Journal of Risk and Financial Management

24 pages, 1653 KB

Open AccessArticle

Conditional Effectiveness of Volatility-Adaptive Exit Rules in Algorithmic Trading Systems: Evidence from the USD/JPY Market

by Byung-Kook Kang

J. Risk Financial Manag. 2026, 19(8), 554; https://doi.org/10.3390/jrfm19080554 - 24 Jul 2026

Abstract

This study examines Average True Range (ATR)-based take-profit (TP) and stop-loss (SL) rules as components of adaptive risk-management design within robust algorithmic trading systems in the USD/JPY foreign exchange market. Rather than simply evaluating whether volatility-adaptive exit rules improve trading performance, the study [...] Read more.

This study examines Average True Range (ATR)-based take-profit (TP) and stop-loss (SL) rules as components of adaptive risk-management design within robust algorithmic trading systems in the USD/JPY foreign exchange market. Rather than simply evaluating whether volatility-adaptive exit rules improve trading performance, the study investigates the conditions under which they contribute to trading outcomes. To this end, the study adopts a systematic framework combining a broad Moving Average Convergence Divergence (MACD) parameter space with ATR-based TP/SL multiplier settings and distinguishes heterogeneous outcome patterns before and after ATR implementation. The results show that the effectiveness of ATR-based exit rules is conditional. Performance improvements occur only for specific combinations of model structures, exit-rule specifications, and market conditions. A notable finding is that optimizing trading-model parameters plays a primary role in determining the effectiveness of exit rules, while ATR-based exit rules function as complementary components that reinforce well-specified trading models. Moreover, under mildly mean-reverting market conditions, profit-enhancement cases expand across a broader range of optimized MACD parameter configurations, suggesting a previously underexplored interaction between market dynamics, model structure, and volatility-adaptive exit-rule design. Overall, the findings provide new evidence that the effectiveness of adaptive risk-management mechanisms depends on the interaction between model structure, exit-rule design, and market conditions, thereby offering broader insights into adaptive trading-system design under changing market conditions. For practitioners, the results suggest that adaptive ATR-based exit rules are most effective when combined with appropriately optimized trading models. Full article

(This article belongs to the Special Issue Financial Risk and Technological Innovation)

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25 pages, 2604 KB

Open AccessArticle

Rethinking Profitability Dynamics in the EU Banking Sector: An Explainable Machine Learning Approach to Bank Sector-Specific, Macroeconomic, and Institutional Quality Factors

by Gökhan Özkul, Özen Akçakanat and Ozan Özdemir

J. Risk Financial Manag. 2026, 19(8), 553; https://doi.org/10.3390/jrfm19080553 - 23 Jul 2026

Abstract

This study comprehensively examines the banking, macroeconomic, and institutional quality dynamics determining the return on equity (ROE) of the banking sector in 27 European Union countries over the 2014–2024 period. Adopting a purely explanatory framework rather than a predictive exercise, the primary aim [...] Read more.

This study comprehensively examines the banking, macroeconomic, and institutional quality dynamics determining the return on equity (ROE) of the banking sector in 27 European Union countries over the 2014–2024 period. Adopting a purely explanatory framework rather than a predictive exercise, the primary aim is to identify and rank the factors driving cross-country profitability variability. The traditional multiple linear regression (MLR) method and three machine learning models (CatBoost, Extra Trees, Gradient Boosting) are comparatively analyzed, with model transparency ensured via the Shapley Additive Explanations (SHAP) algorithm. Empirical findings provide evidence consistent with strong, non-linear interactions among profitability dynamics that traditional econometric models tend to overlook. Comparative analyses indicate that the best-performing CatBoost algorithm possesses notably higher explanatory power compared to the MLR model, an advantage that persists when the linear benchmark is augmented with country fixed effects. According to SHAP results, the non-performing loan (NPL) ratio is the most dominant factor eroding profitability. Conversely, inflation is associated with a positive impact on ROE through the repricing channel up to a certain threshold, after which its marginal contribution flattens, exhibiting a concave structure. These thresholds should be read as model-implied patterns within the present sample rather than as general economic constants. The direct explanatory power of the institutional quality indicators employed here—and of a principal-component composite of the broader governance set—remains relatively limited, suggesting an indirect role operating through macroeconomic channels. These findings, supported by leave-one-country-out (LOCO), fixed-effects, and lagged-regressor robustness checks, suggest that explainable machine learning offers a valuable analytical infrastructure for characterizing the asymmetric effects of macro-financial shocks on bank performance. Full article

(This article belongs to the Section Banking and Finance)

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21 pages, 704 KB

Open AccessArticle

Confidence, Risk Tolerance, and the Dual Role of Peer Influence in the Investment Decisions of Employed Women: A Structural Equation Model from Urban India

by Ramya Haravu Paramesh, Hemalatha Krishnamoorthy Gunasekaran and Deepak Raghava Naik

J. Risk Financial Manag. 2026, 19(8), 552; https://doi.org/10.3390/jrfm19080552 - 23 Jul 2026

Abstract

Although employed women represent one of the fastest-growing segments of the investor population in emerging economies, their investment decision-making is still largely modelled through fragmented, single-determinant frameworks that treat women as a homogeneous group. This study develops and tests an integrated structural model [...] Read more.

