International Journal of Financial Studies

56 pages, 2800 KiB

Open AccessEditor’s ChoiceArticle

Forecasting Selected Commodities’ Prices with the Bayesian Symbolic Regression

by Krzysztof Drachal and Michał Pawłowski

Int. J. Financial Stud. 2024, 12(2), 34; https://doi.org/10.3390/ijfs12020034 - 29 Mar 2024

Viewed by 1592

This study firstly applied a Bayesian symbolic regression (BSR) to the forecasting of numerous commodities’ prices (spot-based ones). Moreover, some features and an initial specification of the parameters of the BSR were analysed. The conventional approach to symbolic regression, based on genetic programming, [...] Read more.

This study firstly applied a Bayesian symbolic regression (BSR) to the forecasting of numerous commodities’ prices (spot-based ones). Moreover, some features and an initial specification of the parameters of the BSR were analysed. The conventional approach to symbolic regression, based on genetic programming, was also used as a benchmark tool. Secondly, various other econometric methods dealing with variable uncertainty were estimated including Bayesian Model Averaging, Dynamic Model Averaging, LASSO, ridge, elastic net, and least-angle regressions, etc. Therefore, this study reports a concise and uniform comparison of an application of several popular econometric models to forecasting the prices of numerous commodities. Robustness checks and statistical tests were performed to strengthen the obtained conclusions. Monthly data beginning from January 1988 and ending in August 2021 were analysed. Full article

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16 pages, 494 KiB

Open AccessEditor’s ChoiceArticle

Crowdfunding versus Traditional Banking: Alternative or Complementary Systems for Financing Projects in Portugal?

by Bruno Torres, Zélia Serrasqueiro and Márcio Oliveira

Int. J. Financial Stud. 2024, 12(2), 33; https://doi.org/10.3390/ijfs12020033 - 29 Mar 2024

Viewed by 1214

Abstract

In an era where crowdfunding in Portugal is garnering increased public attention, exemplified by notable campaigns like the recent funding of the nurses’ strike, we explore its potential as an alternative financial source to traditional banking. Through a comprehensive case study, we delve [...] Read more.

In an era where crowdfunding in Portugal is garnering increased public attention, exemplified by notable campaigns like the recent funding of the nurses’ strike, we explore its potential as an alternative financial source to traditional banking. Through a comprehensive case study, we delve into pertinent issues, encompassing European legislation, market dynamics, and a survey disseminated to representatives of the four prominent Portuguese crowdfunding platforms. Comprising forty-one questions across four categories, the survey extracts insights on platform details, company/project information, investor perspectives, and the financing process, along with an evaluation of platform advantages/disadvantages vis-à-vis traditional banking. Despite heightened visibility, crowdfunding remains relatively unfamiliar to the broader public, yet it diverges from banking not as a substitute but as a complementary financial mechanism. Emphasizing accessibility, process agility, and reduced bureaucracy, crowdfunding serves as a means of swiftly gaining recognition for a company or project while tapping into a broad audience. Rather than competition, it offers supplementary support, facilitating the identification and validation of investment opportunities and concepts. Moreover, it streamlines subsequent interactions with banks and investors, enhancing confidence in a project’s viability. In essence, crowdfunding emerges not as an alternative but a strategic complement, enriching the financial landscape with its unique attributes. Full article

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16 pages, 276 KiB

Open AccessEditor’s ChoiceArticle

How Audit Fees Impact Earnings Management in Service Companies on the Amman Stock Exchange through Audit Committee Characteristics

by Ayman Shehadeh, Mahmoud Daoud Daoud Nassar, Husam Shrouf and Mohammad Haroun Sharairi

Int. J. Financial Stud. 2024, 12(2), 32; https://doi.org/10.3390/ijfs12020032 - 26 Mar 2024

Viewed by 966

Abstract

The primary objective of this research was to investigate the potential moderating role of audit fees in the relationship between audit committee characteristics and earnings management. Specifically, this study aimed to establish connections between audit committee features, such as committee size, member independence, [...] Read more.

