Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange

By Y. Kara, Melek Acar Boyacioglu, Ö. K. Baykan. 2011

886 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research, Signal Processing

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Citations in the corpus

Stock Market Prediction on High-Frequency Data Using Generative Adversarial Nets (2018, methodology): “These techniques include artificial neural networks (ANN) [21, 22], fuzzy logic (FL) [23], support vectormachines (SVM) [24, 25], particle swarm optimization (PSO) [26], and many others.”
Fintech Model: The Random Neural Network with Genetic Algorithm (2018, methodology): “et al [12] apply an Artificial Neural Network to predict the direction of Stock Market index movement.”
Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2015, methodology): “Here in this study, total ten technical indicators as employed in Kara et al. (2011) are used.”
Applications of deep learning in stock market prediction: recent progress (2020, neutral): “To deal with strong noise, Liu & Song (2017) uses weak ANNs to get some information without over-fitting and get better results by combining the weak results together using optimized bagging.”
Can Deep Learning Techniques Improve the Risk Adjusted Returns from Enhanced Indexing Investment Strategies (2017, background): “From this perspective the study undertaken by Kara et al. (2011) is of interest as it is conducted by reference to an emerging market stock market which, as noted by the authors, has experienced high levels of historical volatility and hence provides significant exposure to factors which have been o”
A Multiple-Criteria Approach for Forecasting Stock Price Direction : Nonlinear Probability Models with Application in S & P 500 Index (2016, background): “Numerous studies including [4-8] applied ANN in solving such problems.”
Integrating metaheuristics and Artificial Neural Networks for improved stock price prediction (2016, result): “It is observed that classical ANN model MLP gives ore reliable results than the other models used in this comparison. ara, Boyacioglu, and Baykan (2011) revealed that ANN works bet- er than Support Vector Machine in predicting the direction of stock rice movement in the ISE.”
Short-term stock market price trend prediction using a comprehensive deep learning system (2020, methodology): “in [17] also exploited ANN and SVM in predicting the movement of stock price index.”
A New Model for Stock Price Movements Prediction Using Deep Neural Network (2017, background): “Researchers applied many algorithms such as Moving average, Multiple Kernel Learning, Support Vector Machines and other techniques to analyze the stock market behavior.”
CNNpred: CNN-based stock market prediction using a diverse set of variables (2019, methodology): “In (Kara et al., 2011), ten technical indicators were passed to ANN and SVM in order to forecast120 directional movement of the Istanbul Stock Exchange (ISE) National 100 Index.”
Predicting Stock Market Trends Using Machine Learning and Deep Learning Algorithms Via Continuous and Binary Data; a Comparative Analysis (2020, methodology): “In the case of predicting stock market movement, there are several technical indicators and each of them has a speciﬁc ability to predict future trends of market; however, we choose ten technical indicators in this paper based on previous studies [24]–[26].”