Although employed women represent one of the fastest-growing segments of the investor population in emerging economies, their investment decision-making is still largely modelled through fragmented, single-determinant frameworks that treat women as a homogeneous group. This study develops and tests an integrated structural model of financial-goal-directed investment orientation among employed women, drawing together Behavioural Finance Theory, the Theory of Planned Behaviour, and the Life-Cycle Hypothesis. Primary data were collected through a structured questionnaire from 951 employed women across the four administrative zones of Bengaluru, India, using stratified random sampling. The measurement model was validated through exploratory and confirmatory factor analysis, and four competing structural specifications were estimated by maximum likelihood; the best-fitting model was selected on the basis of the corrected Akaike Information Criterion and approximate fit indices. The results indicate that risk tolerance is the strongest direct correlate of financial-goal-directed investment orientation, that confidence and self-efficacy operates as the pivotal psychological mediator linking macroeconomic perception to risk-taking, and that market sentiments are the strongest external correlate of investor confidence. Peer influence shows a theoretically important dual association, positively related to risk tolerance while negatively related to confidence. A serial mediation pathway running from market sentiments through confidence and risk tolerance to financial goals is supported. Because the design is cross-sectional, the associations are interpreted as structural relationships consistent with the proposed theoretical framework rather than as established causal effects. This study is exploratory and hypothesis-generating in character. The findings reframe financial-inclusion interventions for employed women around confidence-building rather than information provision, with implications for product design, advisory practice, and policy. Full article

(This article belongs to the Special Issue Behaviour in Financial Decision-Making)

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25 pages, 1814 KB

Open AccessArticle

Evaluating Saudi Banks’ Financial Performance Using an Entropy–TOPSIS Framework

by Ziad Albaraki, Abdelhakim Abdelhadi and Talal Al-Sulaiman

J. Risk Financial Manag. 2026, 19(8), 551; https://doi.org/10.3390/jrfm19080551 - 23 Jul 2026

Abstract

As Saudi Arabia accelerates its Vision 2030 economic diversification, the domestic banking sector serves as the critical engine for capital deployment. However, evaluating these institutions is complicated by conflicting performance indicators, where high profitability is often offset by elevated market valuation multiples. This [...] Read more.

As Saudi Arabia accelerates its Vision 2030 economic diversification, the domestic banking sector serves as the critical engine for capital deployment. However, evaluating these institutions is complicated by conflicting performance indicators, where high profitability is often offset by elevated market valuation multiples. This study applies an objective, established multi-criteria decision-making (MCDM) framework—combining Shannon’s Entropy for objective weighting with TOPSIS for ranking—to evaluate ten major banks listed on the Saudi Stock Exchange (Tadawul), tracked by the Tadawul All Share Index (TASI), over the 2021–2025 period. The contribution is contextual and empirical rather than methodological: the systematic application of established objective MCDM methods to the Saudi banking sector during the pivotal Vision 2030 window, with an investor-oriented criterion set. Comparative validation was executed using the CRITIC weighting algorithm and the VIKOR ranking method, complemented by a four-dimensional sensitivity analysis (Weight Perturbation, Leave-One-Criterion-Out, Alternative Normalization, and Equal-Weight scenarios). Spearman correlation coefficients (>0.86) confirm that the framework produces empirically stable rankings resistant to methodological perturbation, providing policymakers and investors with a data-driven decision-support tool for the Saudi banking sector under Vision 2030. Full article

(This article belongs to the Special Issue Banking Stability and Management of Financial Institutions)

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22 pages, 1666 KB

Open AccessArticle

Pairing Uncertainty and Attention Indices to Explain Cryptocurrency Returns: Quantile and Causality Evidence

by Abdulrahman Alsamaani and Huda Aldhahi

J. Risk Financial Manag. 2026, 19(8), 550; https://doi.org/10.3390/jrfm19080550 - 23 Jul 2026

Abstract

Does the pricing of uncertainty in cryptocurrency markets depend on where in the return distribution one looks, and does investor attention carry information beyond uncertainty itself? We address these questions for ten cryptocurrencies spanning dominant and less-dominant coins over September 2018 to December [...] Read more.

