A comparison on particle swarm optimization and genetic algorithm performances in deriving the efficient frontier of stocks portfolios based on a mean‐lower partial moment model-Reference-Cited by-同舟云学术

A comparison on particle swarm optimization and genetic algorithm performances in deriving the efficient frontier of stocks portfolios based on a mean‐lower partial moment model

Published:2020-09-16 Issue:4 Volume:26 Page:5659-5665
ISSN:1076-9307
Container-title:International Journal of Finance & Economics
language:en
Short-container-title:Int J Fin Econ

Author:

Mahmoudi Armin¹,Hashemi Leila²^ORCID,Jasemi Milad³,Pope James³

Affiliation:

1. Department of Industrial Engineering Azad University, Masjed Soleyman Branch Masjed Soleyman Iran

2. Department of Industrial Management Azad University, South Tehran Branch Tehran Iran

3. Department of Computer Informatics, Stephens College of Business University of Montevallo Montevallo Alabama USA

Publisher

Wiley

Subject

Economics and Econometrics,Finance,Accounting

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ijfe.2086

Reference30 articles.

1. Portfolio selection under strict uncertainty: A multi-criteria methodology and its application to the Frankfurt and Vienna Stock Exchanges

2. Portfolio Selection: A Compromise Programming Solution

3. A PSO and pattern search based memetic algorithm for SVMs parameters optimization

4. Optimal rules for ordering uncertain prospects

5. Safety-First, Stochastic Dominance, and Optimal Portfolio Choice

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