International Journal of Financial Studies

25 pages, 1142 KiB

Open AccessArticle

Has US (Un)Conventional Monetary Policy Affected South African Financial Markets in the Aftermath of COVID-19? A Quantile–Frequency Connectedness Approach

by Mashilana Ngondo and Andrew Phiri

Int. J. Financial Stud. 2025, 13(3), 153; https://doi.org/10.3390/ijfs13030153 - 23 Aug 2025

Abstract

The US has undertaken both unconventional and conventional monetary policy stances in response to the COVID-19 pandemic and the Ukraine–Russia conflict, and there has been much debate on the effects of these various monetary policies on global financial markets. Our study considers the [...] Read more.

The US has undertaken both unconventional and conventional monetary policy stances in response to the COVID-19 pandemic and the Ukraine–Russia conflict, and there has been much debate on the effects of these various monetary policies on global financial markets. Our study considers the debate in the context of South Africa and uses the quantile–frequency connectedness approach to examine static and dynamic systemic spillover between the US shadow short rate (SSR) and South African equity, bond and currency markets between 1 December 2019 and 2 March 2023. The findings from the static analysis reveal that systemic connectedness is concentrated at their tail-end quantile distributions and US monetary policy plays a dominant role in transmitting these systemic shocks, albeit these shocks are mainly high frequency with very short cycles. However, the dynamic estimates further reveal that US monetary policy exerts longer-lasting spillover shocks to South African financial markets during periods corresponding to FOMC announcements of quantitative ‘easing’ or ‘tapering’ policies. Overall, these findings are useful for evaluating the effectiveness of the Reserve Bank’s macroprudential policies in ensuring market efficiency, as well as for enhancing investor decisions, portfolio allocation and risk management. Full article

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24 pages, 748 KiB

Open AccessArticle

When Models Fail: Credit Scoring, Bank Management, and NPL Growth in the Greek Recession

by Vasileios Giannopoulos and Spyridon Kariofyllas

Int. J. Financial Stud. 2025, 13(3), 152; https://doi.org/10.3390/ijfs13030152 - 22 Aug 2025

Abstract

The significant increase in non-performing loans (NPLs) during the escalating recession of the Greek economy motivates us to study the predictive power of credit rating models in periods of economic shocks. In parallel, we examined the responsibilities of bank management in the expansion [...] Read more.

The significant increase in non-performing loans (NPLs) during the escalating recession of the Greek economy motivates us to study the predictive power of credit rating models in periods of economic shocks. In parallel, we examined the responsibilities of bank management in the expansion of NPLs in this adverse environment. Certain studies connect bad loans with turbulent conditions. Our paper weighs the relative significance of both economic shock and management effectiveness using data at an individual level, which provides the originality of our study. We use a unique dataset of small business loans that were granted during 2005 (expansion period) by a large commercial Greek bank, and we explore their performance between 2010 and 2012 (early recession period). In the context of a stepwise methodology, we compare the Bank’s credit scoring model with three other prediction models (binomial logistic regression, decision tree, and multilayer perceptron neural network) to check both the predictive ability of credit scoring models during recession and the effectiveness of bank management. The comparative analysis confirms the management’s responsibilities in granting NPLs, since the Bank’s model exhibited the worst predictive performance. Additionally, we find that adverse external conditions lead to an increase in NPLs and decrease the predictive performance of all credit scoring models. The study offers a reliable methodological tool for lending management in economic downturns. Full article

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29 pages, 13156 KiB

Open AccessArticle

Exchange Rate Forecasting: A Deep Learning Framework Combining Adaptive Signal Decomposition and Dynamic Weight Optimization

by Xi Tang and Yumei Xie

Int. J. Financial Stud. 2025, 13(3), 151; https://doi.org/10.3390/ijfs13030151 - 22 Aug 2025

Abstract

Accurate exchange rate forecasting is crucial for investment decisions, multinational corporations, and national policies. The nonlinear nature and volatility of the foreign exchange market hinder traditional forecasting methods in capturing exchange rate fluctuations. Despite advancements in machine learning and signal decomposition, challenges remain [...] Read more.

