International Journal of Financial Studies

36 pages, 2684 KB

Open AccessArticle

The Mediating Role of Financial Decisions and the Moderating Role of Digital Transformation in the Relationship Between Managerial Characteristics and Financial Performance: Evidence from Vietnamese SMEs

by Minh Nguyen Ngoc, Cuong Nguyen Thanh and Ngoc Nguyen Van

Int. J. Financ. Stud. 2026, 14(7), 194; https://doi.org/10.3390/ijfs14070194 - 21 Jul 2026

Viewed by 778

Abstract

This study examines the mediating role of financial decisions and the moderating role of digital transformation in the relationship between managerial characteristics and financial performance among small and medium-sized enterprises (SMEs) in Vietnam. Grounded in Upper Echelons Theory, Behavioral Theory of the Firm, [...] Read more.

This study examines the mediating role of financial decisions and the moderating role of digital transformation in the relationship between managerial characteristics and financial performance among small and medium-sized enterprises (SMEs) in Vietnam. Grounded in Upper Echelons Theory, Behavioral Theory of the Firm, Resource-Based View, and corporate finance theories, the study conceptualizes financial decisions as a formative higher-order construct comprising capital structure, investment, and working capital management decisions. The empirical analysis is based on survey data collected from 510 SMEs in Khanh Hoa Province, Vietnam. The data were analyzed using partial least squares structural equation modeling (PLS-SEM), including mediation and moderation tests. The results show that managerial characteristics have a significant positive effect on financial decisions, which in turn positively affect financial performance. Financial decisions are found to partially mediate the relationship between managerial characteristics and firm performance. In addition, digital transformation positively moderates the relationship between financial decisions and financial performance, indicating that firms with higher levels of digital capability derive greater performance benefits from their financial decisions. Overall, the findings highlight the importance of managerial attributes and digital transformation in shaping financial outcomes through effective financial decision-making in SMEs. Full article

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17 pages, 275 KB

Open AccessArticle

How Do ESG and Innovation Strategies Affect Bank Performance and Risk Stability? Panel Evidence from Taiwan’s Banking Industry

by Ting-Kun Liu

Int. J. Financ. Stud. 2026, 14(7), 193; https://doi.org/10.3390/ijfs14070193 - 21 Jul 2026

Viewed by 414

Abstract

Sustainable finance, digital financial innovation, and green innovation have become central strategic pressures in banking, yet their joint effects on bank performance and risk remain insufficiently understood. This study develops an integrated ESG-innovation framework and examines quarterly panel data for 24 Taiwanese financial [...] Read more.

Sustainable finance, digital financial innovation, and green innovation have become central strategic pressures in banking, yet their joint effects on bank performance and risk remain insufficiently understood. This study develops an integrated ESG-innovation framework and examines quarterly panel data for 24 Taiwanese financial holding and domestic commercial banks from 2016Q1 to 2025Q3, yielding 934 bank-quarter observations. Return on assets (ROA) and the Z-score are used to capture operating performance and financial stability, respectively, and bank fixed-effects panel models are estimated for high- and low-ESG as well as high- and low-innovation subsamples. The re-estimated results reveal a conditional sustainability effect: ESG and innovation do not generate homogeneous financial benefits, but depend on banks’ ESG foundations, innovation intensity, leverage, and scale. Environmental scores are positively associated with ROA in the high-ESG subsample and weakly positive in the low-ESG subsample, whereas credit card transaction expansion is costly for low-ESG banks. In high-innovation banks, credit card transaction volume and green patents are negatively associated with ROA, suggesting adjustment costs and diminishing marginal returns. For financial stability, ESG recognition and green patents are more beneficial in lower ESG or innovation contexts, while leverage is consistently negative across all specifications. These findings contribute to the sustainable finance literature by clarifying how ESG, FinTech-related innovation, and green innovation jointly shape bank performance and risk in a policy-driven emerging market. The results also suggest that banks and regulators should adopt differentiated ESG and innovation strategies rather than assuming that sustainability investment produces uniform outcomes. Full article

(This article belongs to the Special Issue Corporate Financial Performance and Sustainability Practices)

20 pages, 374 KB

Open AccessArticle

Operationalising FinTech-Related Systemic Risks: An Evidence-Mapped Macroprudential Integration Framework (FMIF)

by János Kálmán and András Lapsánszky

Int. J. Financ. Stud. 2026, 14(7), 192; https://doi.org/10.3390/ijfs14070192 - 20 Jul 2026

Viewed by 631

Abstract

Digital finance is reshaping financial intermediation through platform-based credit, stablecoin-based payment and settlement arrangements, and a rapidly deepening reliance on critical third-party technology providers. Existing international frameworks identify many of these vulnerabilities, but macroprudential authorities still lack a traceable operational bridge from FinTech [...] Read more.

Digital finance is reshaping financial intermediation through platform-based credit, stablecoin-based payment and settlement arrangements, and a rapidly deepening reliance on critical third-party technology providers. Existing international frameworks identify many of these vulnerabilities, but macroprudential authorities still lack a traceable operational bridge from FinTech activities to systemic-risk channels, measurable indicators, stress-test assumptions and staged policy escalation. This article proposes the FinTech Macroprudential Integration Framework (FMIF) as an evidence-mapped operationalisation layer for existing macroprudential regimes. The FMIF does not claim to replace the frameworks issued by the FSB, BIS, IMF, BCBS, the EU or cyber-resilience authorities; instead, it translates their risk taxonomies and policy insights into a structured workflow linking activity perimeter, dependency registry, indicator formulas, modular stress tests and governance interfaces. The framework is developed for three activity clusters: platform credit and bank–FinTech partnerships; stablecoin-based payment and settlement; and critical third-party technology dependencies. These clusters are mapped to three channels: liquidity/run dynamics, interconnectedness and market spillovers, and operational concentration/correlated disruption. The article contributes by clarifying the research gap, disclosing the evidence-mapping procedure and source-level coding, classifying evidence quality, specifying indicator formulas and calibration principles, adding a stablecoin-run illustrative application, and discussing legal and institutional feasibility. The FMIF should be understood as a decision-support and decision-preparedness framework rather than as a fully validated decision-ready model. Empirical validation, jurisdiction-specific thresholds and legal triggers remain necessary next steps. Full article

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25 pages, 1131 KB

Open AccessArticle

How Does the Recovery and Resilience Facility Compare to the Cohesion Policy Funds: The Case of Renewable Energy

by Daniel Nigohosyan and Albena Vutsova

Int. J. Financ. Stud. 2026, 14(7), 191; https://doi.org/10.3390/ijfs14070191 - 20 Jul 2026

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Abstract

This paper provides the first systematic, cross-country empirical comparison of the Recovery and Resilience Facility (RRF) and Cohesion Policy funds (CPF) in the domain of renewable energy deployment. Covering 14 EU Member States, the analysis combines quantitative cross-country evidence on financing volumes, technology [...] Read more.

