Stock Price Prediction Based on Machine Learning Algorithms (LSTM, CNN, RNN)

Stock Price Prediction Based on Machine Learning Algorithms (LSTM, CNN, RNN)

Kavya B.G1, Nishmitha.V2, Sindhu.H.M3, Tejashwini.B4, Prof Kavyashree K.R

1Student, Department of CSE, BNM Institute of technology

2Student, Department of CSE, BNM Institute of technology

3Student, Department of CSE, BNM Institute of technology

4Student, Department of CSE, BNM Institute of technology

5Assistant professor, Department of CSE, BNM Institute of technology

Abstract: Human intelligence is currently the dominant trend in stock market. This paper aims to build a model using Recurrent Neural Networks (RNN), Convolutional neural network (CNN) and especially Long-Short Term Memory model (LSTM) to predict future stock market values. The main objective of this paper is to analyze the performance of Machine learning algorithm in predicting stock price and analyze the accuracy obtained by various machine learning algorithms. Using this analysis in stock price prediction the result will be displayed in the form of table and graphical representation.
Keywords: Accuracy, CNN, LSTM, Machine learning, NIFTY50, Prediction, RNN, Stock Market, Time series.