Accurate exchange rate forecasting is crucial for investment decisions, multinational corporations, and national policies. The nonlinear nature and volatility of the foreign exchange market hinder traditional forecasting methods in capturing exchange rate fluctuations. Despite advancements in machine learning and signal decomposition, challenges remain in high-dimensional data handling and parameter optimization. This study mitigates these constraints by introducing an innovative enhanced prediction framework that integrates the optimal complete ensemble empirical mode decomposition with adaptive noise (OCEEMDAN) method and a strategically optimized combination weight prediction model. The grey wolf optimizer (GWO) is employed to autonomously modify the noise parameters of OCEEMDAN, while the zebra optimization algorithm (ZOA) dynamically fine-tunes the weights of predictive models—Bi-LSTM, GRU, and FNN. The proposed methodology exhibits enhanced prediction accuracy and robustness through simulation experiments on exchange rate data (EUR/USD, GBP/USD, and USD/JPY). This research improves the precision of exchange rate forecasts and introduces an innovative approach to enhancing model efficacy in volatile financial markets. Full article

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24 pages, 2329 KiB

Open AccessArticle

Monetary Policy Tightening and Financial Market Reactions: A Comparative Analysis of Soft and Hard Landings

by Gimede Gigante, Fernando Piccolantonio and Francesca Scarlini

Int. J. Financial Stud. 2025, 13(3), 150; https://doi.org/10.3390/ijfs13030150 - 22 Aug 2025

Abstract

This paper investigates the macro-financial consequences of recent monetary policy tightening cycles, focusing on the distinction between soft and hard landings. Using an OLS regression framework applied to U.S. and Euro Area data from 1994 to 2023, we analyze the response of equity [...] Read more.

This paper investigates the macro-financial consequences of recent monetary policy tightening cycles, focusing on the distinction between soft and hard landings. Using an OLS regression framework applied to U.S. and Euro Area data from 1994 to 2023, we analyze the response of equity and bond markets, inflation, and GDP growth to central bank interest rate hikes. The findings suggest that, in most past tightening episodes, central banks succeeded in engineering soft landings without severe disruptions to market conditions or economic growth. However, the current post-pandemic context may lead to a two-stage adjustment, as inflation persistence and geopolitical shocks alter standard transmission dynamics. The study contributes to the ongoing policy debate on the timing and intensity of rate hikes, offering historical insights and empirical evidence from capital market signals. Full article

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20 pages, 324 KiB

Open AccessArticle

Evolutions in the Financial Reporting Quality: A Comparative Analysis of Romanian Companies Listed on the Bucharest Stock Exchange

by Costel Istrate

Int. J. Financial Stud. 2025, 13(3), 149; https://doi.org/10.3390/ijfs13030149 - 20 Aug 2025

Abstract

The permanent evolution of accounting and financial reporting standards, in particular for listed companies, is justified by the need to adapt these standards to economic, societal, financial, institutional and technological developments. The main objective of the standard setters is that the financial statements [...] Read more.

The permanent evolution of accounting and financial reporting standards, in particular for listed companies, is justified by the need to adapt these standards to economic, societal, financial, institutional and technological developments. The main objective of the standard setters is that the financial statements reflect as closely as possible the reality of the entities they describe. The Romanian financial market (Bucharest Stock Exchange—BSE) has two segments: the regulated market, where, since 2012, IFRS are mandatory for the individual financial statements, and the alternative market AeRo, where the Romanian standards (RAS) are applied. This structure allows us to compare a financial reporting quality (FRQ) score, first, longitudinally (IFRS period 2012–2023 vs. non-IFRS period 2000–2011, for companies listed on the regulated market) and, second, IFRS observations (regulated market) vs. RAS observations (alternative market), for the same period (2012–2023). Following and partially replicating a methodology found in the literature, this study found that FRQ scores over the analyzed periods show us an increase in FRQ in the case of IFRS application, but also a favorable evolution of FRQ score for RAS observation. The evolution of accounting rules (including the transition from RAS to IFRS) is important, but the enforcement of the application of the reporting standards and other factors could have a significant impact on the quality of financial reporting. Full article

18 pages, 447 KiB

Open AccessArticle

Islamic vs. Conventional Banking in the Age of FinTech and AI: Evolving Business Models, Efficiency, and Stability (2020–2024)

by Abdelrhman Meero

Int. J. Financial Stud. 2025, 13(3), 148; https://doi.org/10.3390/ijfs13030148 - 19 Aug 2025

Abstract

This study explores how FinTech and artificial intelligence (AI) adoption shape efficiency and financial stability in dual-banking systems. It focuses on 26 listed Islamic and conventional banks across 11 countries in the MENA and Southeast Asia regions between 2020 and 2024. To measure [...] Read more.

This study explores how FinTech and artificial intelligence (AI) adoption shape efficiency and financial stability in dual-banking systems. It focuses on 26 listed Islamic and conventional banks across 11 countries in the MENA and Southeast Asia regions between 2020 and 2024. To measure digital adoption, we create a seven-component FinTech Adoption Index. We use fixed-effects regressions to examine its impact on cost efficiency, profitability, solvency stability, and credit risk. This analysis also controls bank size, capitalization, and macroeconomic conditions. The results show a clear adoption gap. Conventional banks consistently score 0.5–0.8 points higher on the FinTech Index compared to Islamic banks. Each additional FinTech component raised operating costs by about 0.8%, but improved profitability slightly by only 0.03%. This suggests that technological integration creates upfront costs before any real efficiency gains are seen. However, the stability benefits are stronger. FinTech adoption increases the Z-score by 3.6 points and lowers the non-performing loan ratio by 0.1%. Islamic banks gain more stability benefits due to their risk-sharing contracts and asset-backed financing structures. Overall, an efficiency–stability trade-off emerges. Conventional banks focus more on profitability, while Islamic banks gain resilience, but face slower efficiency improvements. By combining the Resource-Based View and Financial Stability Theory, this study provides the first multi-country evidence of how governance structures shape digital transformation in dual-banking markets. The findings offer practical guidance for regulators and bank managers around balancing innovation, efficiency, and stability. Full article

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23 pages, 701 KiB

Open AccessArticle

ESG Rating Divergence and Stock Price Crash Risk

by Chuting Zhang and Wei-Ling Hsu

Int. J. Financial Stud. 2025, 13(3), 147; https://doi.org/10.3390/ijfs13030147 - 19 Aug 2025

Abstract

ESG has emerged as a key non-financial indicator, drawing significant investor focus. Disparities in ESG ratings may skew investor perceptions, potentially endangering stock values and financial market stability. This paper examines the link between ESG rating divergences and stock price crash risk, drawing [...] Read more.

ESG has emerged as a key non-financial indicator, drawing significant investor focus. Disparities in ESG ratings may skew investor perceptions, potentially endangering stock values and financial market stability. This paper examines the link between ESG rating divergences and stock price crash risk, drawing on data from six Chinese and global ESG rating agencies. Focusing on Shanghai and Shenzhen A-share listed firms, it analyzes information from 2015 to 2022 within the theoretical contexts of information asymmetry and external monitoring. This study finds that ESG rating divergence markedly elevates stock price crash risk, a relationship that persists through a series of robustness checks. Specifically, the mechanisms operate through two key pathways: increased reputational damage risk due to information asymmetry and reduced external monitoring due to weakened external governance. The results of the heterogeneity analysis indicate that ESG rating divergence exacerbates stock price crash risk more significantly for non-state-owned firms, firms with low levels of marketization, and firms in high-pollution industries. This study provides clear actionable strategic paths and policy intervention points for investors to avoid risks, firms to optimize management, and regulators to formulate policies. Full article

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30 pages, 1592 KiB

Open AccessArticle

The Role of Accounting Conservatism in the Decreasing Book Equity of U.S. Firms

by Haowen Luo, Bing Luo and S. Drew Peabody

Int. J. Financial Stud. 2025, 13(3), 146; https://doi.org/10.3390/ijfs13030146 - 19 Aug 2025

Abstract

We offer a novel explanation for the widespread decline in U.S. firms’ reported book equity. We find that accounting conservatism is negatively associated with book equity, a result that is both economically and statistically significant, as well as robust to a variety of [...] Read more.

We offer a novel explanation for the widespread decline in U.S. firms’ reported book equity. We find that accounting conservatism is negatively associated with book equity, a result that is both economically and statistically significant, as well as robust to a variety of model specifications. Our findings suggest that the rise in accounting conservatism has significantly contributed to the declines in book equity over the decades. Full article

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24 pages, 566 KiB

Open AccessArticle

Liquidity Drivers in Illiquid Markets: Evidence from Simulation Environments with Heterogeneous Agents

by Lars Fluri, Ahmet Ege Yilmaz, Denis Bieri, Thomas Ankenbrand and Aurelio Perucca

Int. J. Financial Stud. 2025, 13(3), 145; https://doi.org/10.3390/ijfs13030145 - 18 Aug 2025

Abstract

This study investigates the liquidity dynamics in non-traditional financial markets by simulating trading environments for fractional ownership of illiquid alternative investments, grounded in empirical tick data from a Swiss FinTech platform covering December 2022 to June 2024. The research translates an operational digital [...] Read more.

This study investigates the liquidity dynamics in non-traditional financial markets by simulating trading environments for fractional ownership of illiquid alternative investments, grounded in empirical tick data from a Swiss FinTech platform covering December 2022 to June 2024. The research translates an operational digital secondary market into a heterogeneous agent-based simulation model within the theoretical framework of market microstructure and complex systems theory. The main objective is to assess whether a simple agent-based model (ABM) can replicate empirical liquidity patterns and to evaluate how market rules and parameter changes influence simulated liquidity distributions. The findings show that (i) the simulated liquidity closely matches empirical distributions not only in mean and variance but also in higher-order moments; (ii) the ABM reproduces key stylized facts observed in the data; and (iii) seemingly simple interventions in market rules can have unintended consequences on liquidity due to the complex interplay between agent behavior and trading mechanics. These insights have practical implications for digital platform designers, investors, and regulators, highlighting the importance of accounting for agent heterogeneity and endogenous market dynamics when shaping secondary market structures. Full article

(This article belongs to the Special Issue Market Microstructure and Liquidity)

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31 pages, 891 KiB

Open AccessArticle

Corporate Digital Transformation and Capacity Utilization Rate: The Functionary Path via Technological Innovation

by Yang Liu, Hongyan Zhang, Xiang Gao and Yanxiang Xie

Int. J. Financial Stud. 2025, 13(3), 144; https://doi.org/10.3390/ijfs13030144 - 7 Aug 2025

Abstract

The rapid development of digital technology is reshaping the global economic landscape. However, its impact on firms’ capacity utilization rate (CUR), particularly through technological innovation, remains unclear. This study investigates this issue by developing an endogenous growth model that connects digital technology to [...] Read more.

The rapid development of digital technology is reshaping the global economic landscape. However, its impact on firms’ capacity utilization rate (CUR), particularly through technological innovation, remains unclear. This study investigates this issue by developing an endogenous growth model that connects digital technology to CUR. The empirical analysis is based on data from Chinese A-share manufacturing firms. The methods employed include quantile regression, instrumental variable techniques, and various tests to explore underlying mechanisms. CUR is calculated using a special model that looks at random variations, and digital transformation is assessed using text analysis powered by machine learning. The findings indicate that digital transformation significantly enhances CUR, especially for firms with average capacity utilization levels, but has a limited effect on low- and high-end firms. Moreover, technological innovation mediates this relationship; however, factors like “double arbitrage” (involving policy and capital markets) and “herd effects” tend to prioritize quantity over quality, which constrains innovation potential. Improvements in CUR lead to enhanced firm performance and productivity, generating industry spillovers and demonstrating the broader economic externalities of digitalization. This study uniquely applies endogenous growth theory to examine the role of digital transformation in optimizing CUR. It introduces the “quantity-quality” technology innovation paradox as a crucial mechanism and highlights industry spillovers to address overcapacity while offering insights for fostering sustainable economic and social development in emerging markets. Full article