The primary objective of this research was to investigate the potential moderating role of audit fees in the relationship between audit committee characteristics and earnings management. Specifically, this study aimed to establish connections between audit committee features, such as committee size, member independence, and financial expertise, and the practice of earnings management. To address these research questions, a convenient sample of 46 service providers listed on the Amman Stock Exchange between 2016 and the subsequent year was employed. Descriptive statistical methods were applied to characterize the variables under investigation, while a multiple regression model was utilized to assess the study’s hypotheses. The findings of the study revealed that there was no significant correlation between the size of the audit committee and earnings management. However, a negative correlation was observed between the audit committee’s independence and the financial expertise of its members. Importantly, when audit fees were introduced as a moderating variable, the relationships between committee member independence and earnings management, as well as between committee member financial expertise and earnings management, were found to be weakened. These results have potential implications for policymakers and regulators in Jordan. They may offer valuable insights into corporate governance reforms that could assist Jordanian businesses in enhancing their earnings management practices. Full article

17 pages, 251 KiB

Open AccessEditor’s ChoiceArticle

Venture Capital and Dividend Policy

by Yi Tan, Xiaoli Wang and Xiaoyu Fu

Int. J. Financial Stud. 2024, 12(1), 27; https://doi.org/10.3390/ijfs12010027 - 19 Mar 2024

Viewed by 1152

Abstract

In this paper, we empirically examine the impact of venture capital investment on the dividend policy of the invested companies using a sample of list companies from China’s ChiNext market during the period 2014 to 2019. Our empirical results show that different types [...] Read more.

In this paper, we empirically examine the impact of venture capital investment on the dividend policy of the invested companies using a sample of list companies from China’s ChiNext market during the period 2014 to 2019. Our empirical results show that different types of VC investments have different impacts on the dividend policies of the invested companies. To be specific, we found independent venture capital companies (IVCs) promote the company’s dividend payment and increase the level of dividend payments while corporate venture capital (CVC) inhibits the company’s dividend payment. The joint participation of multiple types of venture capital investment (syndication) also increases the company’s dividend distribution. Our main contributions are two-fold. First, we provide a comprehensive analysis in the field of VC and dividend policy; second, we differentiate VC from the perspective of investment objectives and examine its different impacts on the dividend policies of the invested companies. Full article

35 pages, 10470 KiB

Open AccessEditor’s ChoiceArticle

Quantifying Impact, Uncovering Trends: A Comprehensive Bibliometric Analysis of Shadow Banking and Financial Contagion Dynamics

by Ionuț Nica, Camelia Delcea, Nora Chiriță and Ștefan Ionescu

Int. J. Financial Stud. 2024, 12(1), 25; https://doi.org/10.3390/ijfs12010025 - 5 Mar 2024

Cited by 1 | Viewed by 1515

Abstract

This study describes a comprehensive bibliometric analysis of shadow banking and financial contagion dynamics from 1996 to 2022. Through a holistic approach, our study focuses on quantifying the impact and uncovering significant trends in scientific research related to these interconnected fields. Using advanced [...] Read more.

This study describes a comprehensive bibliometric analysis of shadow banking and financial contagion dynamics from 1996 to 2022. Through a holistic approach, our study focuses on quantifying the impact and uncovering significant trends in scientific research related to these interconnected fields. Using advanced bibliometric methods, we explored the global network of publications, identifying key works, influential authors, and the evolution of research over time. The results of the bibliometric analysis have highlighted an annual growth rate of 22.05% in publications related to the topics of shadow banking and financial contagion, illustrating researchers’ interest and the dynamic nature of publications over time. Additionally, significant increases in scientific production have been recorded in recent years, reaching a total of 178 articles published in 2022. The most predominant keywords used in research include “systemic risks”, “risk assessment”, and “measuring systemic risk”. The thematic evolution has revealed that over time, the focus on fundamental concepts used in analyzing these two topics has shifted, considering technological advancements and disruptive events that have impacted the economic and financial system. Our findings provide a detailed insight into the progress, gaps, and future directions in understanding the complex interplay of shadow banking and financial contagion. Our study represents a valuable asset for researchers, practitioners, and policymakers with a keen interest in understanding the dynamics of these critical components within the global financial system. Full article

