Artificial Intelligence Applications in Financial Markets

Afef Rachid Amdouni (Editor)

ISBN: 9798337350325

Published: April 2026

Format: Hardcover

Language: English

Publisher: IGI Global Scientific Publishing

Description

Artificial intelligence is reshaping the landscape of financial markets, introducing new levels of efficiency, accuracy, and analytical power. Artificial Intelligence Applications in Financial Markets explores how AI technologies transform financial analysis and decision-making across both established and emerging markets. From algorithmic trading and deep learning-based stock price forecasting to portfolio optimization and the use of large language models in financial decision-making, this edited volume provides a comprehensive overview of AI's transformative role in modern finance. Researchers, practitioners, and students will find rigorous academic contributions spanning machine learning, ESG investing, digital wallets, and real-time trading systems — making it an essential reference for anyone navigating the intersection of AI and financial markets.

Key Features

• Covers the full spectrum of AI applications in finance: from stock trading algorithms to portfolio management and ESG compliance
• Includes contributions from international researchers across multiple disciplines
• Examines both established and emerging financial markets
• Addresses practical and theoretical aspects of AI in financial decision-making
• Explores cutting-edge topics including large language models (LLMs) and digital wallet classification

Coverage

Accounting and Finance, Algorithms, Artificial Intelligence, Digital Technology, Environmental, Social, and Governance (ESG), Financial Decision Systems, Financial Investment, Machine Learning, Portfolio Management, Predictive Models, Regulatory Compliance, Sustainable Development, Trade and Stock Markets

About the Editor

Afef Rachid Amdouni is an Assistant Professor of Finance in the Department of Finance, College of Business Administration at Taibah University, Saudi Arabia. Her research focuses on financial markets, corporate finance, and the application of artificial intelligence in economic and financial analysis.

Table of Contents

Chapter 1: Artificial Intelligence in Stock Market Trading: A Comprehensive Survey of Models and Applications — Sharneet Singh Jagirdar, Rajat Gupta, Pradeep Kumar Gupta, Navdeep Singh, Sanjeev Jain (pp. 1–30)

Chapter 2: Emerging Trends in AI-Driven Finance: A Topic Modeling Approach — Parul Singh (pp. 31–50)

Chapter 3: AI-Powered Forecasting and Portfolio Optimization: From Predictive Models to Strategic Investment Decisions — Muhammad Usman Tariq (pp. 51–78)

Chapter 4: AI in Portfolio Management and Asset Allocation — Optimizing Investment Strategies in Financial Markets: Transforming Investment With Intelligent Systems — Uju Judith Eziokwu (pp. 79–116)

Chapter 5: Stock Price Forecasting With Deep Learning Models Combined With Classical Statistical Techniques for Enhanced Accuracy — Pawan Kumar Badhan, Vivek Mittal, Priyanka Gupta, Davinder Singh, Ankush Sharma (pp. 117–132)

Chapter 6: Real-Time AI-Driven Stock Trading Systems: From Prediction to Execution — Sushil Bhardwaj, Sunaina Garg, Vinesh Kumari, Sunaina Mehta (pp. 133–164)

Chapter 7: Unveiling the Potential of AI in Volatile and Less Liquid Markets — Silvio Andrae (pp. 165–196)

Chapter 8: The Use of Large Language Models in Financial Forecasting: Analysis, Prediction, and Decision-Making — Silvio Andrae (pp. 197–226)

Chapter 9: Classifying Digital Wallet Apps by Transaction Intensity: A Machine Learning Approach — T. K. Sateesh Kumar, R. Vijaya Kumar, M. S. Annapoorna, Surjit Singha (pp. 227–256)

Why buy this book?

This volume is an essential acquisition for finance and economics libraries, business schools, and research institutions seeking a rigorous, up-to-date treatment of artificial intelligence in financial markets. It bridges the gap between theoretical AI research and its practical financial applications — making it relevant for both academic collections and professional reference shelves. All prices at CLNZ Books include worldwide shipping via international courier. Orders can be placed securely by credit card or PayPal.

Keywords

Artificial intelligence in finance, algorithmic trading, machine learning financial markets, portfolio optimization, stock price forecasting, deep learning finance, large language models, ESG investing, financial decision systems, fintech, quantitative finance, emerging markets

Target Audience

Financial professionals, portfolio managers, investment analysts, quantitative analysts, academic researchers in finance and economics, business school faculty, fintech professionals, economics and finance librarians, institutional investors

Genre

Academic reference book, edited volume, finance and technology, applied artificial intelligence, financial economics

Q&A

Where can I buy Artificial Intelligence Applications in Financial Markets?
You can purchase Artificial Intelligence Applications in Financial Markets edited by Afef Rachid Amdouni directly at CLNZ Books. The price includes worldwide shipping via international courier. Payment is accepted by credit card and PayPal.

How is AI being used in financial markets?
AI is applied across a wide range of financial tasks including algorithmic trading, stock price forecasting using deep learning models, portfolio optimization, risk assessment, regulatory compliance monitoring, and real-time trade execution. This book covers all of these applications in depth.

What machine learning models are used for stock price prediction?
Deep learning architectures such as LSTM networks, convolutional neural networks, and hybrid models combining classical statistical techniques with machine learning are among the most widely used approaches for stock price forecasting. Chapter 5 addresses this topic in detail.

Can large language models (LLMs) be used for financial forecasting?
Yes. Research in this book demonstrates that LLMs such as GPT-4 can assist in financial forecasting, analysis, and decision-making by processing and interpreting large volumes of financial text data. Chapter 8 provides an in-depth investigation of this application.

What is the role of AI in portfolio management?
AI enables dynamic, data-driven portfolio construction and asset allocation, optimizing investment strategies in real time. Chapters 3 and 4 explore AI-powered forecasting and portfolio management in detail, covering predictive models and strategic investment decision frameworks.

📘 View Financial Markets Catalogue 2026

📘 Learn more about shipping, delivery times, and returns, see our FAQ here