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Volume 13
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Int. J. Financial Stud., Volume 13, Issue 2 (June 2025) – 66 articles

Cover Story (view full-size image): This study compares the performance of fine-tuned deep learning models against traditional machine learning techniques for financial sentiment classification. Using datasets from FiQA and Financial PhraseBank, the authors evaluate SVM, Random Forest, and Logistic Regression models alongside transformer-based models such as BERT, FinBERT, GPT-4o, and GPT-4o-mini. The results show that fine-tuned GPT-4o and GPT-4o-mini significantly outperform others, with accuracy near 88%, while traditional models lag behind. GPT-4o-mini proves to be especially efficient, offering strong performance at a reduced cost. These findings highlight the growing relevance of domain-adapted LLMs in finance-related natural language processing tasks. View this paper
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26 pages, 456 KiB  
Article
ESG Risks and Market Valuations: Evidence from the Energy Sector
by Rahul Verma and Arpita A. Shroff
Int. J. Financial Stud. 2025, 13(2), 113; https://doi.org/10.3390/ijfs13020113 - 18 Jun 2025
Viewed by 602
Abstract
The link between ESG and financial performance is still under debate. In this study, we explore which aspects of ESG specifically drive market valuations through both systematic and idiosyncratic risk channels. We analyze the impact of the three core ESG pillars, 10 subcategories, [...] Read more.
The link between ESG and financial performance is still under debate. In this study, we explore which aspects of ESG specifically drive market valuations through both systematic and idiosyncratic risk channels. We analyze the impact of the three core ESG pillars, 10 subcategories, and associated controversies on market valuations in the energy sector. This analysis reveals that the environmental factor has a stronger impact (regression coefficient = 0.05) than the governance factor (regression coefficient = 0.003), emphasizing the need to prioritize environmental performance in ESG strategies. The positive coefficients for environmental resource use (0.005) and innovation (0.008) indicate that investments in efficiency and clean technologies are beneficial, while the negative coefficient for emissions (−0.004) underscores the risks associated with poor emissions management. These findings suggest that environmental risks currently outweigh governance risks for the energy sector, reinforcing the importance of aligning governance practices with environmental goals. To maximize ESG effectiveness, energy firms should focus on measurable improvements in resource efficiency, innovation, and emissions reduction and transparently communicate this progress to stakeholders. The evidence suggests that energy firms approach the ESG landscape differently, with sustainability leaders benefiting from higher valuations, particularly when ESG efforts are aligned with core competencies. However, many energy companies under-invest in value-creating environmental initiatives, focusing instead on emission management, which erodes value. While they excel in emission control, they lag in innovation, missing opportunities to enhance valuations. This underscores the potential for ESG risk analysis to improve portfolio performance, as sustainability can both create value and mitigate risks by factoring into valuation equations as both risks and opportunities. This study uniquely contributes to the ESG–financial performance literature by disentangling the specific ESG dimensions that drive market valuations in the energy sector, revealing that value is created not through emission control but through strategic alignment with eco-innovation, governance, and social responsibility. Full article
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19 pages, 682 KiB  
Article
Analysis of the Behavior of Insider Traders Who Disclose Information to External Traders
by Xingxing Cao, Jing Wang and Zhi Yang
Int. J. Financial Stud. 2025, 13(2), 112; https://doi.org/10.3390/ijfs13020112 - 17 Jun 2025
Viewed by 338
Abstract
This paper establishes an insider trading model under market supervision, which includes four types of trading entities: an insider trader, n external traders, noise traders, and market makers. The insider trader voluntarily discloses information to the external traders during the trading process. The [...] Read more.
This paper establishes an insider trading model under market supervision, which includes four types of trading entities: an insider trader, n external traders, noise traders, and market makers. The insider trader voluntarily discloses information to the external traders during the trading process. The research findings are as follows: (1) strengthening market supervision can significantly reduce the insider’s expected profit and increase the external traders’ expected profits; (2) the optimal market supervision strategy is closely related to the number of external traders; (3) the insider trader tends to disclose low-precision information to maximize their profits; (4) the precision of information disclosed by the insider trader and the intensity of market supervision affect price efficiency and the amount of residual information. The research results provide a basis for how the insider trader discloses information to external traders in market supervision and offer a reference for regulatory authorities to formulate differentiated supervision strategies. Full article
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17 pages, 2116 KiB  
Article
Dynamic Financial Valuation of Football Players: A Machine Learning Approach Across Career Stages
by Danielle Khalife, Jad Yammine, Elias Chbat, Chamseddine Zaki and Nada Jabbour Al Maalouf
Int. J. Financial Stud. 2025, 13(2), 111; https://doi.org/10.3390/ijfs13020111 - 17 Jun 2025
Viewed by 616
Abstract
The financial valuation of professional football players is influenced by multiple factors that evolve throughout a player’s career. This study examines these determinants using Gradient Boosting Machine Learning models, segmented by three age categories and three playing positions to capture the dynamic nature [...] Read more.
The financial valuation of professional football players is influenced by multiple factors that evolve throughout a player’s career. This study examines these determinants using Gradient Boosting Machine Learning models, segmented by three age categories and three playing positions to capture the dynamic nature of player valuation. K-fold cross-validation is applied to measure accuracy, with results indicating that incorporating a player’s projected future potential improves model precision from an average of 74% to 84%. The findings reveal that the relevance of valuation factors diminishes with age, and the most influential features vary by position—shooting for attackers, passing for midfielders, and defensive skills for defenders. The study adopts a dynamic segmentation approach, providing financial insights relevant to club managers, investors, and stakeholders in sports finance. The results contribute to sports analytics and financial modeling in sports, with applications in contract negotiations, talent scouting, and transfer market decisions. Full article
(This article belongs to the Special Issue Sports Finance (2nd Edition))
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23 pages, 4406 KiB  
Article
The Impact of Geographical Factors on the Banking Sector in El Salvador
by Anders Lundvig Hansen and Luís Lima Santos
Int. J. Financial Stud. 2025, 13(2), 110; https://doi.org/10.3390/ijfs13020110 - 13 Jun 2025
Viewed by 589
Abstract
This study explores how geographical factors shape El Salvador’s banking sector, particularly focusing on regional disparities, urbanization, and vulnerability to natural disasters affecting access to financial services. By employing a mixed-methods approach that combines quantitative data and qualitative interviews, the research analyzes how [...] Read more.
