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<p>This editorial introduces a special issue of <i>Computational Economics</i> devoted to recent advances in computational approaches to financial markets and economic decision-making. The contributions collected in this issue illustrate how numerical methods, network analysis, advanced econometric techniques, machine learning, and data-driven modeling can be employed to address economically meaningful questions that are difficult to tackle using purely analytical approaches. The papers cover a broad range of topics, including financial integration and contagion, systemic risk and network dynamics, portfolio choice and life-cycle investment strategies, volatility modeling and high-frequency market behavior, sentiment analysis and textual data, digital advertising strategies, liquidity risk, and green technology adoption. Several contributions originated from presentations at the FMND Workshop held in Paris (<a href="http://www.fmnd.fr">www.fmnd.fr</a> ), which fostered interdisciplinary exchanges at the intersection of finance, mathematics, networks, and data science. Taken together, the papers in this special issue highlight the growing role of computational economics in understanding complex economic systems and point toward promising directions for future research.</p>

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Computational Approaches To Financial Markets, Risk, and Decision-Making

  • 期刊论文

  • 发表日期：

    2026年1月1日

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  • Fredj Jawadi

摘要

This editorial introduces a special issue of Computational Economics devoted to recent advances in computational approaches to financial markets and economic decision-making. The contributions collected in this issue illustrate how numerical methods, network analysis, advanced econometric techniques, machine learning, and data-driven modeling can be employed to address economically meaningful questions that are difficult to tackle using purely analytical approaches. The papers cover a broad range of topics, including financial integration and contagion, systemic risk and network dynamics, portfolio choice and life-cycle investment strategies, volatility modeling and high-frequency market behavior, sentiment analysis and textual data, digital advertising strategies, liquidity risk, and green technology adoption. Several contributions originated from presentations at the FMND Workshop held in Paris (www.fmnd.fr ), which fostered interdisciplinary exchanges at the intersection of finance, mathematics, networks, and data science. Taken together, the papers in this special issue highlight the growing role of computational economics in understanding complex economic systems and point toward promising directions for future research.