This paper uses a statistical test based on entropy theory to propose a new way to distinguish between interdependence, contagion, and the decoupling hypotheses in the context of shock transmission and spillover. Applying the proposed approach, the three hypotheses are examined when measuring...

In this paper, we propose a novel optimization model for portfolio selection that integrates the classical mean-variance criterion with a second-order Tsallis entropy term. This approach enables a trade-off between expected return, risk, and diversification, extending Markowitz's theory to...

We study mean-field games of optimal stopping (OS-MFGs) and introduce an entropy-regularized framework to enable learning-based solution methods. By utilizing randomized stopping times, we reformulate the OS-MFG as a mean-field game of singular stochastic controls (SC-MFG) with entropy...

Public debt has increased steadily over the years, leaving many countries at risk of debt distress and even pushing some to default. This paper analyses the impact of sovereign default on post-default debtto-GDP ratios in 144 countries from 1980 to 2019. Applying the entropy balancing method, we...

This study firstly develops a novel Blue-ESG framework to evaluate marine sustainability across 80 countries over the period 2000-2023. The findings reveal that global Blue-ESG scores follow a "slow rise-fluctuant decline" trend, with a marked decline after 2017, primarily attributable to...

The purpose of this work is twofold: first, it aims to derive an exact analytical form of the Pareto index based on the already developed model of the economy as a scale-free network comprising a given amount of either wealth or income (total number of links, each link representing a non-zero...

The dynamic weighted cumulative residual (DWCR) entropy is regarded as an additional measure of uncertainty related to the residual lifetime function in several disciplines, including survival analysis and reliability. This article presents the DWCR formula based on Havarda and Charvat. This...

In this paper, a beta transform of multivariate normal datasets is obtained. The phi divergence measure, DΦ(F,G) between two distributions F and G is used to obtain a goodnessof-fit test to multivariate normality (MVN) based on the theoretical density function of the beta transformed random...

This study has two objectives: to identify sector-specific sustainability indicators from the literature and industry and to evaluate their importance through expert input.The analysis was conducted using the Fermatean fuzzy entropy and WASPAS method.The study found that, according to experts,...

The aim of this research is to thoroughly investigate the influence of the 2025 Donald Trump Presidential Inauguration on informational efficiency of the U.S. exchange-traded fund market in the context of political risk. The data set includes daily observations for twenty U.S. Exchange-Traded...

Background: The literature on measuring the complexity of production systems employs the graph and information theory. This study analyzes these systems and their coordination under varying states of control, with a focus on the probability of unfavorable events and their temporal...

This study addresses regional disparities and the dynamic evolution of China's science and technology finance integration (STFI) by constructing a composite index system using the entropy method. Recognizing the limitations of subjective weighting in traditional assessment frameworks, the...

To establish a comprehensive sustainable development framework that balances economic development and ESG levels, this paper proposes an EESG (Economics, Environment, Social, and Governance) evaluation system. This paper uses the entropy-weighted TOPSIS method to calculate and compare the EESG...

Financial industry executives are sincerely concerned about the potential effects of greenwashing on their organizations. The primary objective of this research is to investigate the impact of board features on greenwashing and the strategies that executives may develop to mitigate the effects...

We introduce a new coherent risk measure, the minimal-entropy risk measure, which is built on the minimal-entropy 𝜎-martingale measure - a concept inspired by the well-known minimal-entropy martingale measure used in option pricing. While the minimal-entropy martingale measure is commonly...

In contemporary times, energy sustainability and security have become essential economic concerns globally. Nonetheless, in addition to these concerns, inadequate governance inside a corporation within the energy industry may result in corruption and energy instability within the sector. The...

This study investigates systemic risk, return patterns, and diversification within the Johannesburg Stock Exchange (JSE) during the COVID-19 pandemic, utilizing data-centric approaches and the ARMA-GARCH vine copula-based conditional value-at-risk (CoVaR) model. By comparing three investment...

Multiple job holding (MJH) is increasingly frequent in industrialized countries. Individuals holding a secondary job add to their experience, skills, and networks. We study the long-run labor market outcomes after MJH and investigate whether career effects can be validated. We employ...

Multiple job holding (MJH) is increasingly frequent in industrialized countries. Individuals holding a secondary job add to their experience, skills, and networks. We study the long-run labor market outcomes after MJH and investigate whether career effects can be validated. We employ...

This study aims to determine the most important component of economic freedom and to rank the performance of countries using multiple criteria decision-making tools within the context of fuzzy set theory. To do so, we utilize a combination of fuzzy entropy weighting and fuzzy technique for order...

This paper develops a robust portfolio optimization framework that integrates Weighted Shannon Entropy (WSE) into the classical mean-variance paradigm, offering a distribution-free approach to diversification suited for volatile and heavy-tailed markets. While traditional variance-based models...

Predicting the currency exchange rate is crucial for financial agents, risk managers, and policymakers. Traditional approaches use publicly announced news on macroeconomic and financial variables as predictors of currency exchange. However, the rise of social media may have changed the source of...

Firm training is widely regarded as crucial for protecting workers from automation, yet there is a lack of empirical evidence to support this belief. Using internationally harmonized data from over 90,000 workers across 37 industrialized countries, we construct an individual-level measure of...

Financial institutions should prioritize the adoption of comprehensive Environmental, Social, and Corporate Governance (ESG) disclosure policies to improve their market reputation and decrease capital expenditures. The current study's research objective is to investigate the impact of both...