This study explores how geographical factors shape El Salvador’s banking sector, particularly focusing on regional disparities, urbanization, and vulnerability to natural disasters affecting access to financial services. By employing a mixed-methods approach that combines quantitative data and qualitative interviews, the research analyzes how these geographical challenges impact financial inclusion and banking development. Data from the Central Reserve Bank of El Salvador and financial institutions is examined alongside Geographic Information Systems (GISs) to illustrate the spatial distribution of banking services. Interviews with stakeholders, including bank representatives and clients from urban and rural areas, reveal a significant urban–rural divide, with approximately 75% of bank branches and 80% of ATMs situated in urban centers, particularly in San Salvador. Rural areas face limited access to formal banking due to challenging topography and inadequate infrastructure, leading to increased financial exclusion and reliance on informal systems. Natural disasters further disrupt banking infrastructure and heighten the need for emergency loans. While urbanization has spurred financial growth, it has also resulted in informal settlements with restricted access to formal services. As its main contribution, this study provides one of the first in-depth, geographically grounded analyses of financial exclusion in El Salvador, offering original insights into how spatial inequalities and disaster vulnerability intersect to shape banking access and economic participation. The study calls for a more inclusive banking sector, recommending mobile and digital banking expansion, agent banking in underserved areas, and improved disaster risk management to enhance economic participation across all regions. Full article
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24 pages, 318 KiB  
Article
Bridging Digital Finance and ESG Success: The Role of Financing Constraints, Innovation, and Governance
by Zhengren Luo, Pick Schen Yip and Robert Brooks
Int. J. Financial Stud. 2025, 13(2), 109; https://doi.org/10.3390/ijfs13020109 - 9 Jun 2025
Viewed by 648
Abstract
This study investigates the impact of digital finance on corporate ESG performance, using panel data from A-share listed companies on the Shanghai and Shenzhen stock markets between 2011 and 2022. Our findings demonstrate that digital finance significantly enhances corporate ESG outcomes, with financing [...] Read more.
This study investigates the impact of digital finance on corporate ESG performance, using panel data from A-share listed companies on the Shanghai and Shenzhen stock markets between 2011 and 2022. Our findings demonstrate that digital finance significantly enhances corporate ESG outcomes, with financing constraints and digital transformation serving as partial mediators and internal control quality acting as a moderating factor. The results from channel tests indicate that digital finance facilitates notable improvements in social performance and corporate governance, while its influence on environmental performance remains limited. Further analysis reveals that the positive impacts of digital finance on ESG are more evident in small-scale, technology-intensive, and non-polluting firms. This study concludes by proposing tailored recommendations for government, financial institutions, and corporations, emphasizing the need for differentiated policies to elevate ESG practices and promote higher quality, sustainable economic, and social development in China. Full article
(This article belongs to the Special Issue Investment and Sustainable Finance)
16 pages, 350 KiB  
Article
Bitcoin Return Dynamics Volatility and Time Series Forecasting
by Punit Anand and Anand Mohan Sharan
Int. J. Financial Stud. 2025, 13(2), 108; https://doi.org/10.3390/ijfs13020108 - 9 Jun 2025
Viewed by 1207
Abstract
Bitcoin and other cryptocurrency returns show higher volatility than equity, bond, and other asset classes. Increasingly, researchers rely on machine learning techniques to forecast returns, where different machine learning algorithms reduce the forecasting errors in a high-volatility regime. We show that conventional time [...] Read more.
Bitcoin and other cryptocurrency returns show higher volatility than equity, bond, and other asset classes. Increasingly, researchers rely on machine learning techniques to forecast returns, where different machine learning algorithms reduce the forecasting errors in a high-volatility regime. We show that conventional time series modeling using ARMA and ARMA GARCH run on a rolling basis produces better or comparable forecasting errors than those that machine learning techniques produce. The key to achieving a good forecast is to fit the correct AR and MA orders for each window. When we optimize the correct AR and MA orders for each window using ARMA, we achieve an MAE of 0.024 and an RMSE of 0.037. The RMSE is approximately 11.27% better, and the MAE is 10.7% better compared to those in the literature and is similar to or better than those of the machine learning techniques. The ARMA-GARCH model also has an MAE and an RMSE which are similar to those of ARMA. Full article
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19 pages, 1662 KiB  
Article
Highlighting the Role of Morality in News Framing and Its Short-Term Effects on Stock Market Fluctuations
by Paula T. Wang, Musa Malik and René Weber
Int. J. Financial Stud. 2025, 13(2), 107; https://doi.org/10.3390/ijfs13020107 - 9 Jun 2025
Viewed by 2120
Abstract
The Model of Intuitive Morality and Exemplars (MIME) suggests that news audiences, including investors, evaluate news based on their moral frames, and that these moral evaluations shape behavior. We extracted moral signals from 382,185 news articles across an 8-month period and examined their [...] Read more.
The Model of Intuitive Morality and Exemplars (MIME) suggests that news audiences, including investors, evaluate news based on their moral frames, and that these moral evaluations shape behavior. We extracted moral signals from 382,185 news articles across an 8-month period and examined their predictive effect on stock market movement. Results indicate that morality is a strong predictor during low economic periods and is driven by subversion and sanctity. Overall, our study suggests that moral framing and its foundations are important considerations for research on news effects, especially during periods of economic instability. The study provides an additional theoretical perspective on stock market fluctuations as well as practical implications for stakeholders with an interest in dampening collective panics and stabilizing investor sentiment. Full article
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25 pages, 729 KiB  
Article
Dynamics of Green and Conventional Bonds: Hedging Effectiveness and Sustainability Implication
by Rihab Belguith
Int. J. Financial Stud. 2025, 13(2), 106; https://doi.org/10.3390/ijfs13020106 - 6 Jun 2025
Viewed by 458
Abstract
This research examines the challenges of issuing green bonds due to a lack of established benchmarks. We compare regional differences between the U.S. and the E.U., hypothesizing that issuers of green bonds stand to benefit from comparing them to conventional (black) bonds. As [...] Read more.
