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Forecasting Orange Juice Futures: LSTM, ConvLSTM, and Traditional Models Across Trading Horizons
Examining Documentation Tools for Audit and Forensic Accounting Investigations
The Effects of Regulated Auditor Tenure on Opinion Shopping: Evidence from the Korean Market
The Influence of Environmental, Social, and Governance (ESG) Perception on Investor Trust and Brand Relationship Quality: A Study Among Retail Investors in Hong Kong

Journal Description

Journal of Risk and Financial Management

Journal of Risk and Financial Management is an international, peer-reviewed, open access journal on risk and financial management, published monthly online by MDPI.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, EconBiz, EconLit, RePEc, and other databases.
Journal Rank: CiteScore - Q1 (Business, Management and Accounting (miscellaneous))
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 21 days after submission; acceptance to publication is undertaken in 3.8 days (median values for papers published in this journal in the second half of 2024).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.

Imprint Information Journal Flyer Open Access ISSN: 1911-8074

Latest Articles

15 pages, 273 KiB

Open AccessArticle

Financial Openness, Trade Openness, and Economic Growth Nexus: A Dynamic Panel Analysis for Emerging and Developing Economies

by Thembalethu Macdonald Seti, Sukoluhle Mazwane and Mzuyanda Christian

J. Risk Financial Manag. 2025, 18(2), 78; https://doi.org/10.3390/jrfm18020078 (registering DOI) - 3 Feb 2025

International market openness has long been regarded as critical for economic development, and recent evidence highlights the distinct roles of financial and trade openness, particularly in emerging and developing economies. This study examines the impact of financial and trade openness on economic growth [...] Read more.

International market openness has long been regarded as critical for economic development, and recent evidence highlights the distinct roles of financial and trade openness, particularly in emerging and developing economies. This study examines the impact of financial and trade openness on economic growth in ten emerging and developing countries from 1970 to 2023. It employs a dynamic panel generalized method of moments (GMM) model, which is selected for its ability to address potential endogeneity and dynamic relationships within panel data. The analysis finds that both financial and trade openness positively influence economic growth and that stable macroeconomic conditions and political stability enhance these growth-promoting effects. In the context of growing geo-economic tensions, trade fairness, and national security concerns, the study underscores the need for policies that balance global integration with national interests. These findings suggest the importance of designing policies that promote greater integration into global financial and trading systems while ensuring sound macroeconomic fundamentals and supportive institutions. The study recommends that policymakers pursue strategic liberalization and strengthen governance structures to achieve sustained and inclusive growth. Full article

(This article belongs to the Special Issue Open Economy Macroeconomics)

30 pages, 3231 KiB

Open AccessArticle

The End of Mean-Variance? Tsallis Entropy Revolutionises Portfolio Optimisation in Cryptocurrencies

by Sana Gaied Chortane and Kamel Naoui

J. Risk Financial Manag. 2025, 18(2), 77; https://doi.org/10.3390/jrfm18020077 (registering DOI) - 3 Feb 2025

Has the mean-variance framework become obsolete? In this paper, we replace traditional variance–covariance methods of portfolio optimisation with relative Tsallis entropy and mutual information measures. Its goal is to enhance risk management and diversification in complicated finance ecosystems. We utilize the S&P 500 [...] Read more.

Has the mean-variance framework become obsolete? In this paper, we replace traditional variance–covariance methods of portfolio optimisation with relative Tsallis entropy and mutual information measures. Its goal is to enhance risk management and diversification in complicated finance ecosystems. We utilize the S&P 500 and Bitwise 10 cryptocurrency indices’ daily returns (2019–2024 data) and conduct our analysis to the year 2020 under extreme shocks. Many models were trained with different configurations, like mean-variance (MV), mean-entropy (ME), and mean-mutual information (MI) traders and their corresponding variants, using Sharpe’s ratio, Jensen’s alpha, and entropy value of risk (EVAR). The findings indicate that entropic models outperform conventional models in terms of diversification and, especially, extreme risk management. Because the appropriate normalization conditions often fail to be satisfied, we can informally see that after a recalibration of the effective frontier, we obtain from EVAR an accumulated resilience aspect to these rare events while also observing the great potential of entropy-based models to replicate non-linear dependencies between assets. The results show that models combining entropy and mutual information optimise the gain–loss ratio (GLR), providing stable diversification and improved risk management, while maximising returns in complex and volatile market environments. Full article

