions and general…

Portfolio Management · Quantitative Finance 2024-01-02 Davide Lauria , W. Brent Lindquist , Svetlozar T. Rachev

In this paper, we study a stochastic optimal control problem with stochastic volatility. We prove the sufficient and necessary maximum principle for the proposed problem. Then we apply the results to solve an investment, consumption and…

Portfolio Management · Quantitative Finance 2018-08-15 Rodwell Kufakunesu , Calisto Guambe

We consider the terminal wealth utility maximization problem from the point of view of a portfolio manager who is paid by an incentive scheme, which is given as a convex function $g$ of the terminal wealth. The manager's own utility…

Portfolio Management · Quantitative Finance 2015-02-24 Maxim Bichuch , Stephan Sturm

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