This paper provides the first systematic, cross-country empirical comparison of the Recovery and Resilience Facility (RRF) and Cohesion Policy funds (CPF) in the domain of renewable energy deployment. Covering 14 EU Member States, the analysis combines quantitative cross-country evidence on financing volumes, technology mixes, implementation speed, and reported capacity achievements. The findings show that the RRF represents a major amplification of EU renewable energy financing, with planned allocations exceeding Cohesion Policy expenditure by a factor of five to ten. At the same time, claims of superior performance-based delivery require qualification: green transition financial progress lags the general RRF disbursement rate, milestone fulfilment for renewable energy falls short of planned indicative rates in most countries, and reported operational capacity figures raise concerns about plausibility. The analysis reveals no meaningful correlation between milestone and target fulfilment and progress with renewable energy country-specific recommendations, suggesting that administrative compliance with milestones does not immediately translate into structural reform outcomes. These findings carry direct implications for the design of the post-2027 EU financial framework, particularly regarding the performance indicators, the introduction of attribution protocols for reform-linked achievements, and the preservation of complementarity between performance-based and non-performance-based approaches. Full article

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20 pages, 836 KB

Open AccessArticle

Channel Observability in Digital Financial Inclusion Measurement: A Diagnostic Study of OIC Countries, 2015–2024

by Nassar Al-Hafidh, Ahmed Lateef Salih Al-Karawi, Hayder Albayati and Erginbay Uğurlu

Int. J. Financ. Stud. 2026, 14(7), 190; https://doi.org/10.3390/ijfs14070190 - 20 Jul 2026

Viewed by 565

Abstract

Digital financial inclusion (DFI) has become a central topic in financial inclusion research because digital payments, mobile money, internet banking, and platform-based finance can reduce access barriers and expand formal financial participation. Prior studies have documented the development relevance of financial inclusion and [...] Read more.

Digital financial inclusion (DFI) has become a central topic in financial inclusion research because digital payments, mobile money, internet banking, and platform-based finance can reduce access barriers and expand formal financial participation. Prior studies have documented the development relevance of financial inclusion and have constructed multidimensional financial inclusion and DFI indices, often using PCA and related composite-indicator methods. A remaining measurement gap concerns the equal observability of different digital-finance architectures within a common cross-country indicator set. This study addresses that gap by analyzing an existing PCA-based DFI score for 40 Organisation of Islamic Cooperation (OIC) countries over 2015–2024 through a channel-observability framework. The objective is to examine whether the observed DFI ranking is captured more directly through mobile-money indicators than through the available infrastructure-based representation of bank-led digital finance. The analysis decomposes the six available indicators into a bank-led visibility proxy, based on internet penetration and ATM density, and a mobile-money visibility proxy, based on mobile agents, mobile accounts, mobile transaction volume, and transaction value relative to GDP. The OIC-wide mean DFI score increased from 11.31 in 2015 to 31.24 in 2024, while dispersion widened and the 2015 and 2024 top-ten country groups had zero overlap. The channel diagnostics show that the highest observed DFI scores are concentrated among countries whose digital-finance activity is directly recorded through mobile-money indicators, whereas several financially advanced economies are visible mainly through the bank-led infrastructure proxy. Zero-coded mobile-money observations are interpreted as indicator-visibility signals for the standalone mobile-money channel and considered separately from broader digital-finance activity. The Random Forest analysis functions as a bounded internal sensitivity audit of the existing six-indicator score and shows that mobile-money transaction variables carry the largest within-score explanatory weight. The theoretical contribution is to frame DFI measurement as an architecture-dependent observability problem rather than only as a weighting problem. The practical implication is that cross-country DFI rankings should be interpreted together with channel diagnostics, especially when bank-led digital services such as mobile banking, card payments, POS transactions, QR payments, and instant-payment systems are outside the balanced indicator set. Full article

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22 pages, 534 KB

Open AccessArticle

Corporate Social Irresponsibility and Market Reactions: An Analysis Based on Investor Sentiment and Investor Attention

by Xiaofang Tan, Ruirui Wei and Rixin Li

Int. J. Financ. Stud. 2026, 14(7), 189; https://doi.org/10.3390/ijfs14070189 - 18 Jul 2026

Viewed by 404

Abstract

Against the backdrop of rising corporate social irresponsibility (CSI) incidents in China’s capital market, this study examines how CSI affects short-window market reactions and through which investor-side mechanisms this effect operates. Using A-share listed companies in Shanghai and Shenzhen from 2017 to 2021, [...] Read more.

Against the backdrop of rising corporate social irresponsibility (CSI) incidents in China’s capital market, this study examines how CSI affects short-window market reactions and through which investor-side mechanisms this effect operates. Using A-share listed companies in Shanghai and Shenzhen from 2017 to 2021, we construct a CSI index adapted to the Chinese institutional setting and employ an event-study framework combined with mediation and moderation models. The results show that CSI is associated with significantly more negative cumulative abnormal returns. Mechanism tests indicate that CSI is negatively associated with investor sentiment, and lower investor sentiment is associated with more negative market reactions, implying a negative indirect path through investor sentiment. Investor attention further conditions this relationship: when investor attention is higher, the negative market reaction to CSI is stronger, although the baseline interaction result should be interpreted cautiously because its significance is marginal. These conclusions are supported by Heckman two-step estimation, alternative sample construction, and alternative event-window tests. Additional analysis shows that prior CSR reputation can mitigate investor punishment after CSI events, suggesting an insurance effect. Full article

(This article belongs to the Collection Corporate Social Responsibility in Finance)

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34 pages, 514 KB

Open AccessSystematic Review

Money Laundering in Crypto-Asset Environments: A Systematic Literature Review

by Francesco Cortellese, Rubén Mora-Ruano and Álvaro Salas-Suárez

Int. J. Financ. Stud. 2026, 14(7), 188; https://doi.org/10.3390/ijfs14070188 - 16 Jul 2026

Viewed by 1058

Abstract

This article provides a systematic literature review of recent research on money laundering in crypto-asset environments, focusing on the main operational challenges and technical solutions proposed. Following PRISMA 2020 guidelines, the review draws on searches in Web of Science, Scopus and Google Scholar, [...] Read more.

This article provides a systematic literature review of recent research on money laundering in crypto-asset environments, focusing on the main operational challenges and technical solutions proposed. Following PRISMA 2020 guidelines, the review draws on searches in Web of Science, Scopus and Google Scholar, which identified 680 records and led, after screening and the application of inclusion and exclusion criteria, to a final sample of 58 academic studies published between 2020 and 2025. The review identifies four core challenges in blockchain-based anti-money laundering: pseudonymity, label scarcity and class imbalance, structural and computational complexity, and cross-blockchain data fragmentation. In response, the literature proposes several detection approaches, particularly feature-based and graph-based models, focusing on transactions, addresses, mixers and service providers. The findings show that, although these methods improve the detection of suspicious activity, important limitations remain regarding real-world identity attribution, reliable AML-specific ground-truth labels, scalability, operational validation and cross-chain flow reconstruction. The article contributes an analytical framework that links structural AML challenges with methodological responses, supporting clearer comparison of models and identifying priorities for future research. It also highlights the need for multidisciplinary collaboration across data science, finance, regulation, economics and forensic investigation. Full article

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47 pages, 6935 KB

Open AccessArticle

Optimizing Risk Profiling of Agricultural Loans: Default Prediction Using Multi-Source Remote Sensing Digital Footprints

by Jue Wang and Mengjiao Gu

Int. J. Financ. Stud. 2026, 14(7), 187; https://doi.org/10.3390/ijfs14070187 - 15 Jul 2026

Viewed by 594

Abstract

Accurate default risk prediction for agricultural loans is a prerequisite for balancing financial inclusion and safety in rural finance, yet traditional assessment methods have a limited capacity to capture exogenous variables such as climate risk. To this end, this paper constructs a credit [...] Read more.

Accurate default risk prediction for agricultural loans is a prerequisite for balancing financial inclusion and safety in rural finance, yet traditional assessment methods have a limited capacity to capture exogenous variables such as climate risk. To this end, this paper constructs a credit risk prediction framework integrating multi-source remote sensing data with explainable machine learning to optimize the credit profile of agricultural loans. Controlling for conventional agricultural loan variables, a logistic regression model examines the statistical association between multi-source remote sensing features and farmers’ default risk. A comparative analysis of multiple machine learning models further demonstrates that incorporating remote sensing data helps improve prediction accuracy, with temperature and precipitation volatility emerging as the most important remote sensing predictors, capturing the predominant climate-related variations in default prediction. Analysis using the Explainable Boosting Machine (EBM) quantifies the contribution of these variables to default risk prediction and identifies notable interaction patterns between remote sensing indicators and traditional agricultural loan variables. Full article

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22 pages, 2479 KB

Open AccessArticle

Credit to Economic Sectors and the Ability to Repay Long-Run External Loans: New Evidence from Jordan

by Raad Mahmoud Al-Tal, Ahmad M. Fawaier and Mohammad Tayeh

Int. J. Financ. Stud. 2026, 14(7), 186; https://doi.org/10.3390/ijfs14070186 - 13 Jul 2026

Viewed by 583

Abstract

Emerging economies face crucial challenges around fiscal stability, particularly servicing foreign debt and securing long-term financing arrangements. In this context, we investigated the relationship between the share of banking facilities allocated to various economic sectors, the growth of public revenues and the proportion [...] Read more.

Emerging economies face crucial challenges around fiscal stability, particularly servicing foreign debt and securing long-term financing arrangements. In this context, we investigated the relationship between the share of banking facilities allocated to various economic sectors, the growth of public revenues and the proportion of long-term loans relative to total foreign debt in Jordan. Using data from 2008: Q1 to 2022: Q4 and employing two regression models along with the Vector Error Correction model, key findings reveal that the share of banking facilities allocated to total financing positively impacts public income and reduces long-term liabilities (LRL). Additionally, the positive effect of direct credit from financial institutions on real GDP and public income is associated with a negative impact on LRL. Conversely, direct credit from financial corporations negatively influences real GDP and public income while positively affecting LRL. Direct credit from public sector financing exhibits an inverse relationship with economic growth and public income, leading to a positive association with LRL. The statistically significant error correction coefficients indicate that short-run deviations are corrected toward the long-run equilibrium, with the first model showing a faster but oscillatory adjustment process and the second model exhibiting a slower and more gradual return to equilibrium. These findings suggest that developing countries like Jordan must prioritize banking facilitation for sectors such as industry, tourism, and agriculture to facilitate debt repayment. Full article

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14 pages, 2077 KB

Open AccessArticle

Learning to Listen? Fed Communication, Global Risk Sentiment, and Emerging Market Capital Flows

by Colin Ellis

Int. J. Financ. Stud. 2026, 14(7), 185; https://doi.org/10.3390/ijfs14070185 - 13 Jul 2026

Viewed by 375

Abstract

This paper examines the relationship between Federal Open Market Committee (FOMC) communication surprises, global risk sentiment, and net portfolio debt inflows to twelve major emerging market economies over the period 2000–2024. Exploiting a high-frequency U.S. Monetary Policy Event-Study Database, we estimate panel fixed-effects [...] Read more.

This paper examines the relationship between Federal Open Market Committee (FOMC) communication surprises, global risk sentiment, and net portfolio debt inflows to twelve major emerging market economies over the period 2000–2024. Exploiting a high-frequency U.S. Monetary Policy Event-Study Database, we estimate panel fixed-effects regressions and local projections at quarterly frequency. We find that global risk sentiment, proxied by the VIX, is a robust and persistent driver of emerging market capital flows, while Fed communication surprises are statistically insignificant in normal times and in the 2022–2024 tightening cycle. A striking exception is the 2013 taper tantrum—the episode of severe capital outflow pressure triggered by Chairman Bernanke’s May 2013 congressional testimony signalling a possible tapering of asset purchases. Regime interaction tests reveal a large, highly significant negative effect of communication surprises on flows during this episode alone, with no comparable effect in 2022. Local projections confirm that the taper tantrum generated a sharp initial outflow followed by partial reversal, while VIX effects are contemporaneous but not persistent. We empirically test for market learning, finding that reduced sensitivity to Fed communication reflects a discrete recalibration after the 2013 shock rather than a gradual learning process. Regarding capital flows, the taper tantrum is clearly the exception, not the rule. Full article

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30 pages, 431 KB

Open AccessArticle

by Zulkifli Umar, Muhammad Arfan, Islahuddin Islahuddin and Mulia Saputra

Int. J. Financ. Stud. 2026, 14(7), 184; https://doi.org/10.3390/ijfs14070184 - 10 Jul 2026

Viewed by 653

Abstract

This study aims to examine the relationship between related party sales (RPS) and earnings management (EMN), as well as to investigate the moderating effects of institutional ownership (IO), single institutional ownership (SIO), and dispersed institutional ownership (DIO) on this relationship. This study examines [...] Read more.

This study aims to examine the relationship between related party sales (RPS) and earnings management (EMN), as well as to investigate the moderating effects of institutional ownership (IO), single institutional ownership (SIO), and dispersed institutional ownership (DIO) on this relationship. This study examines non-service and non-financial firms listed on the Indonesia Stock Exchange during the 2016–2024 period. The sample selection included firms with IO and RPS. The final sample consisted of 68 firms (585 firm-year observations) out of a total of 601 firms and was analyzed using moderated regression with unbalanced panel data. The findings indicate that RPS has a positive effect on EMN. IO weakens the positive effect of RPS on EMN. However, in the group consisting only of SIO, the positive effect of RPS on EMN becomes stronger. In contrast, in the DIO group, DIO is unable to moderate the relationship. Furthermore, EMN in firms engaging in RPS with parent firms does not differ from EMN in firms engaging in RPS with non-parent related parties. Finally, we conclude that, in the Indonesian context, RPS provides opportunities for management to engage in opportunistic behavior. The presence of SIO may increase earnings management, whereas DIO is unable to mitigate earnings management. Full article

(This article belongs to the Topic Sustainable and Green Finance)

26 pages, 579 KB

Open AccessArticle

Board Diversity, Diversity Policies, and Firm Value: Diversity Performance as a Mediating Channel in ASEAN-5 Listed Companies

by Arie Pratama, Winwin Yadiati, Edi Jaenudin and Mohamad Ezrien Mohamad Kamal

Int. J. Financ. Stud. 2026, 14(7), 183; https://doi.org/10.3390/ijfs14070183 - 10 Jul 2026

Viewed by 507

Abstract

This study examines the association among board diversity, diversity policies, diversity performance, and firm value in ASEAN-5 listed companies: Indonesia, Malaysia, Singapore, Thailand, and the Philippines. Board diversity is measured through gender diversity, national diversity, board-specific skills, and board affiliation, while diversity policy [...] Read more.

This study examines the association among board diversity, diversity policies, diversity performance, and firm value in ASEAN-5 listed companies: Indonesia, Malaysia, Singapore, Thailand, and the Philippines. Board diversity is measured through gender diversity, national diversity, board-specific skills, and board affiliation, while diversity policy captures disclosed opportunity and diversity policy, diversity targets, and board diversity policy. Diversity performance is proxied by Refinitiv’s Diversity and Inclusion Rating score, and firm value is measured by price-to-book value. Using 77 firms and 154 firm-year observations from 2022 to 2023, the study applies descriptive analysis, ANOVA, observed-variable SEM-path analysis, regression robustness checks, alternative PBV specifications, PROCESS bootstrapped mediation, and Bayesian path analysis. The results suggest that national diversity, board affiliation, and diversity policy are positively associated with diversity performance, while diversity performance is positively associated with firm value. Diversity policy and diversity performance provide the most stable evidence across specifications, whereas the board diversity results are more sensitive to the estimation approach. Bayesian results support the positive direction of the main paths, but indirect effects remain inconclusive. Overall, the findings provide cautious associational evidence that diversity-related governance may be reflected in market valuation through observable diversity performance, subject to the small sample, short period, and Refinitiv data coverage. Full article

(This article belongs to the Special Issue Advances in Corporate Finance: Theory and Practice)

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21 pages, 1212 KB

Open AccessArticle

Conditional-Mean Predictive Precedence and Information Concentration in a Commodity-Dependent Equity Market: Evidence from Petrobras and the Ibovespa, 2005–2026

by Alejandro Pérez-y-Soto-Domínguez, Juan Manuel Candelo-Viáfara and Edwin Arango-Espinal

Int. J. Financ. Stud. 2026, 14(7), 182; https://doi.org/10.3390/ijfs14070182 - 9 Jul 2026

Viewed by 430

Abstract

This paper examines whether standard price-discovery measures can reliably identify directional predictive precedence in a highly correlated commodity-equity system. Using 21 years of daily data for Petrobras and the Ibovespa (2005–2026), the study separates a measurement problem in forecast error variance decomposition from [...] Read more.

This paper examines whether standard price-discovery measures can reliably identify directional predictive precedence in a highly correlated commodity-equity system. Using 21 years of daily data for Petrobras and the Ibovespa (2005–2026), the study separates a measurement problem in forecast error variance decomposition from the reduced-form question of directional predictability in the conditional mean. The empirical strategy combines Monte Carlo simulation, generalized and Cholesky forecast error variance decompositions, full-sample and rolling-window Granger causality tests, a continuous Granger Leadership Index, Gaussian mixture regime classification, robustness checks, and out-of-sample forecasting validation. The results show that Cholesky-based FEVDs can be systematically misleading in high-correlation settings: at the observed contemporaneous correlation, generalized FEVD symmetry is mechanically induced by row normalization, while Cholesky attribution changes sharply under alternative orderings. By contrast, first-moment predictability reveals a directional asymmetry from Petrobras to the Ibovespa, interpreted as conditional-mean predictive precedence rather than structural informed trading or definitive price discovery. This asymmetry survives alternative lag structures, weekly aggregation, univariate GARCH filtering, within-dataset proxy controls, and a stylized equal-weight ex-Petrobras benchmark. Rolling evidence further identifies five persistent predictive regimes that alternate between firm-led, neutral, and macro-dominant states, indicating that firm-index predictive relations are regime dependent rather than static. Out-of-sample forecasting shows that the identified predictive precedence does not generate exploitable one-step-ahead gains (RMSE ratio = 1.002, OOS-R² = −0.003, DM p = 0.451), thereby delimiting the economic scope of the findings. Overall, the results support a reduced-form interpretation of Petrobras–Ibovespa predictive dynamics and highlight the need to distinguish variance connectedness from conditional-mean predictive content when contemporaneous correlation is high. Full article

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43 pages, 2070 KB

Open AccessArticle

Beyond Tourism Market Recovery: Financial Vulnerability and Operational Drivers of Hotel Profitability

by Elena Muñoz-Muñoz, Carlos Díaz-Caro, Eva Crespo-Cebada and Ángel-Sabino Mirón Sanguino

Int. J. Financ. Stud. 2026, 14(7), 181; https://doi.org/10.3390/ijfs14070181 - 9 Jul 2026

Cited by 1 | Viewed by 1413

Abstract

Tourism recovery and hotel firm profitability do not necessarily move in lockstep. This paper examines the extent to which aggregate demand recovery is translated into firm-level financial performance, introducing the concept of a tourism-to-profitability conversion gap. The study combines bibliometric mapping of hotel [...] Read more.

Tourism recovery and hotel firm profitability do not necessarily move in lockstep. This paper examines the extent to which aggregate demand recovery is translated into firm-level financial performance, introducing the concept of a tourism-to-profitability conversion gap. The study combines bibliometric mapping of hotel performance research with a firm-level econometric analysis of an unbalanced panel of 4159 Spanish hotel firms classified under CNAE 5510 over 2015–2024, representing approximately 38,651 firm-year observations from SABI. Fixed-effects models are estimated using return on assets as the main dependent variable. The results show that leverage is consistently and negatively associated with profitability, and that this association became stronger during the COVID-19 period, as indicated by negative and significant leverage×COVID-19 interaction terms. Labour productivity is positively related to profitability, whereas labour cost intensity and fixed-asset intensity are negatively associated with returns when not matched by sufficient revenue generation. Median ROA fell from 3.7% pre-COVID-19 to −0.9% during the pandemic and recovered to 5.7% post-COVID-19 among surviving firms; however, the modest post-COVID-19 coefficient in the baseline model suggests that aggregate recovery indicators may conceal substantial heterogeneity in firm-level financial recovery. The paper reframes post-crisis hotel recovery as a firm-level financial transmission process: the conversion of renewed tourism demand into accounting profitability appears conditioned by balance-sheet vulnerability, labour productivity, cost structure, and asset rigidity, mechanisms that remain less central in the broader hotel performance literature. Full article

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18 pages, 659 KB

Open AccessArticle

Do Green Bonds Deliver? Green Innovation, Financing Constraints, and High-Quality Development Among Chinese A-Share Listed Firms

by Yutong Wang, Qi Zhang, Yixuan Xie, Xueying Meng and Mahmood Ahmad

Int. J. Financ. Stud. 2026, 14(7), 180; https://doi.org/10.3390/ijfs14070180 - 8 Jul 2026

Cited by 1 | Viewed by 511

Abstract

Every dollar directed toward green finance carries a promise, but does it deliver? This study tests whether corporate green bond issuance translates into measurable improvements in firm-level high-quality development, which is defined as the enhancement of firms’ sustainable growth capacity and resource allocation [...] Read more.

