Modeling Traders’ Behavior with Deep Learning and Machine Learning Methods: Evidence from BIST 100 Index
المؤلفون المشاركون
Akyokus, Selim
Hasan, Afan
Kalıpsız, Oya
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-16، 16ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-06-29
دولة النشر
مصر
عدد الصفحات
16
التخصصات الرئيسية
الملخص EN
Although the vast majority of fundamental analysts believe that technical analysts’ estimates and technical indicators used in these analyses are unresponsive, recent research has revealed that both professionals and individual traders are using technical indicators.
A correct estimate of the direction of the financial market is a very challenging activity, primarily due to the nonlinear nature of the financial time series.
Deep learning and machine learning methods on the other hand have achieved very successful results in many different areas where human beings are challenged.
In this study, technical indicators were integrated into the methods of deep learning and machine learning, and the behavior of the traders was modeled in order to increase the accuracy of forecasting of the financial market direction.
A set of technical indicators has been examined based on their application in technical analysis as input features to predict the oncoming (one-period-ahead) direction of Istanbul Stock Exchange (BIST100) national index.
To predict the direction of the index, Deep Neural Network (DNN), Support Vector Machine (SVM), Random Forest (RF), and Logistic Regression (LR) classification techniques are used.
The performance of these models is evaluated on the basis of various performance metrics such as confusion matrix, compound return, and max drawdown.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Hasan, Afan& Kalıpsız, Oya& Akyokus, Selim. 2020. Modeling Traders’ Behavior with Deep Learning and Machine Learning Methods: Evidence from BIST 100 Index. Complexity،Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1144189
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Hasan, Afan…[et al.]. Modeling Traders’ Behavior with Deep Learning and Machine Learning Methods: Evidence from BIST 100 Index. Complexity No. 2020 (2020), pp.1-16.
https://search.emarefa.net/detail/BIM-1144189
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Hasan, Afan& Kalıpsız, Oya& Akyokus, Selim. Modeling Traders’ Behavior with Deep Learning and Machine Learning Methods: Evidence from BIST 100 Index. Complexity. 2020. Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1144189
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1144189
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر