| Issue |
ITM Web Conf.
Volume 76, 2025
Harnessing Innovation for Sustainability in Computing and Engineering Solutions (ICSICE-2025)
|
|
|---|---|---|
| Article Number | 01007 | |
| Number of page(s) | 11 | |
| Section | Artificial Intelligence & Machine Learning | |
| DOI | https://doi.org/10.1051/itmconf/20257601007 | |
| Published online | 25 March 2025 | |
Artificial Intelligence in Financial Trading Predictive Models and Risk Management Strategies
1 Masters in Computer Applications, Alinma Esnad, Senior Business Consultant, Saudi Arabia
2 Assistant Professor, Department of Business Tashkent Metropolitan University, Tashkent, Uzbekistan
3 Assistant Professor, Department of Information Technology, CVR college of engineering, Hyderabad, Telangana, India
4 Assistant Professor, Department of Management, Brainware University, Kolkata, West Bengal, India
5 Professor, Department of ECE, J.J. College of Engineering and Technology, Tiruchirappalli, Tamil Nadu, India
6 Assistant Professor, Department of CSE, New Prince Shri Bhavani College of Engineering and Technology Chennai, Tamil Nadu, India
asif.shaikmca@gmail.com
Ziaamir70@gmail.com
bkirankumar5859@gmail.com
sandichandumba@gmail.com
sumithras@jjcet.ac.in
monishajothi@npsbcet.edu.in
Financial industry is a prime target for Artificial Intelligence (AI) driven solutions, opening up avenues of predictive. Nevertheless, hurdles around model transparency, compatibility with legacy financial systems, and the high bar of computational resources persist as major pieces of resistance. Therefore, this research is focused on establishing new AI-based models to tackle this problem in predictive models, risk management strategies in financial trading domain. Through computational efficiency enhancement, explainable AI methodologies application, along with Path-independent adaptation to diverse asset classes, this model aims to formulate richer, ambient, and inclusive AI environments for the benefit of sustainability. Moreover, the study examines hybrid AI-based models that integrate private and public blockchains to enhance transaction throughput, scalability, and data privacy. The idea is to make financial systems more stable, accessible, and effective while minimizing environmental impact via energy-efficient consensus mechanisms.
Key words: Block Chain Integration Data Privacy Explainable AI (XAI)Digital Assets (E.g. Portfolio Management) Hybrid AI models for risk management Sustainable finance (integration of ESG factors) Artificial Intelligence in Financial Trading Financial stability / Economy & Risk Management
© The Authors, published by EDP Sciences, 2025
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