Every dollar directed toward green finance carries a promise, but does it deliver? This study tests whether corporate green bond issuance translates into measurable improvements in firm-level high-quality development, which is defined as the enhancement of firms’ sustainable growth capacity and resource allocation efficiency and is proxied by total factor productivity (TFP), a widely adopted indicator of development quality in the economics literature. Using panel data from Shanghai and Shenzhen A-share listed enterprises over 2014–2024, we employ a multi-period difference-in-differences framework, validated by parallel trend and placebo tests, to identify the causal effect of green bond issuance. Results confirm a significant positive impact, with green bond issuance raising firm TFP by 0.240 units, representing a substantial improvement in firms’ productivity performance relative to the sample average, robust across Olley–Pakes, Levinsohn–Petrin, and propensity score matched specifications. Mechanism analysis identifies three transmission channels: green technological innovation and green management practices operate as partial mediators, while financing constraints serve as a mediator. Heterogeneity tests reveal stronger effects among firms with higher agency costs, heavier pollution burdens, and those located in eastern China’s more marketized regions. By uncovering the productivity-enhancing mechanisms of green bond issuance, this study enriches the literature on sustainable finance and corporate high-quality development and provides new firm-level evidence on the economic consequences of green financial instruments. These findings provide micro-level evidence that green finance generates tangible productivity gains beyond signaling, offering actionable guidance for policymakers advancing sustainable corporate development under China’s dual carbon targets. Full article

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30 pages, 12681 KB

Open AccessArticle

Gold-Backed Cryptocurrencies, Precious Metals, and Hedging Performance: Evidence from Dynamic Dependence Structures

by Yasmine Snene Manzli, Oana Panazan, Ahmed Jeribi and Catalin Gheorghe

Int. J. Financ. Stud. 2026, 14(7), 179; https://doi.org/10.3390/ijfs14070179 - 8 Jul 2026

Viewed by 723

Abstract

This study compares gold-backed and conventional cryptocurrencies in terms of dependence structures and hedging effectiveness relative to precious metals. Daily data for gold, silver, cryptocurrencies, gold-backed cryptocurrencies, and USD-backed stablecoins from July 2020 to March 2026 are analyzed using a multivariate stochastic volatility [...] Read more.

This study compares gold-backed and conventional cryptocurrencies in terms of dependence structures and hedging effectiveness relative to precious metals. Daily data for gold, silver, cryptocurrencies, gold-backed cryptocurrencies, and USD-backed stablecoins from July 2020 to March 2026 are analyzed using a multivariate stochastic volatility framework with a grouped factor structure. Gold-backed cryptocurrencies move closely with gold and silver and provide meaningful hedging benefits. Conventional cryptocurrencies present weaker and less stable relationships with precious metals, reducing hedging potential. Important differences emerge between gold and silver, suggesting that precious metals should not be treated as a homogeneous asset class. Gold-backed cryptocurrencies appear much more closely aligned with precious metals than conventional cryptocurrencies. Additional analyses show that hedging effectiveness increases substantially during periods of elevated volatility, particularly for PAXG and XAUT, indicating stronger risk-reduction benefits under stressed market conditions. Robustness tests using SPDR Gold Shares (GLD) confirm the stability of the main findings. The findings are relevant for portfolio diversification, hedging decisions, and risk management. Full article

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38 pages, 1867 KB

Open AccessArticle

Perpetual Futures in Decentralised Finance: Mechanics, Economic Claims, and the Drivers of Trading Volume

by Siddhant Shah and Eugene Pinsky

Int. J. Financ. Stud. 2026, 14(7), 178; https://doi.org/10.3390/ijfs14070178 - 8 Jul 2026

Viewed by 2464

Abstract

DeFi perpetual futures have expanded from crypto-native instruments to tokenised equities and commodities, yet the economics of these instruments remain poorly understood. We study 17 assets—5 crypto coins, 8 tokenised equities, and 4 tokenised commodities—on three DeFi perpetual platforms (Hyperliquid, EdgeX, Lighter) over [...] Read more.

DeFi perpetual futures have expanded from crypto-native instruments to tokenised equities and commodities, yet the economics of these instruments remain poorly understood. We study 17 assets—5 crypto coins, 8 tokenised equities, and 4 tokenised commodities—on three DeFi perpetual platforms (Hyperliquid, EdgeX, Lighter) over July 2025 to February 2026. Applying a rolling 3-day t-test to identify abnormal trading volume without a predetermined event calendar, we document 1797 statistically significant volume anomalies. DeFi perpetual volume is driven primarily by macroeconomic and policy shocks (ADA

t = + 628

on the U.S. Crypto Strategic Reserve announcement; 15 of 17 assets simultaneously anomalous during January 2026 mega-cap earnings), asset-class-specific catalysts, and a recurring 24/7 market-structure effect tied to weekends and U.S. holidays. Price tracking accuracy reveals a sharp maturity gradient: crypto coin perpetuals exhibit near-perfect price tracking (

ρ \geq 0.999

) and strong TradFi volume co-movement (

ρ (0) \in [0.72, 0.83]

), while equity perpetuals show weaker integration and commodity perpetuals range from adequate (oil, gold) to unreliable (natural gas). We conclude that crypto DeFi perpetuals constitute credible synthetic economic claims on underlying assets, while equity and commodity perpetuals remain at an early developmental stage. Integration with traditional financial markets is well-established for crypto coin perpetuals; for equity and commodity perpetuals, the evidence is preliminary, given short observation windows, and further research with longer time series is needed before definitive conclusions can be drawn. Full article

(This article belongs to the Special Issue Advances in Financial Econometrics)

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23 pages, 350 KB

Open AccessArticle

Voluntary Carbon Verification and Corporate Capital Structure Adjustment Speed: A Global Investigation

by Faisal Alnori, Abdullah Bugshan and Walid Bakry

Int. J. Financ. Stud. 2026, 14(7), 177; https://doi.org/10.3390/ijfs14070177 - 7 Jul 2026

Viewed by 635

Abstract

Using an international sample of firms from 47 countries/regions over the years 2010–2020, we examine whether third-party verification of carbon emissions information affects the speed at which firms adjust their capital structure toward the trade-off theory’s optimal leverage target. Using alternative estimation techniques [...] Read more.

Using an international sample of firms from 47 countries/regions over the years 2010–2020, we examine whether third-party verification of carbon emissions information affects the speed at which firms adjust their capital structure toward the trade-off theory’s optimal leverage target. Using alternative estimation techniques and robustness checks, we find that third-party carbon assurance significantly accelerates firms’ leverage adjustment speed. Firms that engage in independent carbon verification adjust more rapidly toward their target capital structure than non-assured firms. We extended our investigation and confirmed that this effect persists across both developed and developing markets. These results support the notion that carbon assurance is associated with lower information asymmetry between firms and lenders, thereby lowering the cost of external debt and facilitating faster capital structure rebalancing. We further investigate whether the relationship differs by assurance provider type by distinguishing between Big Four and non-Big Four assurance providers. The results remain robust when distinguishing between Big Four and non-Big Four assurance providers regardless of the assurer quality, confirming that assured firms adjust their capital structures faster than non-assured firms. The outcomes of this study demonstrate that firms’ sustainability reporting can shape the speed of capital structure adjustment. Full article

(This article belongs to the Special Issue Recent Development in Sustainable Finance, New Trends and Future Directions)

26 pages, 3717 KB

Open AccessArticle

Adapting Investment Strategies in Uncertain Markets: The Case of Romanian ICT Firms

by Andreea Barbu, Mirona Ana-Maria Ichimov and Mircea Boşcoianu

Int. J. Financ. Stud. 2026, 14(7), 176; https://doi.org/10.3390/ijfs14070176 - 7 Jul 2026

Viewed by 440

Abstract

This study investigates the possibilities for recently listed Romanian Information and Communications Technology (ICT) firms to select optimal sets of financial strategies under adverse macroeconomic conditions, with high and persistent inflation, high volatility, high cost of financing and liquidity constraints that influence investment [...] Read more.