This research examines the challenges of issuing green bonds due to a lack of established benchmarks. We compare regional differences between the U.S. and the E.U., hypothesizing that issuers of green bonds stand to benefit from comparing them to conventional (black) bonds. As most investors prioritize net positive returns as opposed to intangible sustainability metrics, the existence of a “green premium”, defined as the opportunity to price green bonds differently, remains to be proven. To this end, we employ a time-varying parameter vector autoregression (TVP-VAR), first deriving dynamic variance–covariance matrices and then conducting variance decomposition analysis to gauge connectedness and spillover effects of various bond benchmarks. Implementing multivariate portfolio construction strategies, we investigate the hedging capabilities of green and black bonds. Our findings show that both green and black bonds contribute to portfolio diversification as a risk management strategy. The paper highlights the role played by green bonds in promoting financial stability. Full article
(This article belongs to the Special Issue Investment and Sustainable Finance)
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47 pages, 4494 KiB  
Review
Past, Present, and Future Research Trajectories on Retail Investor Behaviour: A Composite Bibliometric Analysis and Literature Review
by Finn Christian Simonn
Int. J. Financial Stud. 2025, 13(2), 105; https://doi.org/10.3390/ijfs13020105 - 5 Jun 2025
Viewed by 1796
Abstract
The emergence of online brokerage platforms, mobile banking applications, and commission-free trading has altered the investment landscape, renewing commercial and scholarly interest in retail investors. In light of these changes, the present study aims to provide a structural overview of the current state [...] Read more.
The emergence of online brokerage platforms, mobile banking applications, and commission-free trading has altered the investment landscape, renewing commercial and scholarly interest in retail investors. In light of these changes, the present study aims to provide a structural overview of the current state of research on the behaviour of retail investors. Based on a dataset of 386 articles sourced from the Web of Science database, this study employs a composite bibliometric approach of a co-word and co-citation analysis as well as a network analysis to determine preceding scientific discourses, current research themes, and potential avenues for future research. The co-word analysis identifies seven distinct research themes: (1) implications for financial performance; (2) information behaviour; (3) behavioural biases and investor characteristics; (4) investor attention; (5) attitudes towards financial risks; (6) socially responsible investing; and (7) complex financial retail instruments. Incorporating applicable research on individual investors, private investors, and household investors from referenced articles, the co-citation analysis reveals nine preceding scientific discourses. Additionally, the network analyses highlight the concepts and publications currently shaping and likely to influence future research in this field. The present study contributes to the academic discourse by mapping the intellectual landscape of retail investor behaviour, suggesting avenues for future research, and offering valuable insights for navigating this dynamic field. Full article
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35 pages, 554 KiB  
Article
From Short-Term Volatility to Long-Term Growth: Restricted Stock Units’ Impact on Earnings per Share and Profit Growth Across Sectors
by Won (Albert) Park, Elena Sernova and Cheong-Yeul Park
Int. J. Financial Stud. 2025, 13(2), 104; https://doi.org/10.3390/ijfs13020104 - 5 Jun 2025
Viewed by 518
Abstract
This research empirically investigates how the adoption of restricted stock units (RSUs) affects earnings per share (EPS) and operating profit, focusing on variations across industries. RSUs have emerged as a strategic compensation tool for promoting alignment between employee interests and long-term organizational objectives, [...] Read more.
This research empirically investigates how the adoption of restricted stock units (RSUs) affects earnings per share (EPS) and operating profit, focusing on variations across industries. RSUs have emerged as a strategic compensation tool for promoting alignment between employee interests and long-term organizational objectives, while overcoming the short-sighted focus typically associated with conventional stock options. However, previous studies have mainly focused on analyzing the average effect of RSU or verifying only whether there is a short-term improvement in performance after its introduction, and there has been no sufficient review of the long-term effects. In addition, there is a lack of analyses on how the effects of RSU differ by industry. To fill this research gap, this study applied hierarchical regression analysis to S&P 500 company data from 1997 to 2023 to compare and analyze the differential effects of RSU by industry. The analysis showed that the EPS and operating income were only significantly affected by some industries in the early stages of RSU introduction, but the EPS and operating income were significantly improved in all industries in the long term. In addition, it was confirmed that the effects of RSU differ depending on the characteristics of the industry. This study empirically verifies the long-term effects of RSU and the differences by industry, offering practical insights for executives and shareholders when utilizing RSUs as a forward-looking compensation mechanism that fosters sustainable performance and enduring corporate value. Full article
25 pages, 738 KiB  
Article
Does Disproportionate Financial Inclusion Reduce Gender and Income-Group Inequality? Global Evidence
by Soon Suk Yoon, Ingyu Oh and Shawn S. Park
Int. J. Financial Stud. 2025, 13(2), 103; https://doi.org/10.3390/ijfs13020103 - 4 Jun 2025
Viewed by 542
Abstract
This paper investigates whether countries’ investments in financial inclusion, beyond what their economic capacity would predict, help mitigate gender and income-group gaps in financial opportunities. We construct a novel index, the Abnormal Financial Inclusion Index (AbFII), as the residuals from a [...] Read more.
This paper investigates whether countries’ investments in financial inclusion, beyond what their economic capacity would predict, help mitigate gender and income-group gaps in financial opportunities. We construct a novel index, the Abnormal Financial Inclusion Index (AbFII), as the residuals from a regression of financial inclusion on GDP per capita to isolate country-specific efforts in advancing financial inclusion. Using data from 100 countries between 2014 and 2021, we find that higher AbFII is associated with lower gender and rich-poor inequalities in financial inclusion, particularly in low-income and high-inequality countries. A one-standard-deviation increase in AbFII corresponds to a 1.2 percentage point reduction in gender and income-group disparities in financial access. We also find that AbFII predicts subsequent improvements in broader gender inequality, especially in reproductive health. The results are robust to various controls and remain consistent under instrumental variable analysis using broadband penetration as an instrument. Our findings suggest that financial inclusion policies exceeding the level expected by economic development can significantly reduce social disparities. Full article
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25 pages, 3323 KiB  
Article
A Framework for Gold Price Prediction Combining Classical and Intelligent Methods with Financial, Economic, and Sentiment Data Fusion
by Gergana Taneva-Angelova, Stefan Raychev and Galina Ilieva
Int. J. Financial Stud. 2025, 13(2), 102; https://doi.org/10.3390/ijfs13020102 - 4 Jun 2025
Viewed by 1773
Abstract
Accurate gold price forecasting is essential for informed financial decision-making, as gold is sensitive to economic, political, and social factors. This study presents a hybrid framework for multivariate gold price prediction that integrates classical econometric modelling, traditional machine learning, modern deep learning methods, [...] Read more.