(This article belongs to the Special Issue Mathematical Modelling in Economics and Finance)

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30 pages, 1970 KiB

Open AccessArticle

The Stability of the Financial Cycle: Insights from a Markov Switching Regression in South Africa

by Khwazi Magubane

J. Risk Financial Manag. 2025, 18(2), 76; https://doi.org/10.3390/jrfm18020076 (registering DOI) - 3 Feb 2025

The stability of the financial cycle is paramount for the effective formulation and implementation of macroprudential policy in South Africa. The South African Reserve Bank (SARB) and the Prudential Authority strive to mitigate excessive fluctuations in the financial cycle, recognising that a stable [...] Read more.

The stability of the financial cycle is paramount for the effective formulation and implementation of macroprudential policy in South Africa. The South African Reserve Bank (SARB) and the Prudential Authority strive to mitigate excessive fluctuations in the financial cycle, recognising that a stable cycle provides more reliable signals for financial sector activity and anchors macroprudential policy decisions. However, the tightening of macroprudential policy by the SARB and the Prudential Authority during the post-2009 recovery period, despite mild signs of recovery from the global financial crisis, raises concerns about the stability of the South African financial cycle. This study aims to construct a financial cycle volatility index to assess its stability and identify the key macroeconomic drivers of financial instability in South Africa. Employing monthly data from 1970 to 2024, the study utilises a dynamic conditional correlation model and a Markov switching regression model to analyse the relationship between macroeconomic variables and financial stability. The findings reveal heightened financial cycle volatility around crisis periods and demonstrate that macroeconomic variables such as exchange rate fluctuations, price level changes, and implementing monetary and macroprudential policies can significantly increase financial instability. These results suggest a need for proactive and aggressive macroprudential policy measures in the years preceding potential crises. Moreover, the study’s findings emphasise the importance of considering macroeconomic conditions when calibrating financial cycle policies. Full article

(This article belongs to the Special Issue Financial Econometrics and Quantitative Economic Analysis)

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27 pages, 2311 KiB

Open AccessArticle

The Impact of Earnings Announcements Before and After Regular Market Hours on Asset Price Dynamics in the Fintech Era

by Janhavi Shankar Tripathi and Erick W. Rengifo

J. Risk Financial Manag. 2025, 18(2), 75; https://doi.org/10.3390/jrfm18020075 (registering DOI) - 2 Feb 2025

With the recent increase in retail investor participation led by commission-less fintech trading applications and new features like fractional trading, we now have higher volatility and significantly quicker price changes. This makes it hard to make informed trading decisions. Moreover, these effects are [...] Read more.

With the recent increase in retail investor participation led by commission-less fintech trading applications and new features like fractional trading, we now have higher volatility and significantly quicker price changes. This makes it hard to make informed trading decisions. Moreover, these effects are exacerbated even further around earnings announcements days. In this paper, we use Nasdaq data feed at a minute frequency and show that there is a significant increase in the slope of the price–volume structure during extended hours (after-hours, or pre-market hours) as compared with the ones observed during regular market times. Our analysis shows that the liquidity is much less during the extended market hours. As such, earnings announcements of stocks during these times have a significantly larger price impact than those stocks that have their earnings announced during regular trading hours. This significant difference can be explained by observing the limit order book structures during these different trading periods. We suggest that the earnings announcements should not be made during extended hours given the significantly lower liquidity and thus, the significantly larger price impact that not only determines the prices for the next trading session but also sets the new “fundamental” price signals for the stocks. Full article

(This article belongs to the Special Issue Financial Technologies (Fintech) in Finance and Economics)

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32 pages, 3133 KiB

Open AccessArticle

Innovative Credit Risk Assessment: Leveraging Social Media Data for Inclusive Credit Scoring in Indonesia’s Fintech Sector

by Andry Alamsyah, Aufa Azhari Hafidh and Annisa Dwiyanti Mulya

J. Risk Financial Manag. 2025, 18(2), 74; https://doi.org/10.3390/jrfm18020074 (registering DOI) - 2 Feb 2025

The financial technology domain has undertaken significant strides toward more inclusive credit scoring systems by integrating alternative data sources, prompting an exploration of how we can further simplify the process of efficiently assessing creditworthiness for the younger generation who lack traditional credit histories [...] Read more.

The financial technology domain has undertaken significant strides toward more inclusive credit scoring systems by integrating alternative data sources, prompting an exploration of how we can further simplify the process of efficiently assessing creditworthiness for the younger generation who lack traditional credit histories and collateral assets. This study introduces a novel approach leveraging social media analytics and advanced machine learning techniques to assess the creditworthiness of individuals without traditional credit histories and collateral assets. Conventional credit scoring methods tend to rely heavily on central bank credit information, especially traditional collateral assets such as property or savings accounts. We leverage demographics, personality, psycholinguistics, and social network data from LinkedIn profiles to develop predictive models for a comprehensive financial reliability assessment. Our credit scoring methods propose scoring models to produce continuous credit scores and classification models to categorize potential borrowers—particularly young individuals lacking traditional credit histories or collateral assets—as either good or bad credit risks based on expert judgment thresholds. This innovative approach questions conventional financial evaluation methods and enhances access to credit for marginalized communities. The research question addressed in this study is how to develop a credit scoring mechanism using social media data. This research contributes to the advancing fintech landscape by presenting a framework that has the potential to transform credit scoring practices to adapt to modern economic activities and digital footprints. Full article

(This article belongs to the Special Issue Data and Technology: Shaping the Future of Finance, Accounting, and Business Systems Innovation)

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28 pages, 363 KiB

Open AccessArticle

Unraveling the Impact of Product Market Competition and Earnings Volatility on Zero-Leverage Policies

by Imed Chkir, Alireza Rahimzadeh and Syrine Sassi

J. Risk Financial Manag. 2025, 18(2), 73; https://doi.org/10.3390/jrfm18020073 (registering DOI) - 1 Feb 2025

This paper investigates the impact of product market competition (PMC) on firms’ adoption of zero-leverage (ZL) strategies and examines whether this relationship is influenced by earnings volatility. Using data from 1989 to 2019, we analyze the PMC and ZL behavior of firms using [...] Read more.

This paper investigates the impact of product market competition (PMC) on firms’ adoption of zero-leverage (ZL) strategies and examines whether this relationship is influenced by earnings volatility. Using data from 1989 to 2019, we analyze the PMC and ZL behavior of firms using logistic regression. Our results indicate that as PMC intensifies, firms are more likely to adopt ZL policies. This effect is stronger in firms with higher earnings volatility, suggesting a significant interaction between PMC and earnings volatility in shaping capital structure decisions. This study extends existing research by highlighting the role of earnings volatility in strengthening the relationship between PMC and ZL behavior, offering new insights into the dynamics between market competition, financial decisions, and firm risk. Full article

(This article belongs to the Special Issue Firms’ Behavior, Productivity and Economics of Innovation II)

16 pages, 658 KiB

Open AccessArticle

On the Use of the Harmonic Mean Estimator for Selecting the Hypothetical Income Distribution from Grouped Data

by Kazuhiko Kakamu

J. Risk Financial Manag. 2025, 18(2), 72; https://doi.org/10.3390/jrfm18020072 (registering DOI) - 1 Feb 2025

It is known that the harmonic mean estimator is a consistent estimator of the marginal likelihood and is easy to implement, but it has severe biases and does not change as much as the prior distribution changes. In this study, we investigate the [...] Read more.

It is known that the harmonic mean estimator is a consistent estimator of the marginal likelihood and is easy to implement, but it has severe biases and does not change as much as the prior distribution changes. In this study, we investigate the use of the harmonic mean estimator to select the hypothetical income distribution from grouped data through Monte Carlo simulations and apply it to real data in Japan. From the results, we confirm that there are significant biases, but it can be reliably used to select an appropriate model only when the sample size is large enough under appropriate prior settings. Full article

(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)

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24 pages, 672 KiB

Open AccessArticle

The Big Three Passive Investors and the Cost of Equity Capital

by Sebahattin Demirkan and Ted M. Fikret Polat

J. Risk Financial Manag. 2025, 18(2), 71; https://doi.org/10.3390/jrfm18020071 (registering DOI) - 1 Feb 2025

This study investigates the role of the Big Three passive investors (BlackRock, Vanguard, and State Street) in influencing firms’ cost of equity. By examining the unique ownership structure these investors bring, the research sheds light on a pivotal yet underexplored aspect of institutional [...] Read more.

This study investigates the role of the Big Three passive investors (BlackRock, Vanguard, and State Street) in influencing firms’ cost of equity. By examining the unique ownership structure these investors bring, the research sheds light on a pivotal yet underexplored aspect of institutional ownership and its implications for corporate financing. Using a comprehensive dataset spanning from 1997 to 2016, this study demonstrates that increased ownership by the Big Three is associated with improved disclosure practices and reduced information asymmetry, leading to a lower cost of equity. However, the study also uncovers a nuanced trade-off, as concentrated ownership may introduce liquidity risks in certain contexts. These findings bridge a critical gap in the literature by reconciling divergent perspectives on the role of passive investors and provide actionable insights for institutional investors, regulators, and corporate managers seeking to understand the broader implications of passive ownership on firm valuation and financing strategies. Full article

(This article belongs to the Special Issue Corporate Governance and Earnings Management)

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18 pages, 306 KiB

Open AccessArticle

Characteristics of the Chairman of the Board of Directors and Their Impact on Dividend Payments in the Moroccan Stock Exchange

by Reda Louziri and Khadija Oubal

J. Risk Financial Manag. 2025, 18(2), 70; https://doi.org/10.3390/jrfm18020070 (registering DOI) - 1 Feb 2025

This study examines the influence of chairman characteristics on dividend policy within Moroccan firms listed on the Casablanca Stock Exchange, addressing a critical gap in the behavioral finance literature. This research focuses on five key attributes of chairmen—age, gender, nationality, tenure, and founder [...] Read more.

This study examines the influence of chairman characteristics on dividend policy within Moroccan firms listed on the Casablanca Stock Exchange, addressing a critical gap in the behavioral finance literature. This research focuses on five key attributes of chairmen—age, gender, nationality, tenure, and founder status—and analyzes their impact on dividend decisions over a 16-year period (2003–2018). A fixed effects panel data model was employed, incorporating six control variables—firm age, growth opportunities, size, board size, female representation, and foreign ownership. The results demonstrate that chairman age and tenure significantly affect dividend policy. Older chairmen are more risk-averse, favoring higher dividend distributions to ensure financial stability, while longer-tenured chairmen tend to retain earnings for aggressive investments, reflecting overconfidence. The other variables—gender, nationality, and founder status—showed no statistically significant effects in this context. This research provides the first empirical evidence on the relationship between chairman characteristics and dividend policy in Morocco. The findings offer valuable insights for investors, analysts, and policymakers in emerging markets, emphasizing the role of leadership traits in corporate financial strategies. By highlighting the importance of behavioral factors, this study enhances understanding of dividend policy determinants in developing economies. Full article

(This article belongs to the Special Issue Corporate Dividend Payout Policy)

18 pages, 568 KiB

Open AccessArticle

Board Structure and Executive Compensation for R&D Spending in Innovative Companies Amid COVID-19

by Muhammad Abrar-ul-haq

J. Risk Financial Manag. 2025, 18(2), 69; https://doi.org/10.3390/jrfm18020069 (registering DOI) - 1 Feb 2025

Innovation has played a vital role in continuing business operations worldwide amid the challenges of the COVID-19 pandemic. Innovation is critical for the success and survival of global organizations. Due to the risky long-term nature of innovation, executives with decision-making power may act [...] Read more.

Innovation has played a vital role in continuing business operations worldwide amid the challenges of the COVID-19 pandemic. Innovation is critical for the success and survival of global organizations. Due to the risky long-term nature of innovation, executives with decision-making power may act cynically. Such pessimistic actions become normal when executive compensation is based on the firm’s short-term outcomes. Therefore, the current research examines the effect of executive compensation on research and development (R&D) investment using data from the world’s top 48 innovative companies in Australia. The proposed model was tested using Smart-PLS (v.3.2.8). The findings indicate that board composition significantly and positively affects R&D investment. Likewise, the long-term composition of executives has a positive effect, whereas short-term executive compensation has a negative effect on R&D. Hence, this research suggests that to increase innovation, firms should control the myopic actions of top management by orientating their compensation toward long-term innovation. Full article

(This article belongs to the Special Issue Bridging Financial Integrity and Sustainability)

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20 pages, 1054 KiB

Open AccessArticle

Threshold Effects of Economic-Policy Uncertainty on Food Security in Nigeria

by Goodness C. Aye, Lydia N. Kotur and Peter I. Ater

J. Risk Financial Manag. 2025, 18(2), 68; https://doi.org/10.3390/jrfm18020068 - 30 Jan 2025

The study investigated the threshold effects of economic-policy uncertainty on food security in Nigeria, covering the period from 1970 to 2021. Summary statistics and unit root tests were employed for preliminary analysis, while the threshold regression model was used to realize the key [...] Read more.

The study investigated the threshold effects of economic-policy uncertainty on food security in Nigeria, covering the period from 1970 to 2021. Summary statistics and unit root tests were employed for preliminary analysis, while the threshold regression model was used to realize the key objective of the study. The results revealed that adult population (ADULTPOP), environmental degradation (ENVT), exchange rate uncertainty (EXRU), financial deepening (FINDEEP), food security (FS), government expenditure in agriculture uncertainty (GEAU), global economic uncertainty (GEU), inflation (INF), and interest rate uncertainty (INRU) showed positive mean, maximum, and minimum values over the study period. Most variables exhibited low volatility, except for inflation (SD = 15.619) and interest rate uncertainty (SD = 8.435), which had relatively higher volatility. ADF and PP unit root tests indicated that ADULTPOP, FINDEEP, and FS had unit roots in levels, but became stationary after first differencing (integrated of order one). ENVT, EXRU, GEAU, GEU, INF, and INRU were stationary in level, indicating they were integrated of order zero. The result showed a threshold value of 0.077 for global economic uncertainty (GEU). Above this threshold, exchange rate uncertainty (EXRU) had a statistically significant effect on food security (p = 0.031). Non-threshold variables such as adult population (p = 0.000) and environmental degradation (p = 0.000) also had significant effects on food security. The study thus provided evidence of threshold effects of economic-policy uncertainty on food security. The study recommends that policymakers incorporate threshold values in policy implementation to mitigate risks linked to high economic-policy uncertainty. The Government is also advised to establish strategies for stabilizing exchange rates or alleviating their harmful effects on food supply, which may be crucial for achieving food security. Full article

(This article belongs to the Section Economics and Finance)

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19 pages, 298 KiB

Open AccessArticle

Impact of IPSAS Adoption on Governance and Corruption: A Comparative Study of Southern Europe

by Bassam Mohammad Maali and Amer Morshed

J. Risk Financial Manag. 2025, 18(2), 67; https://doi.org/10.3390/jrfm18020067 - 30 Jan 2025

This study examines the impact that International Public Sector Accounting Standards adoption might have on governance quality and corruption control in Spain, Portugal, and Italy. IPSAS was designed to globally enhance public transparency and accountability thanks to accrual accounting. However, its effectiveness in [...] Read more.

This study examines the impact that International Public Sector Accounting Standards adoption might have on governance quality and corruption control in Spain, Portugal, and Italy. IPSAS was designed to globally enhance public transparency and accountability thanks to accrual accounting. However, its effectiveness in fighting corruption and steering better governance has varied across institutional contexts and implementation phases. This paper examines, using partial least squares structural equation modeling (PLS-SEM) and comparative analysis, how legal systems, political stability, and anti-corruption measures mediate the relationship. The results indicate that full IPSAS adoption, as in the case of Spain, significantly enhances governance if the institutional framework is solid and, by extension, reduces corruption. Partial adoption, such as that by Portugal, exposes moderate improvements, but Italy, still in the preparation of the process, shows the poorest result. The study identifies that the legal system, along with complementary reforms like capacity building and political stability, is a very crucial factor in enhancing the IPSAS impact. This covers the evidential gaps and provides actionable insights for policymakers, while at the same time underlining institutional strength as a key driver for IPSAS adoption, contributing to broader discussions on advancing public sector accounting reforms. Full article

(This article belongs to the Special Issue Auditing, Corporate Governance and Financial Reporting Quality)

23 pages, 3658 KiB

Open AccessArticle

A Supply and Demand Framework for Bitcoin Price Forecasting

by Murray A. Rudd and Dennis Porter

J. Risk Financial Manag. 2025, 18(2), 66; https://doi.org/10.3390/jrfm18020066 - 30 Jan 2025

We develop a flexible supply and demand equilibrium framework that can be used to develop pricing models to forecast Bitcoin’s price trajectory based on its fixed, inelastic supply and evolving demand dynamics. This approach integrates Bitcoin’s unique monetary attributes with demand drivers such [...] Read more.

