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Register a new userDeveloping an Optimal Financial Trading System Using Artificial Intelligent Techniques
تطوير نظام أمثليّ للتداول المالي باستخدام تقنيات الذكاء الصُنعي
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تم في هذا البحث دمج تقنيتين من تقنيات الذكاء الصنعي، و هما خوارزمية أمثلية مستعمرة النمل (ACO) و الخوارزمية الجينية (GA) لتحقيق أمثلية نظام التعلم المُعزّز العودي لتداول الأسهم. و يعتمد نظام التداول المقترح على خوارزمية أمثلية مستعمرة النمل و الخوارزمية الجينية لاختيار مجموعة مثالية من المؤشرات الأساسية و الفنية لتحسين أداء التداول.
In this paper, it has merged two techniques of the artificial intelligent, they are the ants colony optimization algorithm and the genetic algorithm, to The recurrent reinforcement learning trading system optimization. The proposed trading system is based on an ant colony optimization algorithm and the genetic algorithm to select an optimal group of technical indicators, and fundamental indicators.
References used
J. Moody and M. Saffell, “Reinforcement Learning for Trading Systems and Portfolios,” Kdd, pp. 279–283, 1998
G. Molina, “Stock Trading with Recurrent Reinforcement Learning ( RRL ),” Direct
J. Cumming and L. Dickens, “An Investigation into the Use of Reinforcement Learning Techniques within the Algorithmic Trading Domain,” 2015
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The Research Aims:
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