AI-Based Stock Market Prediction Framework Integrating IoT and Secure  Data Analytics

Ruchika Aggarwal, Shashank Kumar Srivastava and Bikrant Kumar

AI-Based Stock Market Prediction Framework Integrating IoT and Secure Data Analytics

Authors

Ruchika Aggarwal, Shashank Kumar Srivastava and Bikrant Kumar

Keywords:

Artificial Intelligence, Stock Market Prediction, Machine Learning, Financial Forecasting, LSTM, CNN, SVM, Ensemble Methods, Alternative Data Sources.

Abstract

Because of its dynamic character and intrinsic unpredictability, the stock market haslong piqued the interest of academics and investors alike, leading to the investigation ofsophisticated techniques to predict its movements. An extensive analysis of the use of artificial intelligence (AI) techniques for stock market prediction is presented

References

1. Asadi, S.; Hadavandi, E.; Mehmanpazir, F.; Nakhostin, M.M. Hybridization of evolutionaryLevenberg–Marquardt neural networks and data pre-processing for stock market prediction. Knowl.-Based Syst. 2012, 35, 245–258. [Google Scholar] [CrossRef]

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Published

2024-09-20

How to Cite

Ruchika Aggarwal, Shashank Kumar Srivastava and Bikrant Kumar. (2024). AI-Based Stock Market Prediction Framework Integrating IoT and Secure Data Analytics . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 8068–8076. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/5905