Leveraging lstm neural networks for stock price prediction and trading strategy optimization in financial markets

HIGHLIGHTS

• What: The aim of support vector machines is to find an optimal decision boundary (hyperplane) that separates different categories of data points.
• Who: Chengru Ju and colleagues from the Columbia University, New York City, USA have published the Article: Leveraging LSTM Neural Networks for Stock Price Prediction and Trading Strategy Optimization in Financial Markets, in the : Proceedings of the 5th International Conference on Signal Processing and Machine Learning
• How: To optimize the model the authors used the commonly used adam optimizer which adaptively adjusts the learning rate to help accelerate the convergence process . . .
  

   

  

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