AI-Driven Financial Modeling Techniques: Transforming Investment Strategies
DOI:
https://doi.org/10.33423/jabe.v26i4.7181Keywords:
business, economics, AI, financial modeling, machine learning, deep learning, natural language processing, predictive analytics, risk management, portfolio optimizationAbstract
Artificial Intelligence (AI) has revolutionized financial modeling and investment strategies by introducing sophisticated algorithms and advanced data processing capabilities. This article delves into a variety of AI-driven financial modeling techniques, such as machine learning, natural language processing, and deep learning, providing detailed examples of their applications. These techniques are shown to significantly enhance predictive accuracy, risk management, portfolio optimization, and trading strategies. Through case studies and empirical evidence, the article highlights the transformative impact of AI on financial modeling. Additionally, it addresses the challenges in implementing AI-driven models, such as data quality issues, model interpretability, and regulatory concerns, and identifies future research opportunities to further advance the field. The comprehensive analysis provided offers a clear understanding of how AI is reshaping the financial industry, the potential benefits it brings, and the hurdles that must be overcome to fully harness its capabilities.
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