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Stock market prediction using deep learning algorithms

CAAI Transactions on Intelligence Technology 2023年第1期8卷 82-94页

作者： Somenath Mukherjee Bikash Sadhukhan nairita sarkar Debajyoti Roy Soumil De Nazrul Center of Social and Cultural Studies Kazi Nazrul UniversityAsansolIndia Department of Computer Science and Engineering Techno International New Town(Techno India College of Technology)KolkataIndia

The Stock Market is one of the most active research areas,and predicting its nature is an epic necessity *** the Stock Market is quite challenging,and it requires intensive study of the pattern of *** statistical models and artificially intelligent algorithms are needed to meet this challenge and arrive at an appropriate *** machine learning and deep learning algorithms can make a firm prediction with minimised error *** Artificial Neural Network(ANN)or Deep Feedforward Neural Network and the Convolutional Neural Network(CNN)are the two network models that have been used extensively to predict the stock market *** models have been used to predict upcoming days'data values from the last few days'data *** process keeps on repeating recursively as long as the dataset is *** endeavour has been taken to optimise this prediction using deep learning,and it has given substantial *** ANN model achieved an accuracy of 97.66%,whereas the CNN model achieved an accuracy of 98.92%.The CNN model used 2-D histograms generated out of the quantised dataset within a particular time frame,and prediction is made on that *** approach has not been implemented earlier for the analysis of such *** a case study,the model has been tested on the recent COVID-19 pandemic,which caused a sudden downfall of the stock *** results obtained from this study was decent enough as it produced an accuracy of 91%.

关键词： artificial neural network convolutional neural network nifty stock market

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