(This article belongs to the Special Issue New Quality Productive Forces: The Role of Green Finance and Artificial Intelligence in Finance)

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30 pages, 20256 KiB

Open AccessArticle

From Fields to Finance: Dynamic Connectedness and Optimal Portfolio Strategies Among Agricultural Commodities, Oil, and Stock Markets

by Xuan Tu and David Leatham

Int. J. Financial Stud. 2025, 13(3), 143; https://doi.org/10.3390/ijfs13030143 - 6 Aug 2025

Abstract

In this study, we investigate the return propagation mechanism, hedging effectiveness, and portfolio performance across several common agricultural commodities, crude oil, and S&P 500 index, ranging from July 2000 to June 2024 by using a time-varying parameter vector autoregression (TVP-VAR) connectedness approach and [...] Read more.

In this study, we investigate the return propagation mechanism, hedging effectiveness, and portfolio performance across several common agricultural commodities, crude oil, and S&P 500 index, ranging from July 2000 to June 2024 by using a time-varying parameter vector autoregression (TVP-VAR) connectedness approach and three common multiple assets portfolio optimization strategies. The empirical results show that, the total connectedness peaked during the 2008 global financial crisis, followed by the European debt crisis and the COVID-19 pandemic, while it remained relatively lower at the onset of the Russia-Ukraine conflict. In the transmission mechanism, commodities and S&P 500 index exhibit distinct and dynamic characteristics as transmitters or receivers. Portfolio analysis reveals that, with exception of the COVID-19 pandemic, all three dynamic portfolios outperform the S&P 500 benchmark across major global crises. Additionally, the minimum correlation and minimum connectedness strategies are superior than transitional minimum variance method in most scenarios. Our findings have implications for policymakers in preventing systemic risk, for investors in managing portfolio risk, and for farmers and agribusiness enterprises in enhancing economic benefits. Full article

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22 pages, 288 KiB

Open AccessArticle

An X-Ray Using NLP Techniques of Financial Reporting Quality in Central and Eastern European Countries

by Tatiana Dănescu and Roxana Maria Stejerean

Int. J. Financial Stud. 2025, 13(3), 142; https://doi.org/10.3390/ijfs13030142 - 6 Aug 2025

Abstract

This study assesses the quality of financial reporting in ten Central and Eastern European countries using a methodology based on natural language processing (NLP) techniques. 570 annual reports of companies listed on the main index on the stock exchanges of 10 Central and [...] Read more.

This study assesses the quality of financial reporting in ten Central and Eastern European countries using a methodology based on natural language processing (NLP) techniques. 570 annual reports of companies listed on the main index on the stock exchanges of 10 Central and Eastern European (CEE) countries, over the period 2019–2023, were evaluated to determine the degree of convergence of the following four measurable qualitative characteristics: relevance, exact representation, comparability and understandability. The main objective is to identify consistency in the quality of accounting information based on the application of an international financial reporting framework. The applied methodology eliminates subjective variability by implementing a standardized scoring system, aligned with the criteria developed by NiCE, using libraries such as spaCy and NLTK for term extraction, respective sentiment analysis and word frequency evaluation. The results reveal significant heterogeneity in all characteristics examined, with statistical tests confirming substantial differences between countries. The investigation of relevance revealed partial convergence, with three dimensions achieving complete uniformity, while the exact representation showed the highest variability. The assessment of comparability showed a significant difference between countries’ extreme values, and in terms of comprehensibility a formalistic approach was evident, with technical dimensions outweighing user-oriented aspects. The overall quality index varied significantly across countries, with a notable average deterioration in 2023, indicating structural vulnerabilities in financial reporting systems. These findings support initial hypotheses on the lack of homogeneity in the quality of financial reporting in the selected region, despite the implementation of international standards. Full article