Accurate gold price forecasting is essential for informed financial decision-making, as gold is sensitive to economic, political, and social factors. This study presents a hybrid framework for multivariate gold price prediction that integrates classical econometric modelling, traditional machine learning, modern deep learning methods, and their combinations. The framework incorporates financial, macroeconomic, and sentiment indicators, allowing it to capture complex temporal patterns and cross-variable relationships over time. Empirical validation on an eleven-year dataset (2014–2024) demonstrates the framework effectiveness across diverse market conditions. Results show that advanced supervised techniques outperform traditional econometric models under dynamic market environment. Key advantages of the framework include its ability to handle multiple data types, apply a structured variable selection process, employ diverse model families, and support model hybridisation and meta-modelling, providing practical guidance for investors, institutions, and policymakers. Full article
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21 pages, 519 KiB  
Article
Do Board Characteristics Affect Non-Performing Loans? GCC vs. Non-GCC Insights
by Abdelaziz Hakimi, Hichem Saidi and Soumaya Saidi
Int. J. Financial Stud. 2025, 13(2), 101; https://doi.org/10.3390/ijfs13020101 - 4 Jun 2025
Viewed by 948
Abstract
The Middle East and North Africa (MENA) region has faced challenges like political instability and economic fluctuations, which have impacted non-performing loans (NPL) levels. At the same time, over the years, reforms and regulations have encouraged stronger board structures to enhance corporate governance [...] Read more.
The Middle East and North Africa (MENA) region has faced challenges like political instability and economic fluctuations, which have impacted non-performing loans (NPL) levels. At the same time, over the years, reforms and regulations have encouraged stronger board structures to enhance corporate governance and improve risk management. The purpose of this paper is to investigate how board characteristics affect non-performing in the MENA region. Board characteristics shape governance quality, which influences risk management and reduces banks’ risk-taking behaviours. Hence, effective governance can reduce non-performing loans by improving oversight and credit decisions. To this end, we used a sample of 70 banks operating in 12 countries in the MENA region from 2010 to 2022. The System Generalized Method of Moments (SGMM) was employed as an empirical technique. To benefit from a comparative analysis, we divided the entire sample into two subsamples. The first subsample covers six Gulf Cooperation Council (GCC) countries with 42 banks. The second subsample is also relative to six non-Gulf Cooperation Council (non-GCC) countries with 28 banks. The empirical findings indicate that the presence of independent board members, a higher number of female board members, board remuneration, and the board index decrease NPLs across all regions, including MENA, GCC, and non-GCC. However, we found that board size, tenure, and duality increase NPLs. The results of this paper are beneficial for both policymakers and bankers, as they provide insights into how governance through board characteristics influences credit risk. These results support better decision-making in board appointments and governance practices to improve risk management and reduce non-performing loans. Full article
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27 pages, 526 KiB  
Article
The Effect of Corporate Venture Capital on Labor Income Share: Evidence from China
by Lanlan Sun, Lu Zhang and Shaolei Qu
Int. J. Financial Stud. 2025, 13(2), 100; https://doi.org/10.3390/ijfs13020100 - 4 Jun 2025
Viewed by 476
Abstract
This study examines the impact of corporate venture capital (CVC) on the labor income share of science and innovation enterprises, focusing on data from China’s Science and Technology Innovation Board (STIB) and Growth Enterprise Market (GEM) between 2010 and 2022. Empirical results reveal [...] Read more.
This study examines the impact of corporate venture capital (CVC) on the labor income share of science and innovation enterprises, focusing on data from China’s Science and Technology Innovation Board (STIB) and Growth Enterprise Market (GEM) between 2010 and 2022. Empirical results reveal a significant inverted U-shaped relationship between CVC shareholding and the labor income share of invested firms. CVC increases the labor income share by enhancing corporate governance, encouraging digital transformation, and improving human capital quality, but this effect diminishes when CVC shareholding exceeds a certain threshold. The moderating role of media attention and the heterogeneity of this relationship across regions and financial conditions are further explored. Additionally, the study identifies a positive U-shaped connection between CVC shareholding and the corporate pay gap, highlighting CVC’s complex role in influencing income inequality within firms. This research contributes to the literature by unveiling the nonlinear effects of CVC on income distribution, offering new insights into its dual role in promoting innovation and equity. Practically, it provides actionable recommendations for firms to optimize CVC ownership and for policymakers to design targeted interventions that address regional and financial disparities. By bridging the gap between CVC investment strategies and labor income fairness, this study lays the foundation for a balanced approach to sustainable economic development. Full article
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18 pages, 1320 KiB  
Article
Consumer Expenditure-Based Portfolio Optimization
by Attila Bányai, Tibor Tatay, Gergő Thalmeiner and László Pataki
Int. J. Financial Stud. 2025, 13(2), 99; https://doi.org/10.3390/ijfs13020099 - 3 Jun 2025
Viewed by 429
Abstract
This study examines whether portfolio optimization can be effectively based on annual changes in the harmonized index of consumer prices (HICP) data. Specifically, we assess whether asset allocation based on consumer expenditure can generate superior returns compared to static or equal-weighted asset allocation. [...] Read more.
This study examines whether portfolio optimization can be effectively based on annual changes in the harmonized index of consumer prices (HICP) data. Specifically, we assess whether asset allocation based on consumer expenditure can generate superior returns compared to static or equal-weighted asset allocation. To explore this, we use consumer expenditure data from HICP statistics categorized by COICOP. Our findings indicate that this strategy outperforms a buy-and-hold benchmark by 13.32% in terms of the Sharpe Ratio and exceeds an annual equal-weighted rebalancing strategy by 3.11%. Additionally, both the Calmar and Sterling Ratios demonstrate improved performance, further reinforcing the robustness of this approach. Furthermore, a hypothetical scenario where sector weights from the end of the given year—though not yet available during the year—are used suggests even greater improvements in performance. A high-sample bootstrap simulation confirms that the observed performance differences are not random but reflect the independent effectiveness of asset allocation based on consumer expenditure trends. This result strengthens the validity of our backtesting findings, indicating that the examined strategy could generate excess returns compared to passive portfolio managment and fixed-weight rebalancing approaches. The result of the study is therefore the development of an effective portfolio rebalancing strategy. Full article
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33 pages, 1452 KiB  
Article
From Policy Mandates to Market Signals: Causal and Dynamic Effects of Carbon Information Disclosure on Firm Value
by Runyu Liu, Mara Ridhuan Che Abdul Rahman and Ainul Huda Jamil
Int. J. Financial Stud. 2025, 13(2), 98; https://doi.org/10.3390/ijfs13020098 - 3 Jun 2025
Viewed by 421
Abstract
This study examines the causal and dynamic effects of carbon information disclosure on firm value, using a policy-driven setting in China’s carbon-intensive industries. In 2018, the Ministry of Ecology and Environment implemented a regulatory policy requiring internal carbon accounting and third-party verification for [...] Read more.