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15 pages, 729 KiB

Open AccessEditor’s ChoiceArticle

Decision Rules for Corporate Investment

by Reinier de Adelhart Toorop, Dirk Schoenmaker and Willem Schramade

Int. J. Financial Stud. 2024, 12(1), 24; https://doi.org/10.3390/ijfs12010024 - 4 Mar 2024

Cited by 1 | Viewed by 1749

Abstract

We investigate the decision rules for corporate investment by designing a company value frontier. This company value frontier allows for balancing the financial value and social and environmental impacts. This article develops novel value concepts—ranging from shareholder value to shareholder welfare and integrated [...] Read more.

We investigate the decision rules for corporate investment by designing a company value frontier. This company value frontier allows for balancing the financial value and social and environmental impacts. This article develops novel value concepts—ranging from shareholder value to shareholder welfare and integrated value—resulting in varying preferences for social and environmental impacts or values. Next, these preferences are incorporated in investment decision rules. The traditional net present value (NPV) rule optimises only the financial value. We propose a new integrated present value (IPV) decision rule that includes a preference for social and environmental values without neglecting the financial value. By applying the new IPV rule, responsible companies are able to achieve more sustainable outcomes. Full article

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36 pages, 428 KiB

Open AccessEditor’s ChoiceArticle

Revisiting the Effect of Dividend Policy on Firm Performance and Value: Empirical Evidence from the Korean Market

by Okechukwu Enyeribe Njoku and Younghwan Lee

Int. J. Financial Stud. 2024, 12(1), 22; https://doi.org/10.3390/ijfs12010022 - 28 Feb 2024

Viewed by 2470

Abstract

This study investigates the relationship between dividend policy, firm performance, and value within the Korean market, taking into account the unique context of Chaebol ownership structures. Utilizing a robust dataset of 5478 observations from the Korean Composite Stock Price Index, our empirical analysis [...] Read more.

This study investigates the relationship between dividend policy, firm performance, and value within the Korean market, taking into account the unique context of Chaebol ownership structures. Utilizing a robust dataset of 5478 observations from the Korean Composite Stock Price Index, our empirical analysis employs advanced regression models, revealing distinctive effects of various dividend policy measures through the lenses of interest alignment and managerial entrenchment hypotheses. Surprisingly, while cash dividend payments exhibit a robust positive impact on Tobin’s Q and market-to-book ratios, suggesting an overall positive link with market valuations, a closer inspection reveals divergent impacts for Chaebol and non-Chaebol firms. In Chaebol entities, dividend policy proxies consistently demonstrate positive effects on performance metrics, aligning with the interest alignment hypothesis and highlighting strategic signaling efforts. Conversely, non-Chaebol firms exhibit intriguingly negative impacts, supporting the managerial entrenchment hypothesis and implying potential challenges to market value. Firms should prioritize transparent communication on dividend policies for improved investor decision making and enhanced corporate governance in the dynamic Korean market. Full article

(This article belongs to the Special Issue Corporate Finance)

18 pages, 733 KiB

Open AccessEditor’s ChoiceArticle

Assessing Energy Mutual Funds: Performance, Risks, and Managerial Skills

by Davinder Malhotra and Srinivas Nippani

Int. J. Financial Stud. 2024, 12(1), 20; https://doi.org/10.3390/ijfs12010020 - 26 Feb 2024

Viewed by 1616

Abstract

This study investigates the risk-adjusted performance of energy equity mutual funds across a 23-year period, employing the Cumulative Wealth Index (CWI) to gauge their long-term performance relative to benchmark indices. Despite inherent volatility due to the energy sector’s cyclical nature, these funds consistently [...] Read more.