We develop a flexible supply and demand equilibrium framework that can be used to develop pricing models to forecast Bitcoin’s price trajectory based on its fixed, inelastic supply and evolving demand dynamics. This approach integrates Bitcoin’s unique monetary attributes with demand drivers such as institutional adoption and long-term holding patterns. Using the April 2024 halving as a baseline, we explore model scenarios with varying assumptions about growth in adoption and supply-side constraints, calibrated to real-world data. Our findings indicate that institutional and sovereign accumulation can significantly influence price trajectories, with increasing demand intensifying the impact of Bitcoin’s constrained liquidity. Forecasts suggest that modest withdrawals from liquid supply to strategic reserves could lead to substantial price appreciation over the medium term, while higher withdrawal levels may induce volatility due to supply scarcity. These results highlight Bitcoin’s potential as a long-term investment and underline the importance of integrating economic fundamentals into forward-looking portfolio strategies. Our framework provides flexibility for testing different market scenarios, demand curve functional forms, and parameterizations, offering a tool for investors and policymakers considering Bitcoin’s role as a strategic asset. By advancing a fundamentals-based approach, this study contributes to the broader understanding of how Bitcoin’s supply–demand dynamics influence market behavior. Full article

(This article belongs to the Special Issue Blockchain Technologies and Cryptocurrencies)

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23 pages, 361 KiB

Open AccessArticle

Whistleblowing Disclosure as a Shield Against Earnings Management: Evidence from the Insurance Sector

by Ines Belgacem

J. Risk Financial Manag. 2025, 18(2), 65; https://doi.org/10.3390/jrfm18020065 - 30 Jan 2025

One of the fundamental components of internal controls, a whistleblowing system (WBS) is crucial for preventing fraud, addressing irregularities, and enhancing good governance. The purpose of this study is to investigate the impact of whistleblower disclosures on earnings management in Saudi Arabia’s Takaful [...] Read more.

One of the fundamental components of internal controls, a whistleblowing system (WBS) is crucial for preventing fraud, addressing irregularities, and enhancing good governance. The purpose of this study is to investigate the impact of whistleblower disclosures on earnings management in Saudi Arabia’s Takaful Insurance (TKI) sector between 2017 and 2023. To this end, a whistleblowing index was constructed as a tool to evaluate the whistleblowing framework’s effectiveness. Using the Dynamic Generalized Method of Moments (GMM) to account for endogeneity, it was found that most Saudi insurance companies increased their efforts to disclose information about whistleblowers, which significantly reduced earnings management practices. Specifically, the study concludes that the size of the audit committee (ACS) significantly and negatively affects how insurance businesses manage their earnings when a whistleblower system is in place. Additionally, there is a notable and adverse effect on earnings management from board size (BSZ), the percentage of non-executive independent members (PNIM), and Shariah board size (SBS). However, it was found that earnings management is unaffected by the frequency of board meetings (BMFR). This study adds to the body of knowledge by demonstrating how corporate governance enhances the effectiveness of the whistleblowing system. Full article

(This article belongs to the Special Issue Environmental, Social, and Governance (ESG), Corporate Social Responsibility (CSR), and Green Finance)

28 pages, 985 KiB

Open AccessArticle

Does Information Asymmetry Affect Firm Disclosure? Evidence from Mergers and Acquisitions of Financial Institutions

by Bing Chen, Wei Chen and Xiaohui Yang

J. Risk Financial Manag. 2025, 18(2), 64; https://doi.org/10.3390/jrfm18020064 - 30 Jan 2025

We use a quasi-exogenous shock to information asymmetry among shareholders to evaluate the effect of information asymmetry on corporate disclosure. In the post-Regulation Fair Disclosure (FD) period, the merger between a shareholder and a lender of the same firm provides a shock to [...] Read more.

