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Convolutional Neural Network(CNN/ConvNet) in Stock Price Movement Prediction

arXiv 2106.01920 ↗First posted 3 Jun 2021cs.NE cs.AI cs.CVcited by 0

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Abstract (arXiv)

With technological advancements and the exponential growth of data, we have been unfolding different capabilities of neural networks in different sectors. In this paper, I have tried to use a specific type of Neural Network known as Convolutional Neural Network(CNN/ConvNet) in the stock market. In other words, I have tried to construct and train a convolutional neural network on past stock prices data and then tried to predict the movement of stock price i.e. whether the stock price would rise or fall, in the coming time.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 10 of its 31 references that are in the map. First posted on arXiv 3 Jun 2021.

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10 of 31 references.

References · 10

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  3. 2014Convolutional Neural Networks for Sentence Classificationcited by 1,124
  4. 2014Caffe: Convolutional Architecture for Fast Feature Embeddingcited by 287
  5. 2017Deep Learning for Time-Series Analysiscited by 55
  6. 2015Equilibrated adaptive learning rates for non-convex optimizationcited by 42
  7. 2020Scheduled Restart Momentum for Accelerated Stochastic Gradient Descentcited by 24
  8. 2018Data Dropout: Optimizing Training Data for Convolutional Neural Networkscited by 23
  9. 2020Stock Price Prediction Using CNN and LSTM-Based Deep Learning Modelscited by 21
  10. 2018Evolutionary Stochastic Gradient Descent for Optimization of Deep Neural Networkscited by 13

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