Quantitative Analysis and Mathematical Modeling in Economics and Financial Decision-Making

A special issue of Risks (ISSN 2227-9091).

Deadline for manuscript submissions: 31 March 2026 | Viewed by 577

Special Issue Editor


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Department of General Economy, Faculty of Economic Sciences, Ovidius University of Constanta, 900470 Constanta, Romania
Interests: econometrics; sustainability; education; ethical behavior; social sciences
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Special Issue Information

Dear Colleagues,

This Special Issue aims to highlight the essential role of mathematical tools and quantitative methods in understanding and optimizing decision-making processes in key areas of the contemporary economy. We welcome contributions that demonstrate the power of data-driven approaches and mathematical modeling in addressing major economic, financial, and societal challenges.

Topics of interest include, but are not limited to, the following:

  • Transition to a circular and sustainable economy;
  • The influence of religious and cultural values on economic and managerial decisions;
  • Strategic leadership and financial governance in key economic sectors;
  • Predictive analytics and risk modeling in financial systems;
  • Integration of digital technologies and artificial intelligence in economic analysis and planning;
  • The role of quantitative tools in evaluating economic performance and sustainability.

In a world increasingly shaped by digital transformation, exploring how quantitative analysis can support innovation, efficiency, and resilience in economic systems has become essential. We encourage interdisciplinary research that bridges mathematics, economics, data science, and social sciences to generate practical and impactful insights.

The main objectives of this Special Issue are as follows:

  • Promote interdisciplinary research applying mathematical and quantitative methods in economic and financial contexts;
  • Encourage the development of mathematical models to support strategic decision-making, risk assessment, and performance evaluation;
  • Explore how cultural, ethical, and technological dimensions can be integrated into economic modeling and financial analysis;
  • Foster innovative approaches to data science, big data analytics, and economic forecasting with societal relevance.

We invite submissions of theoretical articles, empirical studies, case analyses, and innovative methodological contributions from researchers working in fields such as those listed below:

  • Applied mathematics;
  • Economics and finance;
  • Data science and artificial intelligence;
  • Sustainability studies;
  • Risk management and financial modeling.

You may choose our Joint Special Issue in Mathematics.

Prof. Dr. Kamer-Ainur Aivaz
Guest Editor

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Keywords

  • quantitative analysis
  • mathematical modeling
  • decision-making
  • economics
  • finance
  • sustainable economy
  • circular economy
  • risk modeling
  • predictive models
  • data science
  • digital transformation
  • innovation in economics
  • performance evaluation
  • financial governance
  • religious and cultural values
  • big data
  • interdisciplinarity

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Published Papers (1 paper)

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Research

18 pages, 693 KB  
Article
Employee Stock Ownership Plans and Market Stability: A Longitudinal Analysis of Stock Price Crash Risk in China
by Mengfei Liu, Xiyuan Jiang and Xuyan Tong
Risks 2025, 13(12), 234; https://doi.org/10.3390/risks13120234 - 1 Dec 2025
Viewed by 349
Abstract
Reducing stock price crash risk is vital for capital market stability, particularly in emerging economies such as China. This study investigates whether Employee Stock Ownership Plans (ESOPs) can mitigate crash risk by analyzing panel data from A-share listed firms between 2014 and 2022. [...] Read more.
Reducing stock price crash risk is vital for capital market stability, particularly in emerging economies such as China. This study investigates whether Employee Stock Ownership Plans (ESOPs) can mitigate crash risk by analyzing panel data from A-share listed firms between 2014 and 2022. In contrast to prior research that has largely centered on managers and controlling shareholders, we highlight employees as active participants in corporate governance. Employing firm, year, and industry fixed effects, together with propensity score matching and instrumental variable techniques, we find robust evidence that ESOPs significantly reduce crash risk. Mediation analyses indicate that this effect operates through reduced agency costs both between managers and shareholders and between controlling and minority shareholders, as well as enhanced corporate productivity. Moderation tests further show that ESOPs are most effective when investor attention is high and when exit threats from non-controlling major shareholders are stronger. Heterogeneity analyses reveal that ESOPs exert greater influence in non-state-owned enterprises, in eastern regions, in firms with higher employee participation, and when shares are sourced from the secondary market. By extending the observation window to nearly a decade and deploying multiple robustness checks, this study provides one of the most comprehensive examinations of ESOPs and crash risk to date. It contributes to the literature by reframing employees as central actors in market stability and offers actionable insights for managers, investors, and regulators seeking to enhance corporate governance and reduce systemic risk. Full article
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