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. 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.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-03-25
DOI
https://doi.org/10.1051/itmconf/20257601007/pdf
Primary Topic
Stock Market Forecasting Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence in Financial Trading Predictive Models and Risk Management Strategies

Springer Link (Chiba Institute of Technology)
Stock Market Forecasting Methods
article

Artificial Intelligence in Financial Trading Predictive Models and Risk Management Strategies

article en

Abstract

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.

Springer Link (Chiba Institute of Technology)
Responsible consumption and production
Openalex Percentile: Top 30%
Stock Market Forecasting Methods
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