Does the pricing of uncertainty in cryptocurrency markets depend on where in the return distribution one looks, and does investor attention carry information beyond uncertainty itself? We address these questions for ten cryptocurrencies spanning dominant and less-dominant coins over September 2018 to December 2021, using quantile regression, joint (multivariate) quantile regression, and Granger causality tests, together with a COVID-19 sub-sample. Grounding the analysis in the uncertainty- and attention-based asset-pricing literature, we test three hypotheses: that uncertainty is priced in the tails of the return distribution rather than at its centre; that cryptocurrency-specific uncertainty matters more than broad macroeconomic uncertainty; and that uncertainty and attention are complementary, so that pairing an uncertainty index with an attention index explains tail returns better than either index alone. The evidence supports all three. Single indices are largely irrelevant at the median but become influential in bear-market tails and over longer horizons; the cryptocurrency-specific UCRY indices dominate the broader macro proxies; and price-or-policy-plus-attention pairs show stronger and broader tail effects than either index alone, though part of this reflects the additional regressor in paired specifications. Causality runs mainly from indices to returns at longer horizons. The study shows that uncertainty is a tail phenomenon in cryptocurrency markets and that attention operates as a distinct, complementary channel. Full article

(This article belongs to the Special Issue The Future of Money: Central Bank Digital Currencies, Cryptocurrencies and Stablecoins, 2nd Edition)

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21 pages, 6728 KB

Open AccessArticle

Financial Inclusion and Sustainable Development: How Do Financial Literacy and Social Capital Mediate This Relationship?

by Sami Ullah, Resham Iftikhar, Muhammad Mohiuddin, Ijaz Hussain and Ishfaq Ahmad

J. Risk Financial Manag. 2026, 19(8), 549; https://doi.org/10.3390/jrfm19080549 - 23 Jul 2026

Abstract

This article investigates how mediating variables such as financial literacy and social capital can be used in the relationship between financial inclusion and sustainable development in the Pakistani educational sector. A quantitative survey design was used to gather data on educators, students, and [...] Read more.

This article investigates how mediating variables such as financial literacy and social capital can be used in the relationship between financial inclusion and sustainable development in the Pakistani educational sector. A quantitative survey design was used to gather data on educators, students, and stakeholders, in order to quantify financial inclusion, financial literacy, social capital, and sustainable development. Partial least squares structural equation modeling (PLS-SEM) was employed to analyze the proposed relationships with SmartPLS. The results show that there are positive and significant correlations between financial inclusion and financial literacy, along with social capital and sustainable development. The findings also indicate that the connection between financial inclusion and sustainable development is associated with financial literacy and social capital. The present study can be useful because it describes the connection between financial access and sustainable results—based on financial knowledge, trust, cooperation, and networks—and provides implications for policymakers, educators, and financial institutions in practice. Full article

(This article belongs to the Special Issue Emerging Trends and Innovations in Corporate Finance and Governance)

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23 pages, 455 KB

Open AccessArticle

Financial Literacy and FinTech Adoption as Drivers of Financial Behavior: Evidence from Fragile and Digitally Mature Economies

by Nada Jabbour Al Maalouf and Layal Sfeir

J. Risk Financial Manag. 2026, 19(8), 548; https://doi.org/10.3390/jrfm19080548 - 23 Jul 2026

Abstract

In an increasingly complex financial landscape, individual financial behavior is shaped by a range of cognitive, technological, and psychological factors. Existing research on financial behavior often examines financial literacy, FinTech adoption, and financial attitude separately, with limited attention to their combined effects or [...] Read more.

In an increasingly complex financial landscape, individual financial behavior is shaped by a range of cognitive, technological, and psychological factors. Existing research on financial behavior often examines financial literacy, FinTech adoption, and financial attitude separately, with limited attention to their combined effects or to whether these relationships remain consistent across contrasting economic environments. To address this gap, this study examines the associations of financial literacy and FinTech adoption with financial behavior, both directly and indirectly through the mediating role of financial attitude. Grounded in the Theory of Planned Behavior and the Technology Acceptance Model, the study proposes an integrated behavioral model using primary data from two contrasting contexts: Lebanon, a financially constrained and unstable environment, and the United Arab Emirates (UAE), a stable, high-income country with advanced FinTech infrastructure. Data were collected through a survey of 400 respondents and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that financial literacy and FinTech adoption are positively associated with financial behavior in both countries. Moreover, financial attitude significantly mediates both relationships. Measurement invariance was established prior to cross-country comparisons, and the multi-group analysis indicated that the structural relationships were generally comparable across Lebanon and the UAE despite descriptive differences in several path coefficients. The study contributes to the behavioral finance and sustainable finance literature by integrating cognitive, technological, and psychological predictors within a unified framework, validating the mediating role of financial attitude, and providing cross-national evidence from two contrasting economic contexts. The findings suggest that strengthening financial literacy alongside responsible FinTech adoption may support more sustainable and inclusive financial behaviors, particularly in environments characterized by economic instability and unequal access to financial services. Practical and policy implications are offered for educators, FinTech providers, financial institutions, and policymakers, emphasizing the importance of context-sensitive initiatives that promote financial resilience, financial inclusion, and the development of sustainable financial systems. Full article

