CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

A Framework for Optimization of Technical Indicators Parameters for Forex (Foreign Exchange) based on Genetic Algorithm

by Tamer Sh. Mazen
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 25
Year of Publication: 2021
Authors: Tamer Sh. Mazen
10.5120/ijca2021921623

Tamer Sh. Mazen . A Framework for Optimization of Technical Indicators Parameters for Forex (Foreign Exchange) based on Genetic Algorithm. International Journal of Computer Applications. 183, 25 ( Sep 2021), 6-10. DOI=10.5120/ijca2021921623

@article{ 10.5120/ijca2021921623,
author = { Tamer Sh. Mazen },
title = { A Framework for Optimization of Technical Indicators Parameters for Forex (Foreign Exchange) based on Genetic Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2021 },
volume = { 183 },
number = { 25 },
month = { Sep },
year = { 2021 },
issn = { 0975-8887 },
pages = { 6-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume183/number25/32081-2021921623/ },
doi = { 10.5120/ijca2021921623 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:17:51.050869+05:30
%A Tamer Sh. Mazen
%T A Framework for Optimization of Technical Indicators Parameters for Forex (Foreign Exchange) based on Genetic Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 25
%P 6-10
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A new methodology to optimize the parameters of a collection technical analysis indicators of Forex (Foreign Exchange) based genetic algorithm (GA), over two objective functions Sharpe ratio and annual profit is presented in this study. 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. A proposed framework is tested on 20 years of historical data EURUSD. 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.

References
  1. S. Taylor., Modeling Financial Time Series, John Wiley & Sons , 1986.
  2. B. G. Malkiel, A Random Walk Down Wall street 6th Ed., W.W. Norton & Company, 1973.
  3. J. J. Murphy, TECHNICAL ANALYSIS OF THE GUIDE TO TRADING METHODS AND APPLICATIONS, New York Institute of Finance , 2009.
  4. A. W. Teeples, "An Evolutionary Approach to Optimization of Compound Stock Trading Indicators Used to Confirm Buy Signals," p. Paper 820, 2010.
  5. M. D. a. C. M. Jones., "The profitability of intra-day FX trading using technical indicators," University of Cambridge Judge Institute of Management Studies, 2010.
  6. C. A. a. H. I. Akinori Hirabayashi, "Optimization of the Trading Rule in Foreign Exchange using Genetic Algorithm," GECCO, 2009.
  7. S.-k. L. a. B.-R. Moon, "Finding attractive rules in stock markets using a modular genetic programming," GECCO, 2009.
  8. D. F. a. J. P.Fernandez, "Technical market indicators optimization using EA," GECCO, 2008.
  9. R. F. N. N. H. Adriano Simões, "An Innovative GA Optimized Investment Strategy based on a New Technical Indicator using Multiple MAS," in International Joint Conference on Computational Intelligence IJCCI 2010, Valencia,Spain, 2010.
  10. S. a. A. K. V.Kapoor, "Genetic Algorithm: An Application to Technical Trading System Design," International Journal of Computer Applications (0975 – 8887), vol. 36– No.5, 2011.
  11. V. C. L. a. Y. S. O. Devayan Mallick, "An Empirical Study of Genetic Programming Generated Trading Rules in Computerized Stock Trading Service System," IEEE proceedings, 2018.
  12. M. Becket, How the stock market works, London: Kogan Page Limited, 2014.
  13. M. Heitkoetter, The complete guide to day trading, USA: BookSurge, LLC, 2014.
  14. M. J. Pring, Technical Analysis for Short-Term Traders, Traders’ Library, 2000.
  15. S. a. A. K. V.Kapoor, "Genetic Algorithm: An Application to Technical Trading System Design," International Journal of Computer Applications, vol. 36, no. 5, 2011.
  16. C. M. Brown, Tecincal Analysis for Trading Profissional, USA: The McGraw Hill, 2012.
  17. M. C. Weigend, "Nonlinear Trading Models Through Sharpe Ratio Maximization," Leonard N. Stern School of Business, 2012.
  18. A. S. Weigend, "Decision Technologies for Financial Engineering," in Fourth International Conference on Neural Networks in the Capital Markets,NNCM, 2015.
  19. E. J. M. &. S. M. Alejandro, "A Technical Analysis Indicator Based on Fuzzy Logic," Electronic Notes on Theoretical Computer Science, vol. 292, pp. 27-37, 2013.
  20. P. S. Hussein Dourraa, "Investment using Technical Analysis and Fuzzy Logic. Fuzzy Sets and Systems," Fuzzy Sets and Systems, vol. 127, no. 2, pp. 221-240, 2012.
  21. J. F. Yates, Judgment and Decision Making, Prentice-Hall, Englewood Cliffs, NJ, 1990.
Index Terms

Computer Science
Information Sciences

Keywords

Forex Forex Indicators Technical Analysis Genetic Algorithms Parameter Optimization.

Powered by PhDFocusTM