Research Article | OPEN ACCESS
A Postulatory Study on Portfolio Optimization Algorithms: A Survey
Abijith Sankar, Renu Parameswaran, Sachin P. Shenoi and P.N. Kumar
Department of Computer Science and Engineering, Amrita School of Engineering, Amrita University, India
Research Journal of Applied Sciences, Engineering and Technology 2015 9:988-993
Received: May 20, 2015 | Accepted: June 19, 2015 | Published: November 25, 2015
Abstract
A stock represents the capital a company or corporation raises by issuing and subscribing shares. The stock market is a term used to describe the physical location where the buying and selling as well as overall market activity takes place. Companies issue stocks to acquire capital while investors buy them to own a portion of the company. Investors buy stocks with the belief that the company will grow continuously to raise the value of their shares. Every shareholder in a company will have a say on how the company runs. Making investment among various financial enterprises, industries and other categories is associated by a risk factor. Diversification is a technique that is used to mitigate the effects of such risks and creating a portfolio of stocks is the technique used in diversification. In this study, effort has been taken to describe three of the most important portfolio optimization algorithms viz. Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing.
Keywords:
Genetic algorithm, Markowitz model, particle swarm optimization, portfolio, portfolio management, portfolio optimization, simulated annealing,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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