This study investigates the possibilities for recently listed Romanian Information and Communications Technology (ICT) firms to select optimal sets of financial strategies under adverse macroeconomic conditions, with high and persistent inflation, high volatility, high cost of financing and liquidity constraints that influence investment decisions and financial resilience. Using a stochastic investment model with the Tobin’s Q factor in a dynamic framework equipped with a generalized Wiener process, this study offers an intuitive approach for simultaneously assessing corporate market value under financial constraints and formulating optimal decisions based on liquidity management. In this research, the numerical simulations in Python for a set of 16 scenarios resulting from combining technological and macroeconomic variables were performed, with a series of parameters held constant. The results highlight the decisive role of financial restrictions and macroeconomic volatility in shaping the investment behavior, as well as the importance of adjusting the timing of investments together with liquidity mechanisms capable of improving financial resilience. The main contribution of this study is the simplicity with which one can assess the impact of the risk-free rate and volatility on the main parameters of the set of strategies (earnings dynamics, liquidity risk, cost of capital, liquidation value, opportunity cost associated with holding cash) and to assess the integrated perspective on financial resilience. This procedure is simple and scalable and can also represent a practical tool to support management and investment decisions in volatile and turbulent conditions. Full article

(This article belongs to the Special Issue Stock Market Developments and Investment Implications)

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24 pages, 14807 KB

Open AccessArticle

Dynamic Co-Movement Among Exchange Rate Volatility, Energy Commodities, and Stock Indices: A Multiple Wavelet Approach

by Benjamin Mudiangombe Mudiangombe and Charles Raoul Tchuinkam-Djemo

Int. J. Financ. Stud. 2026, 14(7), 175; https://doi.org/10.3390/ijfs14070175 - 7 Jul 2026

Viewed by 846

Abstract

This study employed a different type of wavelet approach to investigate the dynamic interdependence among exchange rate volatility, stock indices, and energy commodity markets. Using daily data covering the period from 2005 to October 2025 on energy commodities, stock index, and foreign exchange [...] Read more.

This study employed a different type of wavelet approach to investigate the dynamic interdependence among exchange rate volatility, stock indices, and energy commodity markets. Using daily data covering the period from 2005 to October 2025 on energy commodities, stock index, and foreign exchange rates of selected BRICS economies. We include both crude oil and Brent oil, along with natural gas, aiming to capture not only the time–frequency interconnectedness among these assets but also to gain deeper insights into cross-commodity correlations across various energy sectors, thereby clarifying whether economic shocks in these markets are localized or globalized. Assessing data volatility, it can be observed that exchange rates and stock indexes tend to be less volatile than oil markets. The coherence zone indicates that foreign currency significantly influences the interdependence between the Bovespa and Brent oil prices. While rising oil prices can generate inflationary pressures, for an oil-exporting nation like Brazil, the favorable impacts on exports and the trade balance often led to an appreciation of the Brazilian Real (BRL) against the US dollar. Full article

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27 pages, 1129 KB

Open AccessArticle

Deterministic and Stochastic Modeling of Deposit–Loan Dynamics with Optimal Regulatory Control

by Moch. Fandi Ansori, F. Hilal Gümüş, Ratna Herdiana, Hafidh Khoerul Fata, Nurcahya Yulian Ashar and Handika Lintang Saputra

Int. J. Financ. Stud. 2026, 14(7), 174; https://doi.org/10.3390/ijfs14070174 - 6 Jul 2026

Viewed by 605

Abstract

Banks must balance deposit stability, loan expansion, and regulatory compliance while operating under liquidity constraints and financial risks. This study presents a mathematical model to examine the dynamics of bank deposits and loans under the influence of liquidity mechanisms and regulatory policies. The [...] Read more.

Banks must balance deposit stability, loan expansion, and regulatory compliance while operating under liquidity constraints and financial risks. This study presents a mathematical model to examine the dynamics of bank deposits and loans under the influence of liquidity mechanisms and regulatory policies. The model proceeds in three stages: a deterministic nonlinear model, a dynamic optimal control model, and a stochastic model. Under the deterministic model, deposit withdrawals are liquidity-dependent, leading to a feedback mechanism in which liquidity improves deposit stability while financing loan growth. The theoretical results demonstrate the model’s positive and bounded solutions and show the existence and local stability of equilibria. Several parameters are based on regulatory policies or calibrated from Indonesian banking data, while the unknown parameters are estimated using the particle swarm optimization (PSO) algorithm. The results show that the proposed model is capable of fitting and predicting the data and has slightly lower mean absolute percentage errors for in-sample and out-of-sample compared with the benchmark model, and achieves comparable directional forecasting performance based on the index of directionality. Sensitivity analysis shows that the capital adequacy ratio supports lending, whereas an increased reserve requirement limits lending. An optimal control approach is developed by considering the reserve and capital requirements as time-varying policy variables. By applying Pontryagin’s maximum principle, we establish the necessary conditions for optimality. Numerical experiments demonstrate that the optimal control regulation enhances financial ratios, particularly the loan-to-deposit and liquidity ratios, at a reasonable cost. Finally, the stochastic model accounts for random variations in withdrawals and credit risks. Simulation-based observations reveal that although the system becomes more volatile, the mean dynamics are close to the deterministic case. Our framework offers a data-based and analytically tractable approach for studying the dynamics of banking variables and the effects of regulatory policies. The proposed model provides a mathematical tool for assessing the long-term effects of regulatory policies on banking performance and can assist bank managers and regulators in designing strategies that balance lending activity and liquidity resilience. Full article

(This article belongs to the Special Issue Mathematical Finance: Theory, Methods, and Applications)

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19 pages, 785 KB

Open AccessArticle

Financial Literacy and Teachers’ Saving Behavior: Evidence of a Mediated Relationship Through Financial Practices and the Role of Technological Access

by Thalía Marianela Linares Rojas and Marco Agustín Arbulú Ballesteros

Int. J. Financ. Stud. 2026, 14(7), 173; https://doi.org/10.3390/ijfs14070173 - 6 Jul 2026

Viewed by 1245

Abstract

Financial literacy has become critical for mitigating everyday financial risks and sustaining saving behavior, particularly in professions with stable but often constrained income such as teaching. This study examines whether financial literacy predicts teachers’ saving habits indirectly through financial practices, and whether technological [...] Read more.