We use a quasi-exogenous shock to information asymmetry among shareholders to evaluate the effect of information asymmetry on corporate disclosure. In the post-Regulation Fair Disclosure (FD) period, the merger between a shareholder and a lender of the same firm provides a shock to the information asymmetry among equity investors, because Regulation FD applies to shareholders but not lenders. After the merger, the shareholder gains access to the firm-specific private information held by the lender, which produces an asymmetry in the information held by shareholders. We first provide evidence that information asymmetry among shareholders indeed increases after the shareholder–lender mergers. We then use a difference-in-differences research design to show that after shareholder–lender merger transactions, firms issue more quarterly forecasts (including earnings, sales, capital expenditure, earnings before interest, taxes, amortization (EBITDA), and gross margin), and the quarterly earnings forecasts are more precise. This study provides direct empirical evidence that information asymmetry among shareholders affects corporate disclosure. Firms can address increased information asymmetry by providing more disclosures, fostering a more equitable information environment. Additionally, policymakers might consider these results when evaluating the implications of Regulation FD, particularly in the context of mergers and acquisitions (M&A) of financial institutions where a shareholder gains access to private information held by a debt holder. Full article

(This article belongs to the Section Business and Entrepreneurship)

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20 pages, 699 KiB

Open AccessArticle

Diagnostic for Volatility and Local Influence Analysis for the Vasicek Model

by Manuel Galea, Alonso Molina and Isabelle S. Beaudry

J. Risk Financial Manag. 2025, 18(2), 63; https://doi.org/10.3390/jrfm18020063 - 29 Jan 2025

The Ornstein–Uhlenbeck process is widely used in modeling biological systems and, in financial engineering, is commonly employed to describe the dynamics of interest rates, currency exchange rates, and asset price volatilities. As in any stochastic model, influential observations, such as outliers, can significantly [...] Read more.

The Ornstein–Uhlenbeck process is widely used in modeling biological systems and, in financial engineering, is commonly employed to describe the dynamics of interest rates, currency exchange rates, and asset price volatilities. As in any stochastic model, influential observations, such as outliers, can significantly influence the accuracy of statistical analysis and the conclusions we draw from it. Identifying atypical data is, therefore, an essential step in any statistical analysis. In this work, we explore a set of methods called local influence, which helps us understand how small changes in the data or model can affect an analysis. We focus on deriving local influence methods for models that predict interest or currency exchange rates, specifically the stochastic model called the Vasicek model. We develop and implement local influence diagnostic techniques based on likelihood displacement, assessing the impact of the perturbation of the variance and the response. We also introduce a novel and simple way to test whether the model’s variability stays constant over time based on the Gradient test. The purpose of these methods is to identify potential risks of reaching incorrect conclusions from the model, such as the inaccurate prediction of future interest rates. Finally, we illustrate the methodology using the monthly exchange rate between the US dollar and the Swiss franc over a period exceeding 20 years and assess the performance through a simulation study. Full article

(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)

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50 pages, 2656 KiB

Open AccessArticle

Selection and Timing Skill in Bond Mutual Fund Returns: Evidence from Bootstrap Simulations

by Lifa Huang, Wayne Y. Lee and Craig G. Rennie

J. Risk Financial Manag. 2025, 18(2), 62; https://doi.org/10.3390/jrfm18020062 - 29 Jan 2025

We show that U.S. open-end actively managed domestic bond mutual fund managers possess selection and short-term timing skills based on monthly returns from 1999 to 2016. Parametric tests bias against finding evidence of manager skill, and correction for precision of alpha matters most [...] Read more.

We show that U.S. open-end actively managed domestic bond mutual fund managers possess selection and short-term timing skills based on monthly returns from 1999 to 2016. Parametric tests bias against finding evidence of manager skill, and correction for precision of alpha matters most when true alpha is uncertain. Our bootstrap simulations use precision-adjusted alpha (t(α)) controlling for luck without relying on parametric statistics. We find: the top 50 percent of bond mutual fund managers generate positive precision-adjusted alpha net of expense; selection skill contributes to long-term fund performance; and timing skill adds to short-term fund results, especially for government bond funds compared to corporate bond funds. Full article

(This article belongs to the Special Issue Financial Markets and Institutions)

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22 pages, 1708 KiB

Open AccessArticle

Economic and Sectoral Convergence in Latin America and the Caribbean: An Analysis of Beta, Sigma, and Gamma Convergence

by César Lenin Navarro-Chávez

J. Risk Financial Manag. 2025, 18(2), 61; https://doi.org/10.3390/jrfm18020061 - 29 Jan 2025

The purpose of this study is to examine the economic and sectoral convergence of 32 countries in Latin America and the Caribbean (LAC) region from 1980 to 2022. The economic convergence hypothesis suggests that two economies with similar structural characteristics but different per [...] Read more.

