Algorithm of construction of Optimum Portfolio of stocks using Genetic Algorithm

Pankaj Sinha, Abhishek Chandwani and Tanmay Sinha

MPRA Paper from University Library of Munich, Germany

Abstract: The objective of this paper is to develop an algorithm to create an Optimum Portfolio from a large pool of stocks listed in a single market index SPX 500 Index: USA (for example) using Genetic Algorithm. The algorithm selects stocks on the basis of a priority index function designed on company fundamentals, and then genetically assigns optimum weights to the selected stocks by finding a genetically suitable combination of return and risk on the basis of historical data. The effect of genetic evolution on portfolio optimization has been demonstrated by developing a MATLAB code to implement the genetic application of reproduction, crossover and mutation operators. The effectiveness of the obtained portfolio has been successfully tested by running its performance over a six month holding period. It is found that genetic algorithm is successful in providing the optimum weights to stocks which were initially screened through a predetermined priority index function. The constructed portfolio beats the market for the considered holding period by a significant margin.

Keywords: Optimum Portfolio; Genetic Algorithm; Portfolio Construction; MATLAB (search for similar items in EconPapers)
JEL-codes: C6 C61 C63 G11 (search for similar items in EconPapers)
Date: 2013-07-10
New Economics Papers: this item is included in nep-cmp and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/48204/1/MPRA_paper_48204.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:48204

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().