This study investigates the risk-adjusted performance of energy equity mutual funds across a 23-year period, employing the Cumulative Wealth Index (CWI) to gauge their long-term performance relative to benchmark indices. Despite inherent volatility due to the energy sector’s cyclical nature, these funds consistently outperformed benchmarks based on monthly returns, showcasing resilience amid market fluctuations. However, challenges emerged during the COVID-19 pandemic, with notable improvements post-vaccination. Utilizing a multi-factor model, the research highlights the interconnectivity of energy equity mutual funds with broader market movements and systemic factors. Despite their primary focus on the energy sector, these funds exhibit sensitivity to larger market trends, rendering them susceptible to market dynamics. Additionally, an assessment of portfolio manager expertise reveals some proficiency in security selection post-vaccinations against COVID-19. Full article

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17 pages, 295 KiB

Open AccessEditor’s ChoiceArticle

Synthetic Central Bank Digital Currencies and Systemic Liquidity Risks

by John E. Marthinsen and Steven R. Gordon

Int. J. Financial Stud. 2024, 12(1), 19; https://doi.org/10.3390/ijfs12010019 - 18 Feb 2024

Viewed by 2440

Abstract

The failure of major banks in 2023, such as Silicon Valley Bank (SVB), Signature Bank, First Republic Bank, and Credit Suisse, points to the continuing need for financial institutions to price liquidity risk properly and for financial systems to find alternative sources of [...] Read more.

The failure of major banks in 2023, such as Silicon Valley Bank (SVB), Signature Bank, First Republic Bank, and Credit Suisse, points to the continuing need for financial institutions to price liquidity risk properly and for financial systems to find alternative sources of liquidity in times of dire need. Central bank digital currencies (CBDCs), fiat-backed stablecoins (fsCOINs), and synthetic central bank digital currencies (sCBDCs) could offer improvements, but each comes with its own set of problems and conditions. Prior research reaches conflicting conclusions about the effect that each of these three financial assets has on systemic bank liquidity and fails to adequately address their net benefits relative to each other. This paper addresses these issues, including those connected to financial disintermediation, bank runs, outsourcing central bank activities, financial interoperability, cash equivalents, maturity transformation, required reserves, and changes in nations’ monetary bases. After addressing the strengths and weaknesses of fsCOINs and CBDCs, we conclude that sCBDCs provide the most significant net liquidity benefits when risks and returns are considered. Full article

15 pages, 1569 KiB

Open AccessEditor’s ChoiceArticle

Board Expertise Background and Firm Performance

by Chiou-Yann Lee, Chun-Ru Wen and Binh Thi-Thanh-Nguyen

Int. J. Financial Stud. 2024, 12(1), 17; https://doi.org/10.3390/ijfs12010017 - 14 Feb 2024

Viewed by 1886

Abstract

This study presents a novel financial performance forecasting method that combines the threshold technique with Artificial Neural Networks (ANN). It applies the threshold regression method to identify the factors within the board of directors that influence the financial performance of traditional industries in [...] Read more.

This study presents a novel financial performance forecasting method that combines the threshold technique with Artificial Neural Networks (ANN). It applies the threshold regression method to identify the factors within the board of directors that influence the financial performance of traditional industries in Taiwan. The findings indicate that the ANN method effectively predicts financial performance by using relevant board structure data. Furthermore, the empirical results suggest that boards with more members demonstrate increased profitability. Additionally, a more significant presence of board members with accounting expertise contributes to more consistent profits. In contrast, an increased presence of members with financial expertise has a more pronounced impact on profitability. Full article

(This article belongs to the Topic Artificial Intelligence Applications in Financial Technology)

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34 pages, 2202 KiB

Open AccessEditor’s ChoiceArticle

Velocity of Money and Productivity Growth: Explaining the 2% Inflation Target in the U.S. (1959–2007)

by Christophe Faugere

Int. J. Financial Stud. 2024, 12(1), 15; https://doi.org/10.3390/ijfs12010015 - 8 Feb 2024

Viewed by 1397

Abstract

This article provides a macro-foundation for why the specific value of 2% is a valid inflation target. The approach postulates that innovations generate transactional cost savings by comparison to barter. The optimal velocity of money is derived as a function of productivity growth [...] Read more.