This study examines the causal and dynamic effects of carbon information disclosure on firm value, using a policy-driven setting in China’s carbon-intensive industries. In 2018, the Ministry of Ecology and Environment implemented a regulatory policy requiring internal carbon accounting and third-party verification for carbon-intensive enterprises, without mandating public disclosure. This exogenous policy shock offers a quasi-natural experiment to investigate how firms in carbon-intensive industries respond to environmental mandates through voluntary disclosure and how such disclosure affects their market valuation. Employing a difference-in-differences framework combined with two-stage least squares estimation, we identify a significant increase in carbon information disclosure following the policy intervention. This disclosure leads to a positive and growing effect on firm value, particularly when sustained over multiple years. Moreover, the valuation effect is moderated by regional environmental regulation: firms in areas with lower enforcement intensity benefit more from disclosure, as the signal is perceived to be more voluntary and credible. These findings provide robust causal evidence on the role of carbon information disclosure in shaping market outcomes under regulatory pressure. The study contributes to the literature on environmental regulation and corporate financial behavior in emerging markets. Full article
(This article belongs to the Special Issue Sustainable Corporate Governance and Financial Performance)
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21 pages, 914 KiB  
Article
Dynamic Spillover Effects Among China’s Energy, Real Estate, and Stock Markets: Evidence from Extreme Events
by Fusheng Xie, Jingbo Wang and Chunzi Wang
Int. J. Financial Stud. 2025, 13(2), 97; https://doi.org/10.3390/ijfs13020097 - 1 Jun 2025
Viewed by 624
Abstract
This paper employs a Time-Varying Parameter Vector Autoregression Directional–Spillover (TVP-VAR-DY) model to investigate the dynamic spillover effects among China’s energy, real estate, and stock markets from 2013 to 2023, with a focus on the impact of extreme events. The findings show that the [...] Read more.
This paper employs a Time-Varying Parameter Vector Autoregression Directional–Spillover (TVP-VAR-DY) model to investigate the dynamic spillover effects among China’s energy, real estate, and stock markets from 2013 to 2023, with a focus on the impact of extreme events. The findings show that the total conditional spillover index (TCI) typically remains below 40% in the absence of extreme events, but significantly increases during such events, reaching 51.09% during the 2015 stock market crisis and nearing 60% during the COVID-19 pandemic in 2020. Specifically, the oil and gas market exhibited a net spillover index of 4.61%, emerging as a major source of risk transmission. In contrast, the real estate market, which had a net spillover index of −9.38%, became a net risk absorber. The net spillover index indicates that the risk transmission role of different markets towards other markets is dynamically changing over time and is closely related to significant global or domestic economic events. These results indicate that extreme events not only directly impact specific markets but also rapidly propagate risks through complex inter-market linkages, exacerbating systemic risks. Therefore, it is recommended to enhance market monitoring, improve transparency, and optimize risk management strategies to cope with uncertainties in the global economy and financial markets. Full article
(This article belongs to the Special Issue Risks and Uncertainties in Financial Markets)
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24 pages, 2193 KiB  
Article
The Effect of Fat Tails on Rules for Optimal Pairs Trading: Performance Implications of Regime Switching with Poisson Events
by Pablo García-Risueño, Eduardo Ortas and José M. Moneva
Int. J. Financial Stud. 2025, 13(2), 96; https://doi.org/10.3390/ijfs13020096 - 1 Jun 2025
Viewed by 607
Abstract
This study examines the impact that fat-tailed distributions of the spread residuals have on the optimal orders for pairs trading of stocks and cryptocurrencies. Using daily data from selected pairs, the spread dynamics has been modeled through a mean-reverting Ornstein–Uhlenbeck process and investigates [...] Read more.
This study examines the impact that fat-tailed distributions of the spread residuals have on the optimal orders for pairs trading of stocks and cryptocurrencies. Using daily data from selected pairs, the spread dynamics has been modeled through a mean-reverting Ornstein–Uhlenbeck process and investigates how deviations from normality affect strategy design and profitability. Specifically, we compared four fat-tailed distributions—Lévy stable, generalized hyperbolic, Johnson’s SU, and non-centered Student’s t—and showed how they modify optimal entry and exit thresholds, and performance metrics. The main findings reveal that the proposed pairs trading strategy correctly captures some key stylized facts of residual spreads such as large jumps, skewness, and excess Kurtosis. Interestingly, we considered regime-switching behaviors to account for structural changes in market dynamics, providing empirical evidence that optimal trading rules are regime-dependent and significantly influenced by the residual distribution’s tail behavior. Unlike conventional approaches, we optimized the entry signal and link heavy tails not only to volatility clustering but also to the nonlinearity in switching regimes. These findings suggest the need to account for distributional properties and dynamic regimes when designing robust pairs trading strategies, providing a more realistic and effective framework of these strategies in highly volatile and non-normal markets. Full article
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19 pages, 268 KiB  
Article
Financial Attention and Household Consumption Upgrading
by Han Li and Rui Zhang
Int. J. Financial Stud. 2025, 13(2), 95; https://doi.org/10.3390/ijfs13020095 - 1 Jun 2025
Viewed by 986
Abstract
Based on data from the China Household Finance Survey (CHFS) conducted in 2019, this paper conducted an in-depth study on the impact and mechanism of financial attention on household consumption upgrading. The study found that an increase in financial attention can help to [...] Read more.
