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Related papers: Relative Robust Portfolio Optimization

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We derive a closed form portfolio optimization rule for an investor who is diffident about mean return and volatility estimates, and has a CRRA utility. The novelty is that confidence is here represented using ellipsoidal uncertainty sets…

Portfolio Management · Quantitative Finance 2015-02-11 Sara Biagini , Mustafa Pinar

The optimal allocation of assets has been widely discussed with the theoretical analysis of risk measures, and pessimism is one of the most attractive approaches beyond the conventional optimal portfolio model. The $\alpha$-risk plays a…

Portfolio Management · Quantitative Finance 2024-05-20 Sungchul Hong , Jong-June Jeon

The question of optimal portfolio is addressed. The conventional Markowitz portfolio optimisation is discussed and the shortcomings due to non-Gaussian security returns are outlined. A method is proposed to minimise the likelihood of…

Physics and Society · Physics 2008-12-02 Robert Kitt , Jaan Kalda

Portfolio management problems are often divided into two types: active and passive, where the objective is to outperform and track a preselected benchmark, respectively. Here, we formulate and solve a dynamic asset allocation problem that…

Portfolio Management · Quantitative Finance 2018-07-31 Ali Al-Aradi , Sebastian Jaimungal

Financial portfolio management is one of the problems that are most frequently encountered in the investment industry. Nevertheless, it is not widely recognized that both Kelly Criterion and Risk Parity collapse into Mean Variance under…

Portfolio Management · Quantitative Finance 2019-06-11 Yoshiharu Sato

The sparse portfolio selection problem is one of the most famous and frequently-studied problems in the optimization and financial economics literatures. In a universe of risky assets, the goal is to construct a portfolio with maximal…

Optimization and Control · Mathematics 2022-02-22 Dimitris Bertsimas , Ryan Cory-Wright

We consider the class of single machine scheduling problems with the objective to minimize the weighted number of late jobs, under the assumption that completion due-dates are not known precisely at the time when decision-maker must provide…

Data Structures and Algorithms · Computer Science 2017-08-11 Maciej Drwal

The optimization of the variance supplemented by a budget constraint and an asymmetric $\ell_1$ regularizer is carried out analytically by the replica method borrowed from the theory of disordered systems. The asymmetric regularizer allows…

Portfolio Management · Quantitative Finance 2018-07-16 Imre Kondor , Gábor Papp , Fabio Caccioli

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

A common problem in the optimization of structures is the handling of uncertainties in the parameters. If the parameters appear in the constraints, the uncertainties can lead to an infinite number of constraints. Usually the constraints…

Optimization and Control · Mathematics 2012-05-01 Daniel P. Mohr , Ina Stein , Thomas Matzies , Christina A. Knapek

We analyze characteristics' joint predictive information through the lens of out-of-sample power utility functions. Linking weights to characteristics to form optimal portfolios suffers from estimation error which we mitigate by maximizing…

General Finance · Quantitative Finance 2024-02-05 Christopher G. Lamoureux , Huacheng Zhang

This paper studies a robust utility maximization problem for intractable claims under distributional ambiguity, where the distribution of the claim cannot be inferred from market information and its dependence with tradable assets is…

Optimization and Control · Mathematics 2026-04-17 Guohui Guan , Zongxia Liang , Xingjian Ma

This work studies the design of safe control policies for large-scale non-linear systems operating in uncertain environments. In such a case, the robust control framework is a principled approach to safety that aims to maximize the…

Systems and Control · Computer Science 2019-03-04 Edouard Leurent , Yann Blanco , Denis Efimov , Odalric-Ambrym Maillard

Traditional risk-adjusted returns, such as the Treynor, Sharpe, Sortino, and Information ratios, have been pivotal in portfolio asset allocation, focusing on minimizing risk while maximizing profit. Nevertheless, these metrics often fail to…

Portfolio Management · Quantitative Finance 2024-07-09 Ju-Hong Lee , Bayartsetseg Kalina , KwangTek Na

We propose a framework which generalizes "decision making with structured observations" by allowing robust (i.e. multivalued) models. In this framework, each model associates each decision with a convex set of probability distributions over…

Machine Learning · Computer Science 2025-06-27 Alexander Appel , Vanessa Kosoy

This paper considers a robust time-consistent mean-variance-skewness portfolio selection problem for an ambiguity-averse investor by taking into account wealth-dependent risk aversion and wealth-dependent skewness preference as well as…

Optimization and Control · Mathematics 2022-01-19 Jian-hao Kang , Nan-jing Huang , Zhihao Hu , Ben-Zhang Yang

While $\mathcal{H}_\infty$ methods can introduce robustness against worst-case perturbations, their nominal performance under conventional stochastic disturbances is often drastically reduced. Though this fundamental tradeoff between…

Systems and Control · Electrical Eng. & Systems 2023-05-29 Bruce D. Lee , Thomas T. C. K. Zhang , Hamed Hassani , Nikolai Matni

This paper studies robust forward investment and consumption preferences and optimal strategies for a risk-averse and ambiguity-averse agent in an incomplete financial market with drift and volatility uncertainties. We focus on non-zero…

Portfolio Management · Quantitative Finance 2025-09-17 Wing Fung Chong , Gechun Liang

In this paper the minimum spanning tree problem with uncertain edge costs is discussed. In order to model the uncertainty a discrete scenario set is specified and a robust framework is adopted to choose a solution. The min-max, min-max…

Computational Complexity · Computer Science 2010-04-19 Adam Kasperski , Pawel Zielinski

We consider a multi-stock continuous time incomplete market model with random coefficients. We study the investment problem in the class of strategies which do not use direct observations of the appreciation rates of the stocks, but rather…

Mathematical Finance · Quantitative Finance 2015-02-10 Nikolai Dokuchaev