Artificial Intelligence Based Method for Portfolio Selection

Daniel Gonzalez Cortes, Aida Jenny Cortes Jofre, Lilian San Martin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

The construction of an investment portfolio with tradable assets is one of the most studied problems in Finance and is done correctly through an optimal asset allocation. This research attempts to construct an efficient portfolio using an artificial intelligence approach using Particle Swarm Optimization (PSO) technique and the use of the genetic algorithm (GA) to find the best parameters setting for the PSO model. Historical price quotes for companies listed in the Dow Jones Industrial Average (DJIA) at different times frames were used to build a portfolio with the best Sharpe Ratio (SR) by maximizing the rate of return and minimizing risk.

Original languageEnglish
Title of host publication2018 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2018 - Proceedings
EditorsCarlos Andres Lozano-Garzon
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538681312
DOIs
Publication statusPublished - 21 Dec 2018
Event4th Innovation and Trends in Engineering Congress, CONIITI 2018 - Bogota, Colombia
Duration: 3 Oct 20185 Oct 2018

Publication series

Name2018 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2018 - Proceedings

Conference

Conference4th Innovation and Trends in Engineering Congress, CONIITI 2018
Country/TerritoryColombia
CityBogota
Period3/10/185/10/18

Keywords

  • asset allocation
  • efficient portfolio
  • Genetic Algorithm
  • Meta-Heuristics
  • Particle Swarm Optimization

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Education
  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems and Management
  • Civil and Structural Engineering
  • Control and Systems Engineering

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