26 pages, 344 KiB

Open AccessArticle

The Impact of Green Bond Issuance on Corporate Environmental and Financial Performance: An Empirical Study of Japanese Listed Firms

by Yutong Bai

Int. J. Financial Stud. 2025, 13(3), 141; https://doi.org/10.3390/ijfs13030141 - 1 Aug 2025

Abstract

Based on firm-level data of Japanese listed companies for the period of 2013–2022, this study conducts an empirical analysis to investigate how the issuance of green bonds influences corporate environmental and financial performance. The results show that the green bond issuance demonstrates a [...] Read more.

Based on firm-level data of Japanese listed companies for the period of 2013–2022, this study conducts an empirical analysis to investigate how the issuance of green bonds influences corporate environmental and financial performance. The results show that the green bond issuance demonstrates a reduction in corporate greenhouse gas emission intensity and energy consumption intensity in the long term. Moreover, the issuance of green bonds enhances the financial performance of firms in the long run. However, the positive effect of green bond issuance on corporate environmental and financial performance is significant only among firms that have set specific quantitative environmental targets. In addition, for manufacturing and transportation green bond issuers that have set specific quantitative environmental targets, the improvement in environmental performance is evident in both the long and short term. Full article

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

16 pages, 263 KiB

Open AccessArticle

Hospitality in Crisis: Evaluating the Downside Risks and Market Sensitivity of Hospitality REITs

by Davinder Malhotra and Raymond Poteau

Int. J. Financial Stud. 2025, 13(3), 140; https://doi.org/10.3390/ijfs13030140 - 1 Aug 2025

Abstract

This study evaluates the risk-adjusted performance of Hospitality REITs using multi-factor asset pricing models and downside risk measures with the aim of assessing their diversification potential and crisis sensitivity. Unlike prior studies that examine REITs in aggregate, this study isolates Hospitality REITs to [...] Read more.

This study evaluates the risk-adjusted performance of Hospitality REITs using multi-factor asset pricing models and downside risk measures with the aim of assessing their diversification potential and crisis sensitivity. Unlike prior studies that examine REITs in aggregate, this study isolates Hospitality REITs to explore their unique cyclical and macroeconomic sensitivities. This study looks at the risk-adjusted performance of Hospitality Real Estate Investment Trusts (REITs) in relation to more general REIT indexes and the S&P 500 Index. The study reveals that monthly returns of Hospitality REITs increasingly move in tandem with the stock markets during financial crises, which reduces their historical function as portfolio diversifiers. Investing in Hospitality REITs exposes one to the hospitality sector; however, these investments carry notable risks and provide little protection, particularly during economic upheavals. Furthermore, the study reveals that Hospitality REITs underperform on a risk-adjusted basis relative to benchmark indexes. The monthly returns of REITs show significant volatility during the post-COVID-19 era, which causes return-to-risk ratios to be below those of benchmark indexes. Estimates from multi-factor models indicate negative alpha values across conditional models, indicating that macroeconomic variables cause unremunerated risks. This industry shows great sensitivity to market beta and size and value determinants. Hospitality REITs’ susceptibility comes from their showing the most possibility for exceptional losses across asset classes under Value at Risk (VaR) and Conditional Value at Risk (CvaR) downside risk assessments. The findings have implications for investors and portfolio managers, suggesting that Hospitality REITs may not offer consistent diversification benefits during downturns but can serve a tactical role in procyclical investment strategies. Full article

20 pages, 1978 KiB

Open AccessReview

Banking Profitability: Evolution and Research Trends

by Francisco Sousa and Luís Almeida

Int. J. Financial Stud. 2025, 13(3), 139; https://doi.org/10.3390/ijfs13030139 - 29 Jul 2025

Abstract

This study aims to map the scientific knowledge of bank profitability and its determinants. It identifies trends and gaps in existing research through a bibliometric analysis. To this end, 634 documents published in the Web of Science database over the last 54 years [...] Read more.