(This article belongs to the Special Issue Fintech, Digital Finance, and Socio-Cultural Factors)

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18 pages, 3164 KB

Open AccessArticle

Machine-Readable Accountability: eXtensible Business Reporting Language, Artificial Intelligence, and the Institutional Rewriting of Accounting Judgement

by Alessio Faccia

J. Risk Financial Manag. 2026, 19(7), 547; https://doi.org/10.3390/jrfm19070547 - 22 Jul 2026

Abstract

Machine-readable financial reporting changes how corporate disclosures become visible, verified, and answerable. Inline eXtensible Business Reporting Language (Inline XBRL) combines a human-readable report with embedded structured data, while artificial intelligence expands automated extraction and screening. The study develops Machine-Readable Accountability as a bounded [...] Read more.

Machine-readable financial reporting changes how corporate disclosures become visible, verified, and answerable. Inline eXtensible Business Reporting Language (Inline XBRL) combines a human-readable report with embedded structured data, while artificial intelligence expands automated extraction and screening. The study develops Machine-Readable Accountability as a bounded socio-technical construct organised around dynamic visibility, distributed judgement, and responsibility displacement. A qualitative documentary analysis examines four primary archives: regulatory rules, official filing-evidence records, verification materials, and algorithmic-governance documents. Peer-reviewed studies serve as contextual framing and external corroboration. They do not form primary documentary observations. The corpus covers the mature United States Securities and Exchange Commission regime and the European Single Electronic Format from 2020 to July 2026, with earlier sources retained for historical grounding. A seven-family codebook guides analysis of classification, visibility, validation, judgement, audit, artificial intelligence, and accountability. Results arise from coded rules, official filing observations, assurance requirements, and cross-archive role mapping. Structured reporting reduces extraction costs, supports comparison, and permits automated quality checks. It also places institutional weight on taxonomy fit, extension design, validation logic, and software-mediated review. Documentary evidence supports the relocation of judgement across preparers, taxonomy designers, software vendors, auditors, and regulators. Evidence for deliberate narrative optimisation aimed at artificial intelligence remains indirect, so algorithmic answerability remains a bounded theoretical proposition. The framework links market-efficiency research with studies of quantification, professional judgement, and digital governance, and specifies controls for data lineage, extension approval, model documentation, human review, and responsibility assignment. Full article

(This article belongs to the Section Financial Technology and Innovation)

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29 pages, 445 KB

Open AccessArticle

Does ESG Performance Improve Corporate Profit Quality? Evidence from Chinese A-Share Listed Firms

by Wei Gao, Quan Fang and Ting Sun

J. Risk Financial Manag. 2026, 19(7), 546; https://doi.org/10.3390/jrfm19070546 - 21 Jul 2026

Abstract

In the context of advocating the high-quality development of companies, this study explores the mechanism underlying the relationship between ESG performance and profit quality (PQ) and the moderating effect of media reputation. Given the wide variety and large number of indicators of corporate [...] Read more.

In the context of advocating the high-quality development of companies, this study explores the mechanism underlying the relationship between ESG performance and profit quality (PQ) and the moderating effect of media reputation. Given the wide variety and large number of indicators of corporate profitability, establishing evaluation methods for assessing PQ presents a critical challenge. We adopted the game theory combination weight method to construct a multi-dimensional PQ evaluation system. Using a sample of Chinese A-share listed companies from 2011 to 2024, the study applies two-way fixed effects estimation and instrumental variable analysis to test study hypotheses. The research findings indicate that (1) ESG performance and its sub-dimensions positively influence PQ and that (2) media reputation positively moderates the relationship between ESG performance and PQ. We further discovered that different ESG dimensions have distinct effects on various dimensions of PQ. Therefore, this study contributes to the literature on ESG and PQ while providing practical guidance for companies pursuing high-quality development. Full article

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

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29 pages, 546 KB

Open AccessArticle

Green Bond Market Development and Fiscal Sustainability in the EU: Drivers of Market Entry and Depth

by Radosveta Krasteva-Hristova and Vanya Georgieva

J. Risk Financial Manag. 2026, 19(7), 545; https://doi.org/10.3390/jrfm19070545 - 21 Jul 2026

Abstract

Green bond markets have expanded rapidly across the European Union, but development remains uneven across Member States. Using a balanced EU-27 panel for 2021–2025, this study distinguishes sovereign market entry from the depth of the overall green debt market. Pooled Probit and Tobit [...] Read more.

