Algo-Trading Strategy for Intraweek Foreign Exchange Speculation Based on Random Forest and Probit Regression
Joint Authors
Chihab, Younes
Bousbaa, Zineb
Chihab, Marouane
Bencharef, Omar
Ziti, Soumia
Source
Applied Computational Intelligence and Soft Computing
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-08-27
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Information Technology and Computer Science
Abstract EN
In the Forex market, the price of the currencies increases and decreases rapidly based on many economic and political factors such as commercial balance, the growth index, the inflation rate, and the employment indicators.
Having a good strategy to buy and sell can make a profit from the above changes.
A successful strategy in Forex should take into consideration the relation between benefits and risks.
In this work, we propose an intraweek foreign exchange speculation strategy for currency markets based on a combination of technical indicators.
This system has a two-level decision and is composed of the Probit regression model and rules discovery using Random Forest.
There are two minimum requirements for a trading strategy: a rule to enter the market and a rule to exit it.
Our proposed system, to enter the currency market, should validate two conditions.
First, it should validate Random Forest access rules over the following week while in the second one the predicted value of the next day using Probit should be positive.
To exit the currency market just one negative warning from Probit or Random Forest is enough.
This system was used to develop dynamic portfolio trading systems.
The profitability of the model was examined for USD/(EUR, JYN, BRP) variation within the period from January 2014 to January 2016.
The proposed system allows improving the prediction accuracy.
This indicates a good prediction of the behavior market and it helps to identify the good times to enter it or to leave it.
American Psychological Association (APA)
Chihab, Younes& Bousbaa, Zineb& Chihab, Marouane& Bencharef, Omar& Ziti, Soumia. 2019. Algo-Trading Strategy for Intraweek Foreign Exchange Speculation Based on Random Forest and Probit Regression. Applied Computational Intelligence and Soft Computing،Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1117611
Modern Language Association (MLA)
Chihab, Younes…[et al.]. Algo-Trading Strategy for Intraweek Foreign Exchange Speculation Based on Random Forest and Probit Regression. Applied Computational Intelligence and Soft Computing No. 2019 (2019), pp.1-13.
https://search.emarefa.net/detail/BIM-1117611
American Medical Association (AMA)
Chihab, Younes& Bousbaa, Zineb& Chihab, Marouane& Bencharef, Omar& Ziti, Soumia. Algo-Trading Strategy for Intraweek Foreign Exchange Speculation Based on Random Forest and Probit Regression. Applied Computational Intelligence and Soft Computing. 2019. Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1117611
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1117611