Finance & Economics Tracks > Track 12: Econophysics, Complexity, and Numerical Methods in Business Analytics

Track Chairs:

• Prof. Carlo Cattani, Engineering School (DEIM), University of Tuscia, Largo dell'Università, Viterbo, Italy
• Dr. Hana Rabbouch, Rabat Business School, Université Internationale de Rabat, Morocco

In today's rapidly evolving business landscape, the integration of cutting-edge quantitative methods has become imperative for informed decision-making and understanding complex financial systems. The "Econophysics, Complexity, and Numerical Methods in Business Analytics" track delves into the interdisciplinary realm where the principles of physics meet the intricacies of economics and finance. This track invites researchers, academics, and practitioners to explore the application of econophysics, complexity theory, and advanced numerical techniques in addressing real-world business challenges.

Potential topics include, but are not limited to:

• Complexity in Financial Markets: Exploring the dynamics of financial markets through complexity theory, agent-based modeling, and network analysis.
• Econophysics and Risk Management: Analyzing and mitigating risks in financial systems using tools and concepts from physics.
• Time Series Analysis and Predictive Modeling: Leveraging econophysics techniques and advanced numerical methods for time series forecasting, volatility modeling, and predictive analytics in business.
• Numerical Solutions for Complex Financial Models: Exploring innovative numerical techniques for solving complex financial equations and optimizing quantitative models.
• Networks and Financial Systems: Investigating the interconnectedness of financial institutions and systemic risk within complex networks, with a focus on numerical analysis.
• Behavioral Economics and Complex Decision-Making: Understanding human behavior and irrationality in economic and financial contexts, and its impact on complex decision-making, with numerical insights.
• Big Data and Quantitative Analytics: Harnessing big data, machine learning, artificial intelligence, and numerical methods to unravel complex economic and financial phenomena.
• Emerging Technologies in Finance: Exploring the role of emerging technologies like blockchain, cryptocurrency, and quantum computing in reshaping the financial landscape, with numerical implications.
• Numerical Methods for Regulatory Compliance: Examining the use of numerical techniques in compliance, regulations, and policy-making within the financial sector.
• Neutrosophic Statistics in Finance: Examining the incorporation of neutrosophic probability and statistics for advanced financial data analysis.

This track provides a platform for researchers and industry experts to exchange ideas, share insights, and foster collaborations at the intersection of econophysics, complexity science, numerical methods, and business analytics. We welcome contributions that utilize advanced numerical approaches to address contemporary challenges in finance and economics.