Close category search window
 

Multi-objective portfolio optimization and rebalancing using genetic algorithms with local search

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Soam, V. ; Sch. of Electr. Eng., Univ. of Tokyo, Tokyo, Japan ; Palafox, L. ; Iba, H.

The Portfolio Optimization problem is an example of a resource allocation problem with money as the resource to be allocated to assets. We first have to select the assets from a pool of them available in the market and then assign proper weights to them to maximize the return and minimize the risk associated with the Portfolio. In our work, we have introduced a new “greedy coordinate ascent mutation operator” and we have also included the trading volumes concept. We performed simulations with the past data of NASDAQ100 and DowJones30, concentrating mainly on the 2008 recession period. We also compared our results with the indices and the simple Genetic Algorithms approach.

Published in:
Evolutionary Computation (CEC), 2012 IEEE Congress on

Date of Conference: 10-15 June 2012

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.