Artificial Intelligence in Financial Trading Predictive Models and Risk Management Strategies
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. T...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2025-01-01
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| Series: | ITM Web of Conferences |
| Subjects: | |
| Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2025/07/itmconf_icsice2025_01007.pdf |
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| Summary: | 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. |
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| ISSN: | 2271-2097 |