Special Issue Submission Closed

Advancements in Finance and Investment through Machine Learning: Emerging Trends and Innovations

01About This Special Issue

The integration of machine learning (ML) into the fields of finance and investment is driving a new era of innovation, offering advanced techniques to improve asset selection, risk management, and decision-making processes. As financial markets become increasingly complex and data-driven, the adoption of machine learning models is reshaping traditional methodologies, enabling more accurate predictions, enhanced portfolio optimization, and better risk mitigation strategies.
The primary goal of this special issue is to showcase the latest advancements in applying machine learning to finance and investment. We invite contributions that explore the intersection of these disciplines, with a particular focus on how machine learning can optimize financial processes, predict market movements, and mitigate risks in real-time.
We welcome a variety of article types, including original research articles, review articles, and case studies, which contribute to the body of knowledge in finance and machine learning.
Through this special issue, we aim to provide interdisciplinary perspectives that deepen the understanding of how machine learning is transforming finance. We expect the contributions to advance both academic knowledge and practical applications, fostering innovation that will shape the future of global financial markets.

Potential topics include, but are not limited to:

  1. Machine learning in portfolio optimization
  2. Predictive modelling for asset preselection and financial forecasting
  3. AI-driven risk management and anomaly detection
  4. Algorithmic trading and decision-making
  5. Behavioral finance and sentiment analysis using machine learning
  6. Financial fraud detection using AI
  7. Impact of machine learning on global financial markets
  8. Impact of machine learning on global financial markets
  9. AI in Option Pricing

02Meet the Guest Editors

Our distinguished editors bring deep subject-matter expertise to curate high-quality research and ensure a rigorous peer-review process.

Lead Guest Editor

Priya Singh

Department of Mathematics, bioinformatics and Computer Applications, Maulana Azad National Institute of Technology, Bhopal, India

Guest Editor

Kanchan Rajwar

Statistical Quality Control and Operations Research Unit, Indian Statistical Institute, Hyderabad, India

Guest Editor

Dheeraj Kumar Dixit

Department of Computer Science and Engineering, Madhav Institute of Technology and Science Deemed university, Gwalior, India

Guest Editor

Dharmendra Dangi

Department of Information Technology, Indian Institute of Information Technology, Bhopal, India

Guest Editor

Akanksha Sharma

Department of Mathematics, bioinformatics and Computer Applications, Maulana Azad National Institute of Technology, Bhopal, India

Guest Editor

Bhavana Singh

Department of Mathematics, bioinformatics and Computer Applications, Maulana Azad National Institute of Technology, Bhopal, India

Guest Editor

Dharmendra Singh Rajput

School of Computer Science Engg. & Information Systems, Vellore Institute of Technology, Vellore, India