The purpose of this study is to examine the economic and sectoral convergence of 32 countries in Latin America and the Caribbean (LAC) region from 1980 to 2022. The economic convergence hypothesis suggests that two economies with similar structural characteristics but different per capita income levels can tend to equalize in terms of income level in the long run. Confirming economic convergence has led to the development of various methodologies, among which dynamic and static disparity measures stand out. To achieve the objective of this research, both types of measures were calculated, determining beta and sigma convergence for dynamic disparity and gamma convergence for static disparity. This was accomplished by adopting the methodological approaches proposed by Sala-I-Martin and Marchante, Ortega, and Sánchez. The results show a gradual but steady evolution towards economic and sectoral convergence in LAC region during the 1980–2022 period. However, inequalities and divergences persist, requiring less developed countries to strengthen their institutions, implement sound macroeconomic policies, and diversify their economies. These measures are essential to driving economic growth and fostering more balanced and sustainable development across the region. Full article

(This article belongs to the Special Issue International Financial Flows and Economic Growth)

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25 pages, 1642 KiB

Open AccessArticle

Forecasting Follies: Machine Learning from Human Errors

by Li Sun and Yongchen Zhao

J. Risk Financial Manag. 2025, 18(2), 60; https://doi.org/10.3390/jrfm18020060 - 28 Jan 2025

Reliable inflation forecasts are essential for both business operations and macroeconomic policy making. This study explores the potential of using machine learning (ML) techniques to improve the accuracy of human forecasts of inflation. Specifically, we develop and examine ML-centered forecast adjustment procedures where [...] Read more.

Reliable inflation forecasts are essential for both business operations and macroeconomic policy making. This study explores the potential of using machine learning (ML) techniques to improve the accuracy of human forecasts of inflation. Specifically, we develop and examine ML-centered forecast adjustment procedures where advanced ML techniques are employed to predict and thus mitigate the errors of human forecasts, akin to how an AI-powered spell and grammar checker helps to prevent mistakes in human writing. Our empirical exercises demonstrate the benefits of several popular ML techniques, such as the elastic net, LASSO, and ridge regressions, and provide evidence of their ability to improve both our own benchmark inflation forecasts and those reported by the frequent participants in the US Survey of Professional Forecasters. The forecast adjustment procedures proposed in this paper are conceptually appealing, widely applicable, and empirically effective in reducing forecast bias and improving forecast accuracy. Full article

(This article belongs to the Special Issue Forecasting, Predictive Analytics and Econometrics in Business Research)

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15 pages, 778 KiB

Open AccessArticle

The Call to Shift from the Narrow Legalistic to the Broader Moral and Legal Stakeholder Model in Indonesian State-Owned Enterprises: Its Implications and Challenges

by Yafet Yosafet Wilben Rissy

J. Risk Financial Manag. 2025, 18(2), 59; https://doi.org/10.3390/jrfm18020059 - 28 Jan 2025

This article aims to elaborate on the narrow legalistic stakeholder model and the need to apply a new revised moral and legal stakeholder model in Indonesian state-owned enterprises (SOEs) with its implications and challenges. Studies on the narrow legalistic stakeholder model in Indonesian [...] Read more.

This article aims to elaborate on the narrow legalistic stakeholder model and the need to apply a new revised moral and legal stakeholder model in Indonesian state-owned enterprises (SOEs) with its implications and challenges. Studies on the narrow legalistic stakeholder model in Indonesian SOEs are still uncommon, despite the rising awareness of the model. This study expects to initiate discourse on the ideal stakeholder model in the industry. This study combined doctrinal and empirical legal research methods. The SOE laws and the Minister of SOEs’ regulations were examined aside from the investigation of empirical data on the accusation of SOEs breaching their obligations to their legitimate stakeholders as indicated in court decisions and mass media publications. This study shows that the Minister of SOEs’ Regulation on Implementing Corporate Governance Implementation has promoted a narrow legalistic approach to the stakeholder model. As a result, only those who have a written contract with SOEs can be considered as the legitimate direct stakeholders. This approach has led to the expropriation of other indirect legitimate stakeholders of the SOEs. This study can be used to revise the narrow legalistic stakeholder model and to strengthen research on the stakeholder model in SOEs and corporate governance. Full article

(This article belongs to the Special Issue Featured Papers in Corporate Finance and Governance)

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