This study aims to map the scientific knowledge of bank profitability and its determinants. It identifies trends and gaps in existing research through a bibliometric analysis. To this end, 634 documents published in the Web of Science database over the last 54 years were analyzed using the bibliometric package. The results indicate an increase in the volume of publications following the 2008 financial crisis, focusing on analyzing the factors influencing bank profitability and economic growth. The Journal of Banking and Finance is the preeminent publication in this field. The literature reviewed shows that bank profitability depends on internal factors (size, credit risk, liquidity, efficiency, and management) and external factors (such as GDP, inflation, interest rates, and unemployment). In addition to the traditional determinants, the recent literature highlights the importance of innovation and technological factors such as digitalization, mobile banking, and electronic payments as relevant to bank profitability. ESG (environmental, social, and governance) and governance indicators, which are still emerging but have been extensively researched in companies, indicate a need for evidence in this area. This paper also provides relevant insights for the formulation of monetary policy and the strategic formulation of banks, helping managers and owners to improve bank performance. It also provides directions for future empirical studies and research collaborations in this field. Full article

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29 pages, 498 KiB

Open AccessArticle

Modeling the Determinants of Stock Market Investment Intention and Behavior Among Studying Adults: Evidence from University Students Using PLS-SEM

by Dostonbek Eshpulatov, Gayrat Berdiev and Andrey Artemenkov

Int. J. Financial Stud. 2025, 13(3), 138; https://doi.org/10.3390/ijfs13030138 - 25 Jul 2025

Abstract

The development of stock markets is pivotal for economic growth, particularly through the mobilization of idle resources into productive investments. Despite recent reforms to enhance Uzbekistan’s capital market, public engagement remains limited. This study examines the behavioral determinants of stock market investment intention [...] Read more.

The development of stock markets is pivotal for economic growth, particularly through the mobilization of idle resources into productive investments. Despite recent reforms to enhance Uzbekistan’s capital market, public engagement remains limited. This study examines the behavioral determinants of stock market investment intention and participation among university students, employing the Theory of Planned Behavior (TPB) and Partial Least Squares Structural Equation Modeling (PLS-SEM). The model investigates the influence of digital literacy, financial literacy, social interaction, herding behavior, overconfidence bias, risk tolerance, and financial well-being on investment intention and behavior. A survey of 369 university students was conducted to assess the proposed relationships. The results reveal that risk tolerance, overconfidence bias, and herding behavior significantly and positively affect investment intention, while digital literacy demonstrates a notable negative effect, suggesting caution in assuming technology readiness automatically translates to investment readiness. Investment intention, in turn, strongly predicts actual participation and mediates several of these effects. Conversely, financial literacy, financial well-being, and social interaction showed no significant direct or mediating influence. Additionally, differences according to gender and academic background were observed in how intention translates into behavior. The findings underscore the need for integrated financial and behavioral education to enhance market participation and contribute to policy discourse on youth financial engagement in emerging economies. Full article

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20 pages, 4490 KiB

Open AccessArticle

Mapping Trends in Green Finance: A Bibliometric and Topic Modeling Analysis

by Orlando Joaqui-Barandica, Jesús Heredia-Carroza, Sebastian López-Estrada and Daniela-Tatiana Agheorghiesei

Int. J. Financial Stud. 2025, 13(3), 137; https://doi.org/10.3390/ijfs13030137 - 25 Jul 2025

Abstract

This study presents a comprehensive bibliometric and topic modeling analysis of the academic literature on green and sustainable finance. Using 1372 peer-reviewed articles indexed in the Web of Science up to 2024, we identify key publication trends, influential authors, prominent journals, and thematic [...] Read more.

