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Multi-objective Optimization of Technical Stock Market Indicators using GAs

by Magda B. Fayek, Hatem M. El-boghdadi, Sherin M. Omran
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 68 - Number 20
Year of Publication: 2013
Authors: Magda B. Fayek, Hatem M. El-boghdadi, Sherin M. Omran
10.5120/11698-7428

Magda B. Fayek, Hatem M. El-boghdadi, Sherin M. Omran . Multi-objective Optimization of Technical Stock Market Indicators using GAs. International Journal of Computer Applications. 68, 20 ( April 2013), 41-48. DOI=10.5120/11698-7428

@article{ 10.5120/11698-7428,
author = { Magda B. Fayek, Hatem M. El-boghdadi, Sherin M. Omran },
title = { Multi-objective Optimization of Technical Stock Market Indicators using GAs },
journal = { International Journal of Computer Applications },
issue_date = { April 2013 },
volume = { 68 },
number = { 20 },
month = { April },
year = { 2013 },
issn = { 0975-8887 },
pages = { 41-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume68/number20/11698-7428/ },
doi = { 10.5120/11698-7428 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:28:26.417436+05:30
%A Magda B. Fayek
%A Hatem M. El-boghdadi
%A Sherin M. Omran
%T Multi-objective Optimization of Technical Stock Market Indicators using GAs
%J International Journal of Computer Applications
%@ 0975-8887
%V 68
%N 20
%P 41-48
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Recent financial researches showed that technical indicators are useful tools for stock prediction. Technical indicators are used to generate trading signals (buy/sell) signals. The main problem of an indicator usage is to determine its appropriate parameters. In this paper a new GA based technique for optimizing the parameters of a collection of technical indicators over two objective functions Sharpe ratio and annual profit is proposed. The technique handles four indicators DEMAC (Double Exponential Moving Average Crossovers), RSI (Relative Strength Index), MACD (Moving Average Convergence Divergence), and MARSI (Moving Average RSI) indicators. The technique was tested on 30 years of historical data of DJIA (Dow Jones Industrial Average) stock index. Results showed that the optimized parameters obtained by the proposed technique improved the profits obtained by the indicators with their typical parameters, the Buy and Hold strategy and the random strategy.

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Index Terms

Computer Science
Information Sciences

Keywords

Technical Analysis Genetic Algorithms Parameter Optimization

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