DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Electronics and Computer Science-IJAECS |
 Journal Home Volume Issue |
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Issue |
Volume-8,Issue-5 ( May, 2021 ) | |||||||||
Paper Title |
Stock Market Prediction using Machine Learning Algorithm | |||||||||
Author Name |
Bhuvan Garg, Chinmay Choudhary, Deepak Patel, Rina Mishra | |||||||||
Affilition |
B.Tech Computer Science Engineering, Department of Computer Science and Engineering, Medicaps University, Indore, India Assistant Professor, Department of Computer Science and Engineering, Medicaps University, Indore, India | |||||||||
Pages |
59-62 | |||||||||
Abstract |
The stock market is a very volatile market so predicting the exactness in it is very difficult. Research endeavors in improving the exactness of determining models are expanding since the most recent decade. Therefore we are using different machine learning algorithms to see the accuracy of the models. The purpose of this project is to explore the field of machine learning models and in the future take it to next level so that we can train our data accurately. . In this work, LSTM, Naive Forecast, RNN, and dense forecasting models have been utilized for predicting the stock price. The financial data Open, High, Low, and Close prices of stock Spy Etf is taken in time-series format. The models are evaluated using mean absolute error(MAE), the lower the value of MAE higher is the accuracy of the model. Keywords - LSTM, CNN, STOCK MARKET PREDICTION, MAE. | |||||||||
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