Financial literacy has become critical for mitigating everyday financial risks and sustaining saving behavior, particularly in professions with stable but often constrained income such as teaching. This study examines whether financial literacy predicts teachers’ saving habits indirectly through financial practices, and whether technological access may be associated with the link between practices and saving. Using a cross-sectional survey of 180 teachers from public educational institutions in the Jequetepeque Valley (Peru) in 2025, we tested a moderated mediation model (PROCESS Model 14). Financial literacy showed a strong positive association with financial practices, while its direct effect on saving habits was not significant after controls. The indirect effect through financial practices was significant across levels of technological access; however, the moderation effect of technological access was only marginally significant (p = 0.057) and the index of moderated mediation did not reach statistical significance at α = 0.05, indicating that the moderating role of technology requires further investigation. Overall, the results suggest that financial knowledge alone does not predict saving habits: the effect operates through consistent financial practices, and digital access may facilitate the continuity of these practices. The study contributes to financial risk management research in teacher populations and to Sustainable Development Goals (SDGs) 4, 8, and 9 in rural educational contexts. Full article

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21 pages, 698 KB

Open AccessArticle

Unlocking Corporate Performance: The Role of Blockchain and Financial Transparency in Jordan’s Banking Sector Through Digital Accounting Systems

by Ahmad Rajab Jwailes, Saleh M. Kadi, Ehsan Almoataz, Bandar Altubaishe and Hamid Ghazi H Sulimany

Int. J. Financ. Stud. 2026, 14(7), 172; https://doi.org/10.3390/ijfs14070172 - 4 Jul 2026

Viewed by 602

Abstract

This study examines the impact of blockchain adoption and financial transparency on corporate performance in Jordan’s banking sector, with a focus on the mediating role of digital accounting systems. Targeting senior managers and financial analysts from Jordan’s banking sector, a sample of 152 [...] Read more.

This study examines the impact of blockchain adoption and financial transparency on corporate performance in Jordan’s banking sector, with a focus on the mediating role of digital accounting systems. Targeting senior managers and financial analysts from Jordan’s banking sector, a sample of 152 participants is analyzed using a quantitative, cross-sectional research design. Data is evaluated through Partial Least Squares Structural Equation Modeling (PLS-SEM). The results demonstrate that blockchain adoption and financial transparency significantly improve corporate performance, both directly and indirectly, through the mediating effect of digital accounting systems. These findings underscore the importance of integrating blockchain and digital accounting systems to enhance financial transparency, reduce inefficiencies, and build stakeholder trust. This study addresses a critical gap in the literature by exploring the mediating role of digital accounting systems in the relationship between blockchain adoption, financial transparency, and corporate performance, particularly in developing economies. This research offers valuable insights for managers, policymakers, and regulators, emphasizing the strategic value of blockchain and digital accounting systems in driving corporate performance. Its originality lies in combining the Technology–Organization–Environment (TOE) framework and Institutional Theory to provide a comprehensive understanding of these dynamics in Jordan’s banking sector. Full article

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27 pages, 421 KB

Open AccessArticle

Do Stable Banks Disclose More Climate Risk? Governance Evidence from the MENA Region

by Abdelmoneim Bahyeldin Mohamed Metwally, Mohamed Samy El-Deeb, Ahmed Bahieg Ragheb Mohamed and Eman Adel Ahmed

Int. J. Financ. Stud. 2026, 14(7), 171; https://doi.org/10.3390/ijfs14070171 - 3 Jul 2026

Viewed by 611

Abstract

The current study aims to identify the factors influencing the disclosure of climate-related risk information by the MENA banking sector and how bank financial stability acts as a moderator. The study draws from agency theory, resource dependency theory, and organizational legitimacy theory. Textual [...] Read more.

The current study aims to identify the factors influencing the disclosure of climate-related risk information by the MENA banking sector and how bank financial stability acts as a moderator. The study draws from agency theory, resource dependency theory, and organizational legitimacy theory. Textual analysis is used to analyze a panel data set comprising 46 banks of 13 MENA countries for the years 2020 to 2024 (230 observations). We investigate the impact of board independence, board size, and gender diversity on climate risk disclosure. It is found that while board size and gender diversity have a positive effect on CRD, there is no direct effect of board independence on CRD. However, after taking bank financial stability (Z-score) into account as a moderating variable, it is revealed that there is a significantly positive relationship between board independence and bank financial stability. Therefore, it can be said that independent board members are helpful in CRD only when banks have sound financial stability. This study provides various robustness tests through subsample analysis and alternative methods of estimating model parameters. Full article

(This article belongs to the Special Issue Banking Stability, Credit Risk and Financial Resilience in Emerging Markets)

23 pages, 582 KB

Open AccessArticle

Capital Market Development and Economic Growth in Romania: A Supply-Leading ARDL Analysis

by Catalin Drob, Ioana Plescau and Valentin Zichil

Int. J. Financ. Stud. 2026, 14(7), 170; https://doi.org/10.3390/ijfs14070170 - 3 Jul 2026

Viewed by 490

Abstract

This study investigates the long-run and short-run relationships between capital market development, foreign direct investment, trade openness, and real GDP per capita in Romania over 2003–2024, employing the Autoregressive Distributed Lag (ARDL) bound testing approach, complemented by lag-augmented VAR Granger-causality analysis and a [...] Read more.

This study investigates the long-run and short-run relationships between capital market development, foreign direct investment, trade openness, and real GDP per capita in Romania over 2003–2024, employing the Autoregressive Distributed Lag (ARDL) bound testing approach, complemented by lag-augmented VAR Granger-causality analysis and a comprehensive set of diagnostic and stability tests. The bounds tests strongly reject the null of no cointegration, confirming a long-run relationship that remains robust under finite-sample critical values. The causality analysis demonstrates a supply-leading mechanism from the equity market to real economic activity, while economic growth in turn Granger-causes both market liquidity and trade openness, pointing to demand-following dynamics for these channels. The analysis shows that foreign direct investment, market liquidity, and trade openness exert positive and significant short-run effects; yet their long-run coefficients are negative, significantly for FDI (foreign direct investments), capturing an asymmetry between immediate output gains and durable structural contribution that is characteristic of emerging European economies. The error-correction term is positive, demonstrating that real GDP (gross domestic product) per capita does not adjust back toward the long-run relationship in the conventional sense, but, instead, it behaves as a forcing variable that leads the financial and trade channels rather than being led by them. All in all, the findings describe an economy with functional short-run transmission channels, but limited long-run structural anchoring, with direct relevance for Sustainable Development Goals 8 and 17 and Romania’s ongoing OECD accession. Full article

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21 pages, 987 KB

Open AccessArticle

How Digital Transformation Shapes Corporate Financial Flexibility: The Phased Moderating Role of Supply Chain Resilience

by Chenxi Wu, Thoo Ai Chin and Yuihui Dai

Int. J. Financ. Stud. 2026, 14(7), 169; https://doi.org/10.3390/ijfs14070169 - 2 Jul 2026

Viewed by 628

Abstract

As a key engine of corporate innovation, digital transformation permeates business management. Can digital transformation improve corporate financial flexibility by leveraging the external supply chain? Our sample comprises Chinese listed companies over the period from 2015 to 2024, employing Python 3.10 crawling to [...] Read more.

