Risks

This study investigates whether Corporate Social Responsibility Disclosure (CSRD) serves as a risk-mitigating or cost-inducing signal for firms’ market value in an emerging market. Utilising a panel dataset of 120 companies listed on the Tehran Stock Exchange (2015–2023) and employing content analysis alongside panel regression and System GMM models, we find that disclosure quality in social, employee, and environmental dimensions is positively associated with market value, while customer-related disclosure is not. The role of family ownership is nuanced: baseline specifications suggest no broad moderating influence, yet robust dynamic modelling reveals that family ownership significantly enhances the positive market valuation of environmental disclosure. The primary contribution is a nuanced, dimension-specific analysis of CSRD’s value relevance, challenging blanket assumptions about family firm behaviour and offering granular, methodologically informed insights for stakeholders in institutionally complex environments.

This study investigates credit unions’ expansion into non-core lending and its association with risk and financial resilience. Using US credit union call report data from 1994 to 2024, we measure the share of purchased loans, lease receivables, and loans held for sale in non-core lending. We document robust conditional, within-credit-union associations that point to a clear risk trade-off. Credit unions with higher non-core exposure grow faster in terms of loans and membership but exhibit weaker financial buffers, including lower net worth ratios and weaker economic solvency, alongside higher delinquency. Decomposition tests indicate that loans held for sale are most strongly associated with adverse buffer and asset quality patterns, while purchased loans and lease receivables display smaller and less uniform relationships. Scale interactions suggest that these associations are generally weaker for larger institutions for both membership and assets. Post-COVID estimates indicate that the baseline relationships are broadly stable, while the growth link is becoming stronger.

Cryptocurrencies play a central role in modern financial markets; however, geopolitical tensions and environmental concerns raise critical questions about their stability and informational efficiency. This study distinguishes between green cryptocurrencies (GCs), based on low-energy validation mechanisms, and dirty cryptocurrencies (DCs), which rely on energy-intensive protocols, to examine their behaviour under geopolitical stress. The objective of this paper is to assess how information dynamics, market resilience, and efficiency differ between GCs and DCs during periods of heightened geopolitical uncertainty, with particular focus on the Russia–Ukraine war. Using daily data from 28 April 2019 to 5 October 2023, we employ advanced information-theoretic measures, including mutual information, the rolling local nearest-neighbour entropy estimator (RLNNEE), and approximate entropy. The results show that DCs exhibit stronger information dominance than GCs, with this gap widening during the conflict. In contrast, GCs display lower but more stable mutual information, indicating greater informational resilience. Approximate entropy further reveals a decline in market complexity during the war period. Overall, the findings highlight the relevance of entropy-based tools for evaluating stability and risk in cryptocurrency markets facing geopolitical shocks.