Evaluation of machine and deep learning models for utility mining-based stock market price predictions
- Title
- Evaluation of machine and deep learning models for utility mining-based stock market price predictions
- Creator
- Rajeshwari G.M.; Manasa N.; Rajimol K.P.; Naidu K.; Samal A.; Garg N.
- Description
- Considering the extreme volatility of stock market returns and hazards, accurate price prediction has attracted the attention of both financial institutions and regulatory bodies. Stocks, due to their historically strong returns, have long been considered by investors to be an excellent asset allocation strategy. Predicting stock prices has never ceased being a hot topic of study. Many early-day economists sought to foretell future stock values. In subsequent years, as computer technology has advanced rapidly and mathematical theory has been extensively studied, it has been shown that mathematical models, like the time series model, may be very effective in predicting due to their simplicity and superiority. Over time, the time series model is put into practice. Over time, the horizon widened. Support vector machines and other ML techniques have challenges when applied to stock data because of its non-linearity. In subsequent years, thanks to advancements in deep learning, models like RNN and LSTM Neural Networks were able to analyze non-linear input, remember the sequence, and remember valuable information,Stock data forecasting cannot be done without it. 2024 Author(s).
- Source
- AIP Conference Proceedings, Vol-3214, No. 1
- Date
- 2024-01-01
- Publisher
- American Institute of Physics
- Subject
- Deep Learning; LSTM; Neural Networks; Non-Linearity; RNNM; Stock Market Prediction
- Coverage
- Rajeshwari G.M., Department of Studies in Business Administration, Pooja Bhagavat Memorial Mahajana Education Centre, Mysuru, India; Manasa N., Department of Business and Management, CHRIST (Deemed to Be University) Yeshwantpur Campus, Bangalore, India; Rajimol K.P., Department of MBA, Atria Institute of Technology, Karnataka, Bangalore, India; Naidu K., Department of Management Technology, Shri Ramdeobaba College of Engineering and Management, Nagpur, India; Samal A., Dept of MBA, Sri Venkateshwara College of Engineering, Karnataka, Bangalore, India; Garg N., Department of Studies in Business Administration, RIMS, Maharashtra, India
- Rights
- Restricted Access
- Relation
- ISSN: 0094243X
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Rajeshwari G.M.; Manasa N.; Rajimol K.P.; Naidu K.; Samal A.; Garg N., “Evaluation of machine and deep learning models for utility mining-based stock market price predictions,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/18933.