Based on data from the China Household Finance Survey (CHFS) conducted in 2019, this paper conducted an in-depth study on the impact and mechanism of financial attention on household consumption upgrading. The study found that an increase in financial attention can help to promote household consumption upgrading, and the result was still robust after using the instrumental variable method and substituting the explained variables. The mechanism analysis showed that financial attention can affect household consumption upgrading by influencing credit constraint and risk sharing. Heterogeneity analysis showed that the promotion effect of financial attention on consumption upgrading was significant in middle- and high-income households, high-financial-literacy households, and households living in first-tier cities. Full article
29 pages, 503 KiB  
Article
Derivative Complexity and the Stock Price Crash Risk: Evidence from China
by Willa Li, Yuki Gong, Yuge Zhang and Frank Li
Int. J. Financial Stud. 2025, 13(2), 94; https://doi.org/10.3390/ijfs13020094 - 1 Jun 2025
Viewed by 479
Abstract
This study investigates whether and how the complexity of derivative use influences the stock price crash risk in China’s capital market, a critical question given the growing use of derivatives in emerging economies where governance structures and disclosure standards vary widely. While prior [...] Read more.
This study investigates whether and how the complexity of derivative use influences the stock price crash risk in China’s capital market, a critical question given the growing use of derivatives in emerging economies where governance structures and disclosure standards vary widely. While prior research has examined the binary effects of derivative usage, limited attention has been paid to the multidimensional complexity of such instruments and its informational consequences. Using a novel hand-collected dataset of annual reports from Chinese A-share-listed firms between 2010 and 2023, we develop and implement new indicators that capture both the economic complexity (diversity and scale) and accounting complexity (reporting dispersion and fair-value hierarchy) of derivative use. Our analysis shows that higher complexity is associated with a significantly lower likelihood of stock price crashes. This effect is especially pronounced in non-state-owned firms and those with weaker internal-control systems, suggesting that derivative complexity can enhance information transparency and serve as a substitute for other governance mechanisms. These findings challenge the conventional view that complexity necessarily increases opacity and highlight the importance of disclosure quality and institutional context in shaping the market consequences of financial innovation. Full article
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30 pages, 382 KiB  
Article
Exchange Rates and Inflation Dynamics in Multicurrency Regimes: The Case of Zimbabwe (2014 to 2024)
by Simion Matsvai
Int. J. Financial Stud. 2025, 13(2), 93; https://doi.org/10.3390/ijfs13020093 - 30 May 2025
Viewed by 661
Abstract
Exchange rate volatility has emerged to be one of the most critical determinants of price stability for countries operating in multicurrency systems with their own currency in the basket of currencies. This study empirically examined the impact of exchange rates (official and parallel [...] Read more.
Exchange rate volatility has emerged to be one of the most critical determinants of price stability for countries operating in multicurrency systems with their own currency in the basket of currencies. This study empirically examined the impact of exchange rates (official and parallel market rates) on inflation in Zimbabwe during the multicurrency system for the period 2014 to 2024, together with comparing the impacts of the official and parallel market exchange rates on inflation. Time series and monthly data were used to examine the short and long run impact of exchange rates on inflation in an ARDL estimation framework. Findings revealed a short run and long run positive relationship between both the official and parallel market exchange rates and inflation, with the parallel market exchange rate being the most significant variable. Other control variables used, such as domestic productivity, have a highly significant negative impact on inflation through the official and parallel exchange rate models in both the short and the long run. Money supply, real interest rate, trade balance, foreign prices, foreign output, stock market prices and foreign currency reserves have varied impacts through either the official or parallel market exchange rate models. Policy recommendations include a contractionary Monetary and expansionary Fiscal policy mix that will result in exchange rate appreciation and stability, productivity growth, trade surplus, growth in reserves, and ultimately low prices. The exchange rate policy recommended in this study is to shelve discard the local currency in the multicurrency system until industrial capacity utilization exceeds 50% to add the local currency to the basket of currencies and 75% for mono-local currency (de-dollarization). Full article
22 pages, 504 KiB  
Article
Financial Development and Economic Growth in Sub-Saharan Africa Revisited: Disentangling the Role of Banks and Stock Markets
by Mayoro Diop, Mamadou Moustapha Ka, Ababacar Sedikh Gueye and Babacar Sène
Int. J. Financial Stud. 2025, 13(2), 92; https://doi.org/10.3390/ijfs13020092 - 29 May 2025
Viewed by 924
Abstract
The objective of this paper is to contribute to the analysis of the relationship between banks and stock markets in sub-Saharan African countries and their impacts on economic growth. While the literature on this issue is abundant, our article focuses on disentangling the [...] Read more.
The objective of this paper is to contribute to the analysis of the relationship between banks and stock markets in sub-Saharan African countries and their impacts on economic growth. While the literature on this issue is abundant, our article focuses on disentangling the effects of banks and stock markets on economic growth. Our approach is based on two indicators: the “activity–structure” variable, which measures the importance of stock markets in relation to banks, and the “activity–finance” variable, which takes into account the simultaneous development of banks and stock markets. Our empirical strategy is based on the estimation of a dynamic fixed effect model. The results indicate that the development of banks has a negative and significant impact, while the development of stock markets seems to have a positive influence on economic growth. It also shows that government authorities need to focus on developing stock markets at the expense of banks to promote economic growth. Full article
31 pages, 1989 KiB  
Article
Markov-Modulated and Shifted Wishart Processes with Applications in Derivatives Pricing
by Behzad-Hussein Azadie Faraz, Hamid Arian and Marcos Escobar-Anel
Int. J. Financial Stud. 2025, 13(2), 91; https://doi.org/10.3390/ijfs13020091 - 28 May 2025
Viewed by 1068
Abstract
The popular Wishart (WI) processes, first introduced by Bru in 1991, exhibit convenient analytical properties for modeling asset prices, particularly a closed-form characteristic function, and the ability to jointly model stochastic volatility and correlation. These features tend to increase substantially during crisis periods, [...] Read more.