Green bond markets have expanded rapidly across the European Union, but development remains uneven across Member States. Using a balanced EU-27 panel for 2021–2025, this study distinguishes sovereign market entry from the depth of the overall green debt market. Pooled Probit and Tobit estimates show that larger economies are substantially more likely to issue sovereign green bonds, whereas government debt and the budget balance are not significantly associated with entry. Market depth is positively associated with economic scale and a stronger budget balance, although the latter relationship partly overlaps with institutional quality. Environmental taxation is not significantly associated with market depth, providing no evidence of substitution for green debt financing. The findings support measures to lower entry costs and strengthen institutional capacity in smaller Member States. Full article

(This article belongs to the Section Sustainability and Finance)

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27 pages, 393 KB

Open AccessArticle

Complementarity Between Supply and Demand of Trade Credit in Firm Performance: Evidence from Europe

by Godfred Afrifa, Ahmad Alshehabi and Mariam Alsabah

J. Risk Financial Manag. 2026, 19(7), 544; https://doi.org/10.3390/jrfm19070544 - 21 Jul 2026

Abstract

Our study investigated the interaction of credit from suppliers (trade payables) and credit given to customers (trade receivables) in order to better understand how the reliance on credit from suppliers and credit given to customers interact with each other to affect firms’ performance. [...] Read more.

Our study investigated the interaction of credit from suppliers (trade payables) and credit given to customers (trade receivables) in order to better understand how the reliance on credit from suppliers and credit given to customers interact with each other to affect firms’ performance. Using a sample of 26,731 firm-year observations from 28 European countries, we found new empirical evidence that both trade payables and trade receivables have a more positive effect on firm performance than would be the case if their individual effects were considered in isolation; thus, a complementarity may exist between the credit from suppliers and credit given to customers, affecting firms’ performance. Interestingly, our results showed greater sensitivity to certain firm-specific characteristics. In particular, the interaction effect of trade payables and trade receivables was stronger for young firms, firms with growth potential, and financially constrained firms. Further analysis also revealed that the interaction effect of trade payables and trade receivables was stronger for small- and medium-sized enterprises (SMEs), and firms in countries with French/German legal origins, or countries with more debt-reliant bank-based economies. Full article

(This article belongs to the Section Business and Entrepreneurship)

25 pages, 15736 KB

Open AccessArticle

Improving Apartment Price Index Reliability Under Missing Transaction Data: Evidence from South Korea

by Uk Jo and Jae Goo Kim

J. Risk Financial Manag. 2026, 19(7), 543; https://doi.org/10.3390/jrfm19070543 - 20 Jul 2026

Abstract

In South Korea, apartments dominate the residential housing market, accounting for 67.5% of total housing transactions in the fourth quarter of 2018. With this figure continuing to rise, apartments are the most significant asset for many families. Consequently, precise and timely valuations are [...] Read more.

In South Korea, apartments dominate the residential housing market, accounting for 67.5% of total housing transactions in the fourth quarter of 2018. With this figure continuing to rise, apartments are the most significant asset for many families. Consequently, precise and timely valuations are crucial for stakeholders, including homeowners, buyers, and mortgage lenders. Traditionally, these stakeholders have relied on the qualitative judgments of certified real estate agents. Because of market opacity and low liquidity, agents often use a comparative approach, referencing the most recent transaction prices of nearby comparable apartments. However, this method is subjective, potentially biased, time-consuming, and costly. Our study seeks to offer a more objective and quantitative method for determining fair apartment prices in Korea, helping market participants make informed decisions. The prediction target is the monthly representative price of an apartment complex (the within-complex average of transaction prices), from which a complex-level price index is subsequently constructed; we distinguish this target from individual transaction prices throughout. By employing clustering methods to identify similar apartments and imputation techniques for missing values, our model demonstrates promising results, with a mean absolute percentage error as low as 5.38% in the worst-case (consecutive-mask) setting and 4.76% in the typical (random-mask) setting. Because the training (2006–2015) and test (2016–2022) periods are temporally disjoint, these figures reflect out-of-sample performance rather than in-sample fit. We further validate the resulting series against external references: it attains a 5.03% MAPE against actual transactions nationwide—outperforming the appraiser-based Kookmin Bank index (7.29%)—and, once aggregated, closely tracks the official KREB transaction-based index while becoming available earlier; complex-level Granger tests confirm that our series temporally leads the appraiser-based series about 1.5 times as often as the reverse. We also outline the missing-data assumptions under which the approach is valid. Full article

