Unmanned Artificial Intelligence-Based Financial Volatility Prediction in International Stock Market
- Title
- Unmanned Artificial Intelligence-Based Financial Volatility Prediction in International Stock Market
- Creator
- Rani T.; Vijayakumar L.; Chandirasekar B.; Geethanjali N.; Roja M.P.; Salunkhe H.A.
- Description
- This study investigates the capacity of autonomous artificial intelligence to predict the volatility of the worldwide stock market and proposes an innovative approach utilizing cutting-edge AI algorithms. A comprehensive literature review examines the evolution of financial prediction systems and the transformative effects of artificial intelligence in improving predictive capabilities. The AI system under consideration employs machine learning techniques more effectively than traditional methods for collecting and predicting financial volatility. The strategy heavily relies on automated data capture, preprocessing, and model training. A recall of 76%, an accuracy rate of 94%, a precision of 81%, an area under the curve of 0.87, and a sharp ratio of 1.25 comprise the model's impressive specifications. This research illuminates the prospective financial applications of artificial intelligence and provides a way to navigate the intricacies of international stock markets. 2024 IEEE.
- Source
- 2024 International Conference on Knowledge Engineering and Communication Systems, ICKECS 2024
- Date
- 2024-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Financial Volatility Prediction; International Stock Market; Machine Learning; Predictive Analytics; Unmanned Artificial Intelligence
- Coverage
- Rani T., SRM-IST, Fsh, Institute of Science and Technology, Department of Commerce, Chennai, Ramapuram, India; Vijayakumar L., Saveetha Institute of Medical and Technical Sciences, Saveetha College of Liberal Arts & Sciences, Department of Commerce, Tamil Nadu, Kanchipuram, India; Chandirasekar B., Saveetha Institute of Medical and Technical Sciences, Saveetha College of Liberal Arts & Sciences, Department of Commerce, Tamil Nadu, Kanchipuram, India; Geethanjali N., Psna College of Engineering and Technology, Department of Management Studies, Tamil Nadu, Dindigul, India; Roja M.P., Psna College of Engineering and Technology, Department of Management Studies, Tamil Nadu, Dindigul, India; Salunkhe H.A., Christ University (Deemed to Be University), Department School of Business and Management, Bangalore, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835035968-8
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Rani T.; Vijayakumar L.; Chandirasekar B.; Geethanjali N.; Roja M.P.; Salunkhe H.A., “Unmanned Artificial Intelligence-Based Financial Volatility Prediction in International Stock Market,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/19283.