This study presents a comprehensive bibliometric and topic modeling analysis of the academic literature on green and sustainable finance. Using 1372 peer-reviewed articles indexed in the Web of Science up to 2024, we identify key publication trends, influential authors, prominent journals, and thematic clusters shaping the field. The analysis reveals an exponential growth in publications since 2017 and highlights the dominance of journals such as Journal of Sustainable Finance & Investment and Sustainability. Text mining techniques, including TF-IDF and Latent Dirichlet Allocation (LDA), are applied to abstracts to extract the most relevant terms and classify articles into four latent topics. The findings suggest a growing focus on the impact of green finance on carbon emissions, energy efficiency, and firm performance, particularly in the context of China. This study offers valuable insights for researchers and policymakers by mapping the intellectual structure and identifying emerging research frontiers in the rapidly evolving field of green finance. Full article

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26 pages, 333 KiB

Open AccessFeature PaperArticle

Financial Discrimination: Consumer Perceptions and Reactions

by Miranda Reiter, Di Qing, Kenneth White and Morgen Nations

Int. J. Financial Stud. 2025, 13(3), 136; https://doi.org/10.3390/ijfs13030136 - 24 Jul 2025

Abstract

Access to traditional financial institutions plays a key role in enhancing positive financial outcomes. However, some consumers within the United States experience discrimination from these same institutions. In particular, discrimination based on race and gender has historically been tied to outcomes such as [...] Read more.

Access to traditional financial institutions plays a key role in enhancing positive financial outcomes. However, some consumers within the United States experience discrimination from these same institutions. In particular, discrimination based on race and gender has historically been tied to outcomes such as lower service quality and a lack of access to credit. While the previous literature has discussed some of the discriminatory practices that these groups have faced, there is a lack of research on how these groups respond to discrimination from financial institutions. Through a series of logistic regressions, the authors analyzed how race, ethnicity, and gender are related to reporting experiences of discrimination. The authors then explored how consumers react to discrimination by looking at five reported reactions. Primary results show that Black consumers were more likely than most other racial groups to experience financial discrimination. Additionally, women were less likely than men to report financial discrimination. Race was shown to be a significant factor in four of the five reactions to discrimination, while gender was a factor in two of the reactions. The findings further show that after experiencing financial discrimination, most individuals turned to non-traditional financial services as a direct result of the bias or racism. Full article

19 pages, 1667 KiB

Open AccessArticle

Mapping the Literature on Short-Selling in Financial Markets: A Lexicometric Analysis

by Nitika Sharma, Sridhar Manohar, Bruce A. Huhmann and Yam B. Limbu

Int. J. Financial Stud. 2025, 13(3), 135; https://doi.org/10.3390/ijfs13030135 - 23 Jul 2025

Abstract

This study provides a comprehensive assessment and synthesis of the literature on short-selling. It performs a lexicometric analysis, providing a quantitative review of 1093 peer-reviewed journal articles to identify and illustrate the main themes in short-selling research. Almost half the published literature on [...] Read more.

This study provides a comprehensive assessment and synthesis of the literature on short-selling. It performs a lexicometric analysis, providing a quantitative review of 1093 peer-reviewed journal articles to identify and illustrate the main themes in short-selling research. Almost half the published literature on short-selling is thematically clustered around portfolio management techniques. Other key themes involve short-selling as it relates to risk management, strategic management, and market irregularities. Descending hierarchical classification examines the overall structure of the textual corpus of the short-selling literature and the relationships between its key terms. Similarity analysis reveals that the short-selling literature is highly concentrated, with most conceptual groups closely aligned and fitting into overlapping or conceptually similar areas. Some notable groups highlight prior short-selling studies of market dynamics, behavioral factors, technological advancements, and regulatory frameworks, which can serve as a foundation for market regulators to make more informed decisions that enhance overall market stability. Additionally, this study proposes a conceptual framework in which short-selling can be either a driver or an outcome by integrating the literature on its antecedents, consequences, explanatory variables, and boundary conditions. Finally, it suggests directions for future research. Full article

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