Stock Price Prediction Using Long Short Term Memory

  • D G Bhalke Department of Electronics and Telecommunication Engineering, Dr. D. Y. Patil Institute of Technology (DIT), Pune, India
  • Daideep Bhingarde Department of Electronics and Telecommunication Engineering, AISSMS College of Engineering, Pune, India
  • Siddhi Deshmukh Department of Electronics and Telecommunication Engineering, AISSMS College of Engineering, Pune, India
  • Digvijay Dhere Department of Electronics and Telecommunication Engineering, AISSMS College of Engineering, Pune, India
Keywords: Long Short Term Memory (LSTM), Sequential data, Machine Learning, Regression, Stock Market, Price Prediction.

Abstract

Stock market price prediction is difficult and complex task. Prediction in stock market is very complex and unstable Process. Stock Price are most of the time tend to follow patterns those are more or less regular in stock price curve. Machine Learning techniques use different predictive models and algorithms to predict and automate things to reduce human effort. This research paper focuses on the use of Long Short Term Memory (LSTM) to predict the future stock market company price of stock using each day closing price analysis. LSTM is very helpful in sequential data models. In this paper LSTM algorithm has been used to train and forecast the future stock prices.

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Published
2022-06-30