The popular Wishart (WI) processes, first introduced by Bru in 1991, exhibit convenient analytical properties for modeling asset prices, particularly a closed-form characteristic function, and the ability to jointly model stochastic volatility and correlation. These features tend to increase substantially during crisis periods, more than predicted by a Wishart dynamic. Moreover, the variance processes implied by the Wishart, similar to CIR models, have no buffer away from zero. In this paper, we introduced the Markov-Modulated Shifted Wishart processes (MMSW) and the embedded Shifted Wishart processes (SW) to address these shortcomings in the modeling of asset prices. We obtain analytical representations for several characteristic functions. We also estimate the parameters and evaluate the price of Spread options via the Fourier transform under the two new models compared to the standard Wishart. Our analyses demonstrate a significant impact of the MMSW process compared to the standard Wishart process of up to 7% in Spread option prices. Full article
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24 pages, 1884 KiB  
Article
Fintech Adoption and Commercial Banks’ Environmental Performance: Do Green Accounting Practices Matter?
by Ywana Maher Lamey Badrous, Omar Ikbal Tawfik, Hamada Elsaid Elmaasrawy, Mohamed Ibrahim Srour and Mohammed Ahmed Ahmed Sharaf
Int. J. Financial Stud. 2025, 13(2), 90; https://doi.org/10.3390/ijfs13020090 - 28 May 2025
Viewed by 723
Abstract
From reviewing the literature, there was still a scarcity of research about direct and indirect relationships between fintech adoption (FA) and banks’ environmental performance (BEP), particularly in developing countries. Therefore, this is a pioneering study that empirically explored the impacts of FA on [...] Read more.
From reviewing the literature, there was still a scarcity of research about direct and indirect relationships between fintech adoption (FA) and banks’ environmental performance (BEP), particularly in developing countries. Therefore, this is a pioneering study that empirically explored the impacts of FA on BEP in the Middle East (ME) region, considering the mediating role of green accounting practices (GAPs)—such as green banking practices (GBPs), green finance (GF), and circular economy practices (CEPs)—based on legitimacy and ecological modernization (EM) theories to address these research gaps. Based on a structured survey and convenience sampling technique, the primary data were obtained from a sample of 500 members of staff from banks in Saudi Arabia, Bahrain, Egypt, Oman, Iraq, and Jordan. The structural equation model (SEM) was utilized to investigate the relationships among this study’s variables. The findings indicated that FA positively and significantly impacts GBPs, GF, CEPs, and BEP, which answered the first research question. Furthermore, the linkage between FA and BEP is positively and significantly mediated by GBPs, GF, and CEPs; thus, the second research question was answered. The findings provide bank executives and policy makers with valuable understanding and suggestions to deploy more investments in eco-friendly practices to enhance the environmental performance (EP), societal legitimacy, and achieve competitive advantage. Additionally, collaboration among the banking institutions, governments, and international firms is essential to promote FA and GAPs and enhance the EP. Full article
(This article belongs to the Special Issue Modern Financial Econometrics)
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23 pages, 1184 KiB  
Article
The Inflationary Episode of 1603 in Light of the Austrian Economic Theory
by Cristóbal Matarán
Int. J. Financial Stud. 2025, 13(2), 89; https://doi.org/10.3390/ijfs13020089 - 22 May 2025
Viewed by 395
Abstract
This paper examines the inflationary episode of 1603 in Spain through the lens of Austrian Economic Theory. The study focuses on the effects of monetary expansion caused by the influx of precious metals from the Americas and its impact on real wages and [...] Read more.
This paper examines the inflationary episode of 1603 in Spain through the lens of Austrian Economic Theory. The study focuses on the effects of monetary expansion caused by the influx of precious metals from the Americas and its impact on real wages and raw material prices. Through the analysis of historical data and the application of statistical methods, this study identifies key relationships between monetary inflows, price levels, and income distribution. The findings indicate that the rapid expansion of the money supply triggered inflation, disproportionately impacting various sectors of society. Using the Cantillon Effect as a framework, the study explains how monetary expansion led to uneven wealth redistribution and production distortions. Additionally, the Austrian Business Cycle Theory highlights the consequences of artificial monetary growth, including the misallocation of resources and reduced purchasing power for wage earners. This study employs historical data from Edward J. Hamilton and other sources, utilizing normalization techniques and regression models to empirically examine the economic dynamics of this period. By bridging theoretical insights with empirical analysis, this paper contributes to a deeper understanding of early modern inflationary processes and offers lessons applicable to contemporary economic challenges. Full article
(This article belongs to the Special Issue Financial Stability in Light of Market Fluctuations)
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20 pages, 343 KiB  
Article
Is the ESG Score Part of the Set of Information Available to Investors? A Conditional Version of the Green Capital Asset Pricing Model
by Lucía Galicia-Sanguino and Rubén Lago-Balsalobre
Int. J. Financial Stud. 2025, 13(2), 88; https://doi.org/10.3390/ijfs13020088 - 21 May 2025
Viewed by 431
Abstract
In this paper, we propose a linear factor model that incorporates investor preferences toward sustainability to analyze indirect effects that climate concerns may have on asset prices. Our approach is based on the relationship between environmental, social, and governance (ESG) investing and climate [...] Read more.
In this paper, we propose a linear factor model that incorporates investor preferences toward sustainability to analyze indirect effects that climate concerns may have on asset prices. Our approach is based on the relationship between environmental, social, and governance (ESG) investing and climate change considerations by investors. We use ESG scores as a part of the information set used by investors to determine the unconditional version of the conditional capital asset pricing model (CAPM). Our results show that the ESG score allows the linearized version of the conditional CAPM to greatly outperform the classic CAPM and the Fama–French three-factor model for different sorts of stock portfolios, contributing significantly to reducing pricing errors. Furthermore, we find a negative price of risk for stocks that covary positively with ESG growth, which suggests that green assets may perform better than brown ones if ESG concerns suddenly become more pressing over time. Thus, our paper constitutes a step forward in the attempt to shed light on how climate change is priced regardless of the climate risk measure used. Full article
18 pages, 1136 KiB  
Review
From Tweets to Trades: A Bibliometric and Systematic Review of Social Media’s Influence on Cryptocurrency
by Sheela Sundarasen and Farida Saleem
Int. J. Financial Stud. 2025, 13(2), 87; https://doi.org/10.3390/ijfs13020087 - 19 May 2025
Viewed by 1901
Abstract
The rise of social media has significantly influenced the cryptocurrency market, driving volatility through sentiment-driven trading. This study employs a bibliometric and content analysis approach to examine how social media, particularly Twitter, impacts cryptocurrency price movements. Using the bibliometric analysis, 151 peer-reviewed articles [...] Read more.
