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Modeling Traders’ Behavior with Deep Learning and Machine Learning Methods: Evidence from BIST 100 Index
Joint Authors
Akyokus, Selim
Hasan, Afan
Kalıpsız, Oya
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-29
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract 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.
American Psychological Association (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
Modern Language Association (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
American Medical Association (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
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1144189