Algo-Trading Strategy for Intraweek Foreign Exchange Speculation Based on Random Forest and Probit Regression
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 chang...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Applied Computational Intelligence and Soft Computing |
| Online Access: | http://dx.doi.org/10.1155/2019/8342461 |
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| author | Younes Chihab Zineb Bousbaa Marouane Chihab Omar Bencharef Soumia Ziti |
| author_facet | Younes Chihab Zineb Bousbaa Marouane Chihab Omar Bencharef Soumia Ziti |
| author_sort | Younes Chihab |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-6bdcf03cc1754d72ba9115815272a55b |
| institution | Kabale University |
| issn | 1687-9724 1687-9732 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Computational Intelligence and Soft Computing |
| spelling | doaj-art-6bdcf03cc1754d72ba9115815272a55b2025-02-03T06:13:29ZengWileyApplied Computational Intelligence and Soft Computing1687-97241687-97322019-01-01201910.1155/2019/83424618342461Algo-Trading Strategy for Intraweek Foreign Exchange Speculation Based on Random Forest and Probit RegressionYounes Chihab0Zineb Bousbaa1Marouane Chihab2Omar Bencharef3Soumia Ziti4Department of Computer Sciences, Superior School of Technology, Ibn Toufail University, Kenitra, MoroccoDepartment of Computer Sciences, Faculty of Sciences and Techniques, Cadi Ayyad University, Marrakesh, MoroccoDepartment of Computer Sciences, Faculty of Sciences, Med V University, Rabat, MoroccoDepartment of Computer Sciences, Faculty of Sciences and Techniques, Cadi Ayyad University, Marrakesh, MoroccoDepartment of Computer Sciences, Faculty of Sciences, Med V University, Rabat, MoroccoIn 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.http://dx.doi.org/10.1155/2019/8342461 |
| spellingShingle | Younes Chihab Zineb Bousbaa Marouane Chihab Omar Bencharef Soumia Ziti Algo-Trading Strategy for Intraweek Foreign Exchange Speculation Based on Random Forest and Probit Regression Applied Computational Intelligence and Soft Computing |
| title | Algo-Trading Strategy for Intraweek Foreign Exchange Speculation Based on Random Forest and Probit Regression |
| title_full | Algo-Trading Strategy for Intraweek Foreign Exchange Speculation Based on Random Forest and Probit Regression |
| title_fullStr | Algo-Trading Strategy for Intraweek Foreign Exchange Speculation Based on Random Forest and Probit Regression |
| title_full_unstemmed | Algo-Trading Strategy for Intraweek Foreign Exchange Speculation Based on Random Forest and Probit Regression |
| title_short | Algo-Trading Strategy for Intraweek Foreign Exchange Speculation Based on Random Forest and Probit Regression |
| title_sort | algo trading strategy for intraweek foreign exchange speculation based on random forest and probit regression |
| url | http://dx.doi.org/10.1155/2019/8342461 |
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