The rise of social media has significantly influenced the cryptocurrency market, driving volatility through sentiment-driven trading. This study employs a bibliometric and content analysis approach to examine how social media, particularly Twitter, impacts cryptocurrency price movements. Using the bibliometric analysis, 151 peer-reviewed articles published between 2018 and 2024 were analyzed to identify key research trends, themes, and potential future research. This study finds that social media sentiment plays a crucial role in cryptocurrency price forecasting, with machine learning and natural language processing (NLP) techniques enhancing prediction accuracy. Thematic analysis reveals four primary areas of focus: sentiment analysis and market prediction, machine learning-driven algorithmic trading, blockchain investment risks, and influencer-driven market behavior. This study contributes to the field by consolidating existing social media sentiment and cryptocurrency valuation knowledge, offering insights to investors, regulators, and academics. It highlights the need for future research to integrate multi-platform sentiment analysis, regulatory considerations, and behavioral finance perspectives. These insights are vital for understanding the evolving landscape of digital asset markets and their susceptibility to sentiment-driven speculation. Full article
(This article belongs to the Special Issue Cryptocurrency and Financial Market)
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17 pages, 879 KiB  
Article
Firm Profitability and Economic Crises: The Non-Linear Role of the Cash Conversion Cycle
by Agim Kukeli, Benjamin Widner, Fitim Deari, Gevorg Sargsyan and Nicoleta Barbuta-Misu
Int. J. Financial Stud. 2025, 13(2), 86; https://doi.org/10.3390/ijfs13020086 - 14 May 2025
Viewed by 1646
Abstract
This study investigates the non-linear effect of the cash conversion cycle (CCC) on a firm’s profitability for a sample of 6072 firms from five countries (Germany, Spain, France, Great Britain, and Italy) from 2006 to 2015. Additionally, this study explores the sensitivity of [...] Read more.
This study investigates the non-linear effect of the cash conversion cycle (CCC) on a firm’s profitability for a sample of 6072 firms from five countries (Germany, Spain, France, Great Britain, and Italy) from 2006 to 2015. Additionally, this study explores the sensitivity of economic crises to the non-linear effect of the CCC on a firm’s performance. This study employs fixed-effects unbalanced panel data and weighted least squares (due to heteroscedasticity) to examine a firm’s performance, using return on assets (ROA) to measure profitability. The cash conversion cycle, financial leverage, size, and tangibility are independent variables. The results of this study show that the effect of the cash conversion cycle on firms’ performance is an inverted U-shape (non-linear). It also shows that the economic conditions vis-à-vis crises influence firm performance. This study found the optimal number of the CCC to be 90 days for the entire sample, 85 days for the non-crisis period, and 92 days for the crisis period. It also finds that the marginal effect of the CCC on ROA is 3.9 times higher during economic crises versus non-economic crisis periods. This study contributes to the existing working capital management literature by examining the non-linear effect of the cash conversion cycle on profitability and the sensitivity of these effects during economic crises. Thus, empirical evidence can serve scholars, business policymakers, and corporate finance professionals in managing their working capital strategically. Full article
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46 pages, 15966 KiB  
Review
Decoding the Dynamics of Sustainable Finance: Spillover, Risk, and Connectivity Through a Bibliometric Lens
by Ke Peng, Muhammad Munir, Jifan Ren and Mariem Mejri
Int. J. Financial Stud. 2025, 13(2), 85; https://doi.org/10.3390/ijfs13020085 - 14 May 2025
Viewed by 671
Abstract
The field of sustainable finance has grown rapidly in response to escalating climate and economic challenges, yet its intellectual landscape, especially the connectedness between green and traditional financial systems, remains underexplored. This paper aims to systematically map the evolution, thematic structure, and intellectual [...] Read more.
The field of sustainable finance has grown rapidly in response to escalating climate and economic challenges, yet its intellectual landscape, especially the connectedness between green and traditional financial systems, remains underexplored. This paper aims to systematically map the evolution, thematic structure, and intellectual linkages of the sustainable finance literature with a specific focus on risk spillovers and connectedness across financial systems. This study employs a comprehensive bibliometric methodology to map 1261 Web of Science-indexed articles (1994–2024) on the connectedness of sustainable finance, using techniques such as citation analysis, bibliographic coupling, co-citation analysis, trend cartography, collaboration network, and keyword trend analysis. The study clarifies the field’s evolution and identifies its key themes, influential authors, institutions, and networks. The findings reveal an exponential surge in sustainable finance research after 2015, coinciding with policy milestones like the Paris Agreement and rising ESG investment interest. Notably, the review uncovers how research clusters have formed around topics such as green bond market spillovers, green technology innovation, and climate risk, highlighting both well-established areas and emerging fronts. The contribution lies in providing a roadmap for future research and policy: the study pinpoints knowledge gaps (e.g., systemic risk transmission between green and conventional assets) and suggests how policymakers and investors can leverage these insights to foster a resilient, sustainable financial system. Full article
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25 pages, 1466 KiB  
Article
Impact of Asset Bubbles on Exercise of Executive Stock Options
by Amin Mawani and Saikat Sarkar
Int. J. Financial Stud. 2025, 13(2), 84; https://doi.org/10.3390/ijfs13020084 - 13 May 2025
Viewed by 402
Abstract
This study examines whether Chief Executive Officers (CEOs) exercise a greater proportion of their exercisable options in response to firm-specific stock price bubbles. For a sample of U.S. firms from 1992 to 2021, the study identifies stock price bubble periods using the Generalized [...] Read more.
This study examines whether Chief Executive Officers (CEOs) exercise a greater proportion of their exercisable options in response to firm-specific stock price bubbles. For a sample of U.S. firms from 1992 to 2021, the study identifies stock price bubble periods using the Generalized Sup Augmented Dickey-Fuller (GSADF) method. A bubble is a statistical measure that detects an ex-post firm-specific stock price exuberance that creates abnormally high variation in stock prices arising from changes in discount rates, R&D and market liquidity. If executives have private information and can infer firm-specific bubbles, they are likely to exercise a greater proportion of their exercisable stock options during bubbles to benefit from their firms’ stock price exuberance. Using data aggregated at the CEO-year level, we find that executives are prone to exercising a larger portion of their vested stock options during market bubbles, with the aim of monetizing on the exuberance in the firm’s stock price. They leverage their expertise and their acquired price-sensitive private information to identify these bubbles. We also find that CEOs’ option exercise activity increases as the duration of the bubble increases to capture the price momentum. Full article
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