This article provides a macro-foundation for why the specific value of 2% is a valid inflation target. The approach postulates that innovations generate transactional cost savings by comparison to barter. The optimal velocity of money is derived as a function of productivity growth and of long-term and short-term interest rates, with coefficients reflecting the leverage ratio of depository institutions and the degree of bias in technical progress in the transaction technology. The model is tested for the U.S. (for aggregates M1, M1RS, and M1S) over the period 1959–2007. Setting the inflation target rate equal to the growth rate of velocity leads to an inflation rate near 2% and is akin to pursuing the Friedman k-% rule. This rule provides flexibility to prevent deflation. A long-term Taylor-type rule is derived. A robustness test is also conducted by extending the sample period up to 2023, covering sustained episodes of unconventional U.S. monetary policy. Full article

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16 pages, 324 KiB

Open AccessEditor’s ChoiceArticle

How Local Finance and Enforcement Shaped SME Credit Choices before and during the COVID Crisis

by Francesco Fasano, Maurizio La Rocca, F. Javier Sánchez-Vidal, Maria Josephin Lio and Alfio Cariola

Int. J. Financial Stud. 2024, 12(1), 10; https://doi.org/10.3390/ijfs12010010 - 19 Jan 2024

Viewed by 1456

Abstract

Credit from suppliers is an important source of finance for firms. It can sustain firms’ financial flexibility even in periods of downturn. In this study, using a large database of 90,763 Italian firms in the 2015–2021 period, we investigated how local financial development [...] Read more.

Credit from suppliers is an important source of finance for firms. It can sustain firms’ financial flexibility even in periods of downturn. In this study, using a large database of 90,763 Italian firms in the 2015–2021 period, we investigated how local financial development affects the trade-credit policies of SMEs and how this effect is conditioned by the degree of judicial enforcement. Given that trade credit can be a substitute for bank financing, we find that firms make more use of trade credit in developed financial markets. Moreover, we highlight the finding that a higher degree of judicial enforcement, which reinforces the role of contracts in the market, amplifies this effect. Finally, we observe that the COVID-19 crisis has reduced both the positive effect of local financial development and the positive moderating effect of enforcement in the use of trade credit. Full article

(This article belongs to the Special Issue Bank Funding and Corporate Financial Policies during COVID-19 and FinTech Period)

19 pages, 352 KiB

Open AccessEditor’s ChoiceArticle

Is Artificial Intelligence Really More Accurate in Predicting Bankruptcy?

by Stanislav Letkovský, Sylvia Jenčová and Petra Vašaničová

Int. J. Financial Stud. 2024, 12(1), 8; https://doi.org/10.3390/ijfs12010008 - 18 Jan 2024

Viewed by 1874

Abstract

Predicting bankruptcy within selected industries is crucial because of the potential ripple effects and unique characteristics of those industries. It serves as a risk management tool, guiding various stakeholders in making decisions. While artificial intelligence (AI) has shown high success rates in classification [...] Read more.

Predicting bankruptcy within selected industries is crucial because of the potential ripple effects and unique characteristics of those industries. It serves as a risk management tool, guiding various stakeholders in making decisions. While artificial intelligence (AI) has shown high success rates in classification tasks, it remains uncertain whether its use significantly enhances the potential for early warning of impending problems. The following question arises: will classical methods eventually replace the effectiveness of these advanced techniques? This paper sheds light on the fact that even classical methods continue to achieve results that are not far behind, highlighting their enduring importance in financial analysis. This paper aims to develop bankruptcy prediction models for the chemical industry in Slovakia and to compare their effectiveness. Predictions are generated using the classical logistic regression (LR) method as well as AI techniques, artificial neural networks (ANNs), support vector machines (SVMs), and decision trees (DTs). The analysis aims to determine which of the employed methods is the most efficient. The research sample consists of circa 600 enterprises operating in the Slovak chemical industry. The selection of eleven financial indicators used for bankruptcy prediction was grounded in prior research and existing literature. The results show that all of the explored methods yielded highly similar outcomes. Therefore, determining the clear superiority of any single method is a difficult task. This might be partially due to the potentially reduced quality of the input data. In addition to classical statistical methods employed in econometrics, there is an ongoing development of AI-based models and their hybrid forms. The following question arises: to what extent can these newer approaches enhance accuracy and effectiveness? Full article

