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Related papers: Optimal Payoffs under State-dependent Preferences

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This paper studies the robust portfolio selection problem under a state-dependent confidence set. The investor invests in a financial market with a risk-free asset and a risky asset. The ambiguity-averse investor faces uncertainty over the…

Optimization and Control · Mathematics 2024-10-01 Guohui Guan , Yuting Jia , Zongxia Liang

This paper studies an optimal investing problem for a retiree facing longevity risk and living standard risk. We formulate the investing problem as a portfolio choice problem under a time-varying risk capacity constraint. We derive the…

Portfolio Management · Quantitative Finance 2022-02-16 Weidong Tian , Zimu Zhu

We revisit the problem of portfolio selection, where an investor maximizes utility subject to a risk constraint. Our framework is very general and accommodates a wide range of utility and risk functionals, including non-concave utilities…

Mathematical Finance · Quantitative Finance 2025-09-15 Leonardo Baggiani , Martin Herdegen , Nazem Khan

We consider "time-of-use" pricing as a technique for matching supply and demand of temporal resources with the goal of maximizing social welfare. Relevant examples include energy, computing resources on a cloud computing platform, and…

Computer Science and Game Theory · Computer Science 2017-04-11 Shuchi Chawla , Nikhil R. Devanur , Alexander E. Holroyd , Anna Karlin , James Martin , Balasubramanian Sivan

We propose an algorithm to calculate the exact solution for utility optimization problems on finite state spaces under a class of non-differentiable preferences. We prove that optimal strategies must lie on a discrete grid in the plane, and…

Pricing of Securities · Quantitative Finance 2018-10-01 Marcellino Gaudenzi , Michel Vellekoop

This paper presents a method for incorporating risk aversion into existing decision tree models used in economic evaluations. The method involves applying a probability weighting function based on rank dependent utility theory to reduced…

Theoretical Economics · Economics 2024-01-24 Jacob Smith

This paper considers a distributed stochastic optimization problem where the goal is to minimize the time average of a cost function subject to a set of constraints on the time averages of a related stochastic processes called penalties. We…

Information Theory · Computer Science 2016-10-06 B. N. Bharath , Vaishali P

We study the utility maximization problem for power utility random fields in a semimartingale financial market, with and without intermediate consumption. The notion of an opportunity process is introduced as a reduced form of the value…

Portfolio Management · Quantitative Finance 2010-11-03 Marcel Nutz

We study the Merton portfolio management problem within a complete market, non constant time discount rate and general utility framework. The non constant discount rate introduces time inconsistency which can be solved by introducing sub…

Portfolio Management · Quantitative Finance 2026-02-23 Oumar Mbodji

This paper is concerned with the maximum principle of stochastic optimal control problems, where the coefficients of the state equation and the cost functional are uncertain, and the system is generally under Markovian regime switching.…

Optimization and Control · Mathematics 2025-04-15 Tao Hao , Jiaqiang Wen , Jie Xiong

Many policies allocate harms or benefits that are uncertain in nature: they produce distributions over the population in which individuals have different probabilities of incurring harm or benefit. Comparing different policies thus involves…

Computers and Society · Computer Science 2021-03-11 Hoda Heidari , Solon Barocas , Jon Kleinberg , Karen Levy

We develop a complete analysis of a general entry-exit-scrapping model. In particular, we consider an investment project that operates within a random environment and yields a payoff rate that is a function of a stochastic economic…

Optimization and Control · Mathematics 2018-06-05 Mihail Zervos , Carlos Oliveira , Kate Duckworth

Most work in mechanism design assumes that buyers are risk neutral; some considers risk aversion arising due to a non-linear utility for money. Yet behavioral studies have established that real agents exhibit risk attitudes which cannot be…

Computer Science and Game Theory · Computer Science 2018-03-13 Shuchi Chawla , Kira Goldner , J. Benjamin Miller , Emmanouil Pountourakis

Analyzing decision problems under uncertainty commonly relies on idealizing assumptions about the describability of the world, with the most prominent examples being the closed world and the small world assumption. Most assumptions are…

Methodology · Statistics 2025-12-08 Christoph Jansen , Georg Schollmeyer , Thomas Augustin , Julian Rodemann

We consider a model where an agent has a repeated decision to make and wishes to maximize their total payoff. Payoffs are influenced by an action taken by the agent, but also an unknown state of the world that evolves over time. Before…

Computer Science and Game Theory · Computer Science 2021-01-20 Nicole Immorlica , Ian Kash , Brendan Lucier

This paper considers an optimal life insurance for a householder subject to mortality risk. The household receives a wage income continuously, which is terminated by unexpected (premature) loss of earning power or (planned and intended)…

Portfolio Management · Quantitative Finance 2011-05-03 Masahiko Egami , Hideki Iwaki

In this short note, we address two issues in the literature about modern tontines with bequest and utility maximisation: how to verify optimal controls and the decreasing allocation of funds in the tontine. We want to raise awareness in the…

Risk Management · Quantitative Finance 2025-01-16 Thomas Bernhardt

Modern portfolio theory(MPT) addresses the problem of determining the optimum allocation of investment resources among a set of candidate assets. In the original mean-variance approach of Markowitz, volatility is taken as a proxy for risk,…

Statistical Mechanics · Physics 2009-11-07 Morrel H. Cohen , Vincent D. Natoli

Selective labels are a common feature of consequential decision-making applications, referring to the lack of observed outcomes under one of the possible decisions. This paper reports work in progress on learning decision policies in the…

Machine Learning · Computer Science 2020-11-04 Dennis Wei

Markov decision processes (MDPs) are the defacto frame-work for sequential decision making in the presence ofstochastic uncertainty. A classical optimization criterion forMDPs is to maximize the expected discounted-sum pay-off, which…

Artificial Intelligence · Computer Science 2020-02-28 Tomas Brazdil , Krishnendu Chatterjee , Petr Novotny , Jiri Vahala
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