Dynamic Search Space Particle Swarm Optimization Approach for Portfolio Optimization-Reference-Cited by-同舟云学术

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Dynamic Search Space Particle Swarm Optimization Approach for Portfolio Optimization

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2018 International Conference on Control and Computer Vision - ICCCV '18
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Author:

Feng Cong¹,Dong Yijiang²,Jiang Yuehan¹,Ran Maopeng¹

Affiliation:

1. School of Automation Science and, Electrical Engineering, Beihang University, Beijing, China

2. Beijing No 101 Middle School, Beijing, China

Publisher

ACM Press

Reference13 articles.

1. Markowitz, H. 1952. Portfolio selection. J. Financ. 7, 1 (Mar. 1952), 77--91.

2. Markowitz, H. 1959. Portfolio selection: efficient diversification of investments. Yale University Press.

3. Chen, W. 2015. Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem. Physica A. 429 (Jul. 2015), 125--139. DOI= https://doi.org/10.1016/j.physa.2015.02.060.

4. Qi, Y., Wang, Z., and Zhang, S. 2018. On analyzing and detecting multiple optimal of portfolio optimization. J. IND. MANAG. OPTIM. 14, 1, (Jan. 2018), 309--323. DOI=http://10.3934/jimo.2017048.

5. Kengatharan, L. 2017. CAPITAL INVESTMENT DECISION MAKING UNDER UNCERTAINTY: PERSPECTIVES OF AN EMERGING ECONOMY. Asia. Pac. J. Manag. 12, 2 (Dec. 2017), 1--22.

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1. A Comprehensive Survey on Portfolio Optimization, Stock Price and Trend Prediction Using Particle Swarm Optimization;Archives of Computational Methods in Engineering;2020-06-19

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