21 pages, 581 KiB

Open AccessEditor’s ChoiceArticle

Bank Market Power, Firm Performance, Financing Costs and Capital Structure

by Marisa Pessoa Gonçalves, Pedro M. Nogueira Reis and António Pedro Pinto

Int. J. Financial Stud. 2024, 12(1), 7; https://doi.org/10.3390/ijfs12010007 - 17 Jan 2024

Viewed by 1741

Abstract

In this study, we provide a thorough analysis, conducted on a company-by-company basis, of the impact of bank concentration and the bank-relative power of banks on firm profitability, financing costs, and capital structure in a small economy like Portugal. Using a sample of [...] Read more.

In this study, we provide a thorough analysis, conducted on a company-by-company basis, of the impact of bank concentration and the bank-relative power of banks on firm profitability, financing costs, and capital structure in a small economy like Portugal. Using a sample of 434,990 Portuguese companies, the study spans a time frame of 13 years (from 2006 to 2018). Principal component analysis (PCA) was used to determine bank concentration, and a new variable, “bank-related power”, was introduced. This work employed linear regression with static panel data for fixed and pooled effects, using Driscoll–Kraay standard errors and robust standard error estimation. A direct association was found between business performance and the use of bank credit in highly concentrated banking markets (SMEs), and there is evidence of an inverse relationship when the relative power of banks increases (small business). Evidence also shows that financing costs increase with greater bank concentration, while firms’ capital structure improves under similar conditions. When a bank holds greater relative market power, it tends to exert a negative impact on the capital structure of large companies. However, an inverse relationship is observed in the case of SMEs. Unlike previous studies, the article assesses the effects of bank market power on each of the different companies involved by using both bank concentration (as a composite variable) and a new variable that measures the relative power of banks. Due to its extensive database and expanded time frame, this research is innovative in the context of small-sized companies. Full article

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25 pages, 3436 KiB

Open AccessEditor’s ChoiceArticle

The Efficiency of Alternative and Conventional Energy Exchange-Traded Funds: Are Clean Energy Exchange-Traded Funds a Safer Asset?

by Carla Oliveira Henriques, Maria Elisabete Neves and João Jorge Couceiro

Int. J. Financial Stud. 2024, 12(1), 4; https://doi.org/10.3390/ijfs12010004 - 12 Jan 2024

Viewed by 1473

Abstract

This paper examines the efficiency of alternative energy equity Exchange-Traded Funds (ETFs) and conventional energy equity ETFs from 2018 to 2020, utilizing a combination of an output-oriented Slack-Based Data Envelopment Analysis (DEA) model and cluster analysis. In the context of an output-oriented DEA [...] Read more.

This paper examines the efficiency of alternative energy equity Exchange-Traded Funds (ETFs) and conventional energy equity ETFs from 2018 to 2020, utilizing a combination of an output-oriented Slack-Based Data Envelopment Analysis (DEA) model and cluster analysis. In the context of an output-oriented DEA model, efficiency is defined as the ability of an ETF to maximize its outputs (annualized average return; environmental, social responsibility, and corporate governance; and net asset value) given a fixed level of inputs (expense ratio and beta). The findings indicate that alternative energy ETFs have the potential for long-term outperformance compared to conventional energy ETFs in terms of efficiency. However, during financial crises, the performance differences between the two types of ETFs diminish, with no significant outperformance observed in either category. The expense ratio and net asset value are identified as key factors influencing the efficiency of both ETF types. Additionally, social and governance metrics have a notably stronger positive impact on conventional energy ETFs relative to alternative energy ETFs, highlighting the increasing significance of these factors in financial asset performance. Full article

(This article belongs to the Topic Environmental Social Governance (ESG) Disclosure and Financial Markets)

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