As a key engine of corporate innovation, digital transformation permeates business management. Can digital transformation improve corporate financial flexibility by leveraging the external supply chain? Our sample comprises Chinese listed companies over the period from 2015 to 2024, employing Python 3.10 crawling to measure the degree of digital transformation and utilizing the entropy weight method to construct supply chain resilience. Using a moderated mediation model, this analysis examines how corporate innovation mediates the relationship between digital transformation and financial flexibility, and how supply chain resilience exerts a phased moderating effect along this pathway. The findings reveal the following: (1) Digital transformation has a positive effect on financial flexibility, where corporate innovation plays a mediating role. (2) The promoting effect of digital transformation on financial flexibility exhibits significant heterogeneity, varying with firm-specific micro-level characteristics and internal control quality. (3) Supply chain resilience plays a significant moderating role throughout the entire mediation path. It positively moderates the chain of “digital transformation → corporate innovation → financial flexibility”. This study provides empirical evidence on the mechanisms of digital transformation’s impact on corporate financial flexibility and offers a theoretical view for evaluating the outcomes of digital transformation from a financial perspective. Full article

(This article belongs to the Special Issue Supply Chain Uncertainties and Financial Outcomes)

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23 pages, 2523 KB

Open AccessFeature PaperArticle

Integrated Management of Air-Quality Monitoring Processes as a Framework for Disclosure Quality in Green Bond Markets

by Venera-Stanca Nicolici, Ahmed Adjal, Ioana Ionel and Eugenia Grecu

Int. J. Financ. Stud. 2026, 14(7), 168; https://doi.org/10.3390/ijfs14070168 - 2 Jul 2026

Viewed by 831

Abstract

In the last 10 years, the global green bond market has reached an estimated value of USD 6.8 trillion. However, credibility concerns persist due to greenwashing risks and issues regarding the reporting system. The current measurement, reporting, and verification systems (MRV) have high [...] Read more.

In the last 10 years, the global green bond market has reached an estimated value of USD 6.8 trillion. However, credibility concerns persist due to greenwashing risks and issues regarding the reporting system. The current measurement, reporting, and verification systems (MRV) have high uncertainty levels of 10–30%, and so they contribute to information asymmetries and fuel investor skepticism when allocating capital to green bond instruments. The scope of this study is to develop an integrated management approach that links air quality and greenhouse gas monitoring with financial incentives throughout the lifecycle of green bonds. The central contribution is a four-phase lifecycle model covering issuance, allocation, monitoring, and impact reporting, which systematically identifies where greenwashing risks and verification gaps arise across the investment cycle. Methodologically, the study combines qualitative content analysis, a novel Disclosure Quality Score (DQS) instrument, based on the Regulation (EU) 2023/2631, four documentary case studies, and an advanced verification framework. The content analysis shows that regulatory and market-performance studies dominate the literature, while integrated lifecycle verification frameworks remain less explored. The DQS uses eight indicators, applied to a matched sample of green bonds, in accordance with the European Green Bond Standard (EuGB) and the ICMA Green Bond Principles (GBP). The results demonstrate that bonds issued under the EuGB present higher disclosure quality (mean DQS = 15.4/16) compared to GBP-aligned bonds (mean DQS = 11.4/16). Case studies show strong issuance-stage disclosure, but weak post-issuance verification. The framework enables lifecycle-wide accountability by reducing information asymmetry. The proposed lifecycle framework and DQS instrument offer a replicable model for improving disclosure quality and ESG performance standards, with direct implications for sustainable investment screening and ESG fund selection. Overall, the findings show that improving green bond credibility requires moving beyond issuance-focused disclosure toward lifecycle-wide verification. Full article

(This article belongs to the Special Issue Investment and Sustainable Finance)

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30 pages, 1941 KB

Open AccessFeature PaperArticle

Does Government-Sponsored Mortgage Securitization Mitigate or Aggravate Financial Crises?

by Wayne Passmore and Roger W. Sparks

Int. J. Financ. Stud. 2026, 14(7), 167; https://doi.org/10.3390/ijfs14070167 - 1 Jul 2026

Viewed by 583

Abstract

This paper analyzes a model of the mortgage market, allowing for scenarios with and without government-sponsored mortgage securitization. Conventional wisdom says that securitization, by fostering diversification and creating a “safe” asset in the form of a mortgage-backed security (MBS), will reduce risk and [...] Read more.

This paper analyzes a model of the mortgage market, allowing for scenarios with and without government-sponsored mortgage securitization. Conventional wisdom says that securitization, by fostering diversification and creating a “safe” asset in the form of a mortgage-backed security (MBS), will reduce risk and enhance liquidity, thereby abating financial crises. Our contribution is to examine this claim by imbedding the mortgage market with a sequential strategic game played between the securitizer and banks. In this setting, adverse selection arises from the securitizer’s first-mover advantage rather than from informational asymmetries. In the model, the securitizer chooses the MBS contract terms, including the guaranteed rate and the criterion that qualifies a mortgage for securitization. Banks respond by selecting which qualifying mortgages to exchange for the MBS. Our analysis yields a central result: within this framework, government-sponsored securitization is, somewhat counterintuitively, more likely to exacerbate the severity and frequency of financial crises. This outcome arises in particular when mortgage demand is sufficiently low that originators optimally choose not to retain any higher-risk mortgages on their balance sheets. Full article

(This article belongs to the Topic The Future of Banking and Financial Risk Management)

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24 pages, 3311 KB

Open AccessArticle

The Impact of Political Signal Quality on the Dynamic Spillover of Fourth Industrial Revolution Assets

by Mohammed Alhashim

Int. J. Financ. Stud. 2026, 14(7), 166; https://doi.org/10.3390/ijfs14070166 - 29 Jun 2026

Viewed by 369

Abstract

This paper analyses the dynamics of connectedness among technology-oriented assets, such as fintech, blockchain, cybersecurity, internet, and disruptive technology indices, on the effect of political signal quality on the transmission of spillovers. Applying the Time-Varying Parameter Vector Autoregressive (TVP-VAR) model with frequency-based connectedness, [...] Read more.

This paper analyses the dynamics of connectedness among technology-oriented assets, such as fintech, blockchain, cybersecurity, internet, and disruptive technology indices, on the effect of political signal quality on the transmission of spillovers. Applying the Time-Varying Parameter Vector Autoregressive (TVP-VAR) model with frequency-based connectedness, the paper explores dynamic, horizon-dependent spillovers in the interconnection of innovation-based financial markets from January 2015 to April 2025. The findings show consistently high interconnectedness among 4IR assets, but this level increases significantly during the COVID-19 outbreak and the Russia–Ukraine conflict. It is also found that disruptive technology and fintech indices dominate shock transmission among interconnectedness networks. Based on the frequency decomposition approach, it is evident that spillovers arise from short-run dynamics, indicating that 4IR financial systems respond quickly to uncertainty shocks and to synchronized investor behavior. The regression and quantile regression analyses indicate a conditional effect of political signal quality on connectedness, especially during crisis periods marked by higher market uncertainty and stress. Specifically, it is evident that a deterioration in political signal quality increases spillover effects due to information uncertainty and expectation-based investor behavior. This means that, in an innovation-driven financial system, uncertainty is not just transmitted through macroeconomic and financial factors, but also through political communication and information uncertainty. In summary, this paper adds to the existing literature on connectedness by considering political information quality uncertainty in analyzing the 4IR financial system and by identifying how technological integration makes the financial market vulnerable during crises. Full article

(This article belongs to the Special Issue Financial Risk Management in Times of Geopolitical Uncertainty)

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Int. J. Financ. Stud., Volume 14, Issue 7 (July 2026) – 29 articles

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