2017 International Conference on Computer Science and Engineering (UBMK) 2017
DOI: 10.1109/ubmk.2017.8093449
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Predicting financial market in big data: Deep learning

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Cited by 20 publications
(7 citation statements)
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“…The classification performance obtained by ESA is evaluated to be higher than those obtained with the chi-square feature selection and logistic regression classifier. The approach in [20] focuses on stock market prediction by evaluating deep learning methods for classification purpose. In [21], the accuracy rate of 94.21% prediction is obtained by using LSTM deep learning method in Turkish texts.…”
Section: Literature Reviewmentioning
confidence: 99%
“…The classification performance obtained by ESA is evaluated to be higher than those obtained with the chi-square feature selection and logistic regression classifier. The approach in [20] focuses on stock market prediction by evaluating deep learning methods for classification purpose. In [21], the accuracy rate of 94.21% prediction is obtained by using LSTM deep learning method in Turkish texts.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Deep learning has also been incorporated in long-short-term memory neural networks for financial market predictions by Fischer and Krauss [42] where day returns are calculated for each day at defined stocks. Hasan et al [43] investigate how to apply hierarchical deep learning models for the problems in finance such as stock market prediction and classification; the deep learning models are based on neural networks, recurrent neural networks with big data finance datasets.…”
Section: Artificial Neural Networkmentioning
confidence: 99%
“…Machine learning has been applied to solve nonlinear models in continuous time in economics and finance by Duarte, V. [24] and forecasting the volatility of asset prices by Stefani, J. et al [25]. Deep Learning has also recently incorporated in long short term memory Neural Networks for financial market predictions by Fischer, T. et al [26] and Hasan, A. et al [27].…”
Section: Related Workmentioning
confidence: 99%