(This article belongs to the Section Financial Markets)

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22 pages, 334 KB

Open AccessArticle

Product Market Competition and Commodity Hedging: Evidence from the Metals Industry

by Phoompat Dangwung, Jay Junghun Lee and Junwoo Kim

J. Risk Financial Manag. 2026, 19(7), 542; https://doi.org/10.3390/jrfm19070542 - 20 Jul 2026

Abstract

This study examines the associations among product market competition, commodity hedging, and income smoothing in the metals industry. Using a text-based measure of competition intensity, we find that firms facing stronger competitive pressures are more likely to hedge commodity price risk. We also [...] Read more.

This study examines the associations among product market competition, commodity hedging, and income smoothing in the metals industry. Using a text-based measure of competition intensity, we find that firms facing stronger competitive pressures are more likely to hedge commodity price risk. We also find a positive association between commodity hedging and income smoothing through discretionary accruals, suggesting a complementary relationship in reducing performance volatility. Moreover, this positive association weakens as product market competition intensifies. Collectively, these results contribute to our understanding of the associations between product market competition, firms’ risk management, and financial reporting behavior. Full article

(This article belongs to the Special Issue Commodity Markets in Modern Finance: Structure, Behavior, Risk, and Global Dynamics)

24 pages, 343 KB

Open AccessArticle

Too Much of a Good Thing? ESG Disclosure, the Social Dimension, and Future Stock Price Crash Risk Evidence of a Nonlinear Effect from an Emerging Market

by Ngoc Toan Pham and Hieu Le Tran Trung

J. Risk Financial Manag. 2026, 19(7), 541; https://doi.org/10.3390/jrfm19070541 - 20 Jul 2026

Abstract

Whether environmental, social, and governance (ESG) disclosure stabilizes share prices or merely masks bad news, it remains unsettled, and the evidence is conspicuously weak whenever the relationship is assumed to be linear. This study revisits the question by allowing the effect of ESG [...] Read more.

Whether environmental, social, and governance (ESG) disclosure stabilizes share prices or merely masks bad news, it remains unsettled, and the evidence is conspicuously weak whenever the relationship is assumed to be linear. This study revisits the question by allowing the effect of ESG disclosure on future stock price crash risk to be nonlinear and by breaking down disclosure into its environmental, social, and governance components. Using an unbalanced panel of non-financial firms listed on the Ho Chi Minh Stock Exchange over 2018–2024, we estimate firm and year fixed effects models with firm-clustered standard errors, measuring one-year-ahead crash risk by negative conditional skewness (NCSKEW) and down-to-up volatility (DUVOL). Consistent with prior work, the linear association between overall ESG disclosure and crash risk is statistically insignificant. Once a quadratic term is introduced, however, a U-shaped relationship emerges, and dimension-level tests show that this curvature is driven almost entirely by social disclosure: the linear term is negative and the squared term positive and significant for both crash risk proxies, with turning points of 0.3316 (NCSKEW) and 0.2918 (DUVOL). The U shape is confirmed by the formal test of Lind and Mehlum for both proxies, is robust to additional profitability and valuation controls and, most strongly for NCSKEW, to panel-corrected and feasible-GLS estimators. Low variance inflation factors confirm that multicollinearity does not affect the estimates. The findings support a “too-much-of-a-good-thing” interpretation: social disclosure improves transparency and reduces crash risk up to a moderate threshold, beyond which incremental, hard-to-verify narrative disclosure becomes consistent with impression management and heightens crash risk. Because the turning point lies below the first quartile of social disclosure, most sample firms already operate where additional disclosure raises crash risk. This study reframes the ESG crash risk debate around the level and dimension of disclosure rather than its mere quantity. Full article

(This article belongs to the Special Issue ESG Integration in Financial Markets)

24 pages, 393 KB

Open AccessArticle

Environmental Sustainability, Financial Conditions, and Export Performance in Thailand’s Textile and Clothing Industry Under Trade Liberalization and the Post-ATC Era

by Sasawalai Tonsakunthaweeteam, Siwarit Pongsakornrungsilp, Pimlapas Pongsakornrungsilp, Rachawit Photiyarach, Salucknai Outtanasith and Vikas Kumar

J. Risk Financial Manag. 2026, 19(7), 540; https://doi.org/10.3390/jrfm19070540 - 20 Jul 2026

Abstract

This study investigates the impact of environmental factors, financial conditions, and trade-related policy on Thailand’s textile and clothing exports under the ASEAN–China Free Trade Agreement (ACFTA) and the WTO’s Agreement on Textiles and Clothing (ATC), focusing on export performance and trade creation between [...] Read more.

