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Bachhav, Dr. Shreekala
- Machine Learning and Deep Learning as Predictive Forecasters of Capital Markets: A Systematic Literature Review
Abstract Views :247 |
PDF Views:91
Authors
Dr. Debashree Jana
1,
Dr. Shreekala Bachhav
2,
Dr. Chetan Eknath Khedkar
2,
Dr. Ashutosh Eknath Khedkar
3
Affiliations
1 Asst. Professor, Dr. D.Y.Patil School of Management, Lohegaon, Pune, IN
2 Associate Professor, Dr. D. Y. Patil School of Management, Lohegaon, Pune, IN
3 Asst. Professor, Dr. D. Y. Patil School of Management, Lohegaon, Pune, IN
1 Asst. Professor, Dr. D.Y.Patil School of Management, Lohegaon, Pune, IN
2 Associate Professor, Dr. D. Y. Patil School of Management, Lohegaon, Pune, IN
3 Asst. Professor, Dr. D. Y. Patil School of Management, Lohegaon, Pune, IN
Source
IBMRD's Journal of Management & Research, Vol 11, No 2 (2022), Pagination: 117-124Abstract
As the sun dips across the horizon, the stock exchange closes the bell, marking the closure of the day for traders and analyst to think and speculate the next day stock trends. The financial time series are old fashioned though a base line for all prediction methods. However there is a need to understand the prediction accuracy and capital market volatility augmented by fluctuations. The researchers carried out a systematic literature review to unleash the instruments that play the role of predictors in capital market today. It was found after assessment of the high impact research papers that Machine learning and Deep learning are major technological areas that is aiding the capital market predictions and behavioral analysis. with multiple techniques within to support prediction algorithms and clustering techniques for data analysis to support, this study summarizes the most five common set out the complete list of algorithm and techniques used.Keywords
Capital Market Predictions, Data Science, Deep Learning, , Machine Learning, Prediction AlgorithmsFull Text
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