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Decentralized Robust Portfolio Optimization Based on Cooperative-Competitive Multiagent Systems
IEEE Transactions on Cybernetics, 2021This article addresses decentralized robust portfolio optimization based on multiagent systems. Decentralized robust portfolio optimization is first formulated as two distributed minimax optimization problems in a Markowitz return-risk framework ...
Man-Fai Leung, Jun Wang, Duan Li
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Quantitative stock portfolio optimization by multi-task learning risk and return
Information FusionSelecting profitable stocks for investments is a challenging task. Recent research has made significant progress on stock ranking prediction to select top-ranked stocks for portfolio optimization.
Yu Ma +4 more
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ASYMPTOTICALLY OPTIMAL PORTFOLIOS
Mathematical Finance, 1992This paper extends to continuous time the concept of universal portfolio introduced by Cover (1991). Being a performance weighted average of constant rebalanced portfolios, the universal portfolio outperforms constant rebalanced and buy‐and‐hold portfolios exponentially over the long run.
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An Overview of Machine Learning for Portfolio Optimization
Journal of Portfolio ManagementThis article explores the application of machine learning in portfolio optimization, focusing on two primary areas: parameter estimation and optimization.
Yongjae Lee +3 more
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Optimizing the possession portfolio
Current Opinion in Psychology, 2022Most consumers live surrounded by physical goods, some of which are used often and others that are largely neglected. In this article, we introduce the concept of a "possession portfolio" which we define as an individual's holistic sense (vs. an objective listing) of the totality of the physical goods they own at a given point in time.
Kelly L. Haws, Rebecca Walker Reczek
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Factor-based portfolio optimization
Economics Letters, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jun Kyung Auh, Wonho Cho
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Cardinality-constrained portfolio selection via two-timescale duplex neurodynamic optimization
Neural Networks, 2022This paper addresses portfolio selection based on neurodynamic optimization. The portfolio selection problem is formulated as a biconvex optimization problem with a variable weight in the Markowitz risk-return framework.
Man-Fai Leung, Jun Wang, Hangjun Che
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Expert systems with applications, 2020
Recurrent reinforcement learning (RRL) techniques have been used to optimize asset trading systems and have achieved outstanding results. However, the majority of the previous work has been dedicated to systems with discrete action spaces. To address the
A. M. Aboussalah, Chi-Guhn Lee
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Recurrent reinforcement learning (RRL) techniques have been used to optimize asset trading systems and have achieved outstanding results. However, the majority of the previous work has been dedicated to systems with discrete action spaces. To address the
A. M. Aboussalah, Chi-Guhn Lee
semanticscholar +1 more source
Closed-form solutions for short-term sparse portfolio optimization
Optimization, 2020The short-term sparse portfolio optimization (SSPO) models are dedicated to constructing sparse portfolio in each short period. In this paper, we discuss some existing SSPO model and propose two realistic sparse optimization models via the -norm.
Ziyan Luo +3 more
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Multi-period portfolio optimization using coherent fuzzy numbers in a credibilistic environment
Expert systems with applications, 2020In this paper, we use an extension of fuzzy numbers, called coherent fuzzy numbers, to model asset returns and an investor’s perception of the stock market (pessimistic, optimistic, or neutral) simultaneously.
Pankaj Gupta +2 more
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