This study investigates the impact of environmental factors, financial conditions, and trade-related policy on Thailand’s textile and clothing exports under the ASEAN–China Free Trade Agreement (ACFTA) and the WTO’s Agreement on Textiles and Clothing (ATC), focusing on export performance and trade creation between 1990 and 2024, using strong panel data across 31 countries from 11 ASEAN–China member countries and 20 non-member countries. This study has been guided by Porter’s competitive advantage theory and the gravity trade framework. The analysis was conducted using STATA 18 to analyze the fixed-effects regression alongside a robust Poisson Pseudo-Maximum Likelihood (PPML) estimation. The results indicate that (1) improvements in environmental, trade, and financial conditions are associated with higher export performance, (2) the results do not support trade creation under ACFTA, with the estimated ACFTA coefficient being negatively associated with export volume, and (3) the post-ATC effect is not consistently supported across model specifications and is not statistically significant in the combined specification. The findings suggest that export performance is jointly influenced by these dimensions rather than by trade liberalization and the post-ATC agreement alone. We recommend that policymakers support firms in managing the transition costs associated with green production, strengthen international trade cooperation, and maintain macroeconomic stability to enhance the long-term export performance of Thailand’s textile and clothing industry. These findings provide evidence that environmental sustainability and macro-financial conditions remain important determinants of export performance under changing global trade conditions. Future research may incorporate additional variables, broader datasets, and alternative econometric approaches to further validate the robustness of the findings. Full article

(This article belongs to the Section Energy and Environment: Economics, Finance and Policy)

15 pages, 483 KB

Open AccessArticle

The Impact of Debt Maturity Structure on Financial Resilience: Evidence from Non-Financial Listed Firms on the Vietnamese Stock Market

by Nguyen Thi Hong Duyen, Le Quoc Diem and Nguyen Thao Hoa

J. Risk Financial Manag. 2026, 19(7), 539; https://doi.org/10.3390/jrfm19070539 - 20 Jul 2026

Abstract

How the maturity structure of corporate debt shapes firms’ capacity to withstand financial pressure remains understudied, particularly in bank-dependent emerging markets. This study examines whether greater reliance on short-term debt weakens firms’ ability to absorb financial shocks. Using quarterly panel data for non-financial [...] Read more.

How the maturity structure of corporate debt shapes firms’ capacity to withstand financial pressure remains understudied, particularly in bank-dependent emerging markets. This study examines whether greater reliance on short-term debt weakens firms’ ability to absorb financial shocks. Using quarterly panel data for non-financial listed firms on the Vietnamese stock market from 2015 to 2025, we construct an accounting-based measure of financial resilience (FR), defined as the ratio of earnings before interest, taxes, depreciation and amortization (EBITDA) to the sum of short-term debt and interest expense, and measure debt maturity structure (DMS) as the proportion of short-term debt in total interest-bearing debt. Firm fixed-effects models with quarterly time fixed effects and firm-clustered standard errors are used to estimate the relationship. The results consistently show that firms with a higher proportion of short-term interest-bearing debt exhibit significantly lower financial resilience across all model specifications. This negative relationship remains robust after controlling for alternative measures of financial leverage and using a logarithmic transformation of the dependent variable. The findings highlight the importance of debt maturity management as a key component of corporate financing strategy for firms and policymakers seeking to enhance financial resilience. Full article

(This article belongs to the Section Applied Economics and Finance)

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22 pages, 394 KB

Open AccessArticle

Integrating Rational Choice Theory into TOE Framework to Explain the Intention to Adopt Environmental Management Accounting: An Empirical Analysis in Vietnam

by Nguyen Thi Mai Anh

J. Risk Financial Manag. 2026, 19(7), 538; https://doi.org/10.3390/jrfm19070538 - 20 Jul 2026

Abstract

This study investigates the determinants of the intention to adopt Environmental Management Accounting (EMA) in Vietnam’s steel industry by integrating the Technology–Organization–Environment (TOE) framework with Rational Choice Theory (RCT). While prior research often assumes that external pressure is directly associated with EMA adoption, [...] Read more.

This study investigates the determinants of the intention to adopt Environmental Management Accounting (EMA) in Vietnam’s steel industry by integrating the Technology–Organization–Environment (TOE) framework with Rational Choice Theory (RCT). While prior research often assumes that external pressure is directly associated with EMA adoption, this study argues that such effects are contingent upon managerial evaluation of perceived net benefits (PNB). Using survey data from 420 respondents and applying Partial Least Squares Structural Equation Modeling (PLS-SEM), the empirical results show that top management support has the strongest associations with adoption intentions and PNB is the strongest predictor of adoption intention and serves as the theorized mediating variable. This suggests that EMA adoption is more associated with PNB, as firms are more likely to adopt EMA when its expected benefits are perceived to outweigh implementation costs, organizational risks, resource commitments, and operating burdens. Given the limitations of cross-sectional data, these findings represent theoretically grounded associations rather than conclusive causal inferences. This study refines TOE-based explanation by incorporating a rational-actor perspective, while providing practical guidance for steel-firm managers to integrate EMA into existing operational routines. Full article

(This article belongs to the Section Sustainability and Finance)

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20 pages, 3870 KB

Open AccessReview

Artificial Intelligence and Climate Risk in Finance: A Bibliometric Review of Emerging Trends and Analytical Frontiers

by Triana Arias Abelaira, María Jesús Guillén Palomino, Lázaro Rodríguez Ariza and Carlos Díaz Caro

J. Risk Financial Manag. 2026, 19(7), 537; https://doi.org/10.3390/jrfm19070537 - 20 Jul 2026

Abstract

This study analyses the evolution of the financial literature on climate risk, examining the integration of artificial intelligence techniques into its measurement and management. To this end, a bibliometric approach is employed based on 221 articles indexed in the Web of Science Core [...] Read more.

This study analyses the evolution of the financial literature on climate risk, examining the integration of artificial intelligence techniques into its measurement and management. To this end, a bibliometric approach is employed based on 221 articles indexed in the Web of Science Core Collection, using the Bibliometrix package. Moving beyond existing descriptive bibliometric reviews on ESG and green finance, the novelty of this paper lies in its analytical focus on how financial science operationalises quantitative AI mechanisms to price and integrate climate transition risk into asset and portfolio valuation. The structural analysis reveals that natural language processing (NLP) and digital transformation acting as driving motor themes, suggesting that the reviewed literature associates AI innovation policies with the mitigation of corporate greenwashing and enhance information transparency. Furthermore, while machine learning algorithms establish the cross-cutting predictive foundation for risk assessment, empirical evidence unveils a critical academic shift of traditional ‘financial performance’ towards a declining quadrant, indicating that empirical studies frequently find that that multi-phase investments in risk technologies do not yield immediate financial returns. Finally, the study maps a persistent geographical gap where emerging markets lack the data infrastructure of advanced economies, alongside isolated high-dimensional causal econometric niches like double machine learning. This analytical mapping provides key implications for global risk management and future quantitative research avenues. Full article

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

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21 pages, 1319 KB

Open AccessArticle

Do Recognized Intangible Assets Inform Bank Performance? Macro Digital Infrastructure as a Cross-Layer Condition in Indonesian Banking

by Yan Noviar Nasution and Donny Maha Putra

J. Risk Financial Manag. 2026, 19(7), 536; https://doi.org/10.3390/jrfm19070536 - 18 Jul 2026

Abstract

This study examines whether recognized intangible assets carry information about bank performance in an emerging market, and whether their information value is conditioned by the maturity of macro digital infrastructure. Using a balanced panel of 28 Indonesian commercial banks over 2015–2024 (280 firm-year [...] Read more.

This study examines whether recognized intangible assets carry information about bank performance in an emerging market, and whether their information value is conditioned by the maturity of macro digital infrastructure. Using a balanced panel of 28 Indonesian commercial banks over 2015–2024 (280 firm-year observations), we estimate two-way fixed-effects models with macro digital infrastructure, an economy-wide principal component index of internet penetration, mobile and broadband subscriptions, and electronic payment volume as a cross-layer moderator. Intangible investment intensity, proxied by the ratio of reported intangible assets to total assets, shows weak direct associations with performance; only the operating efficiency ratio displays a marginally significant short-run cost, consistent with transition-cost dynamics. The central result is conditional: the interaction between intangible intensity and macro digital maturity is strongly significant for operating efficiency (β = −2.587, p = 0.005), with the implied efficiency cost contracting by a model-implied 88 percent across the observed range of digital maturity (an estimate computed from the estimated coefficients over the observed sample variation, not a structural causal magnitude). Heterogeneity is pronounced across regulator-defined bank tiers (KBMI): the four largest banks realize positive profitability effects, whereas mid-tier banks bear transition costs. Results are robust to Driscoll–Kraay standard errors, system GMM, sub-sample splits, and outlier exclusion. The findings show that the information value of recognized intangibles in banking is state-contingent, extending the intangible-asset and digitalization literature to emerging-market banking. Full article

(This article belongs to the Section Banking and Finance)

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