Journal Description
International Journal of Financial Studies
International Journal of Financial Studies
is an international, peer-reviewed, scholarly open access journal on financial market, instruments, policy, and management research published quarterly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), EconLit, EconBiz, RePEc, and other databases.
- Journal Rank: CiteScore - Q2 (Finance)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 27.6 days after submission; acceptance to publication is undertaken in 8.5 days (median values for papers published in this journal in the second half of 2023).
- 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.
Impact Factor:
2.3 (2022);
5-Year Impact Factor:
2.1 (2022)
Latest Articles
Dynamic Capital Structure Adjustment: An Integrated Analysis of Firm-Specific and Macroeconomic Factors in Korean Firms
Int. J. Financial Stud. 2024, 12(1), 26; https://doi.org/10.3390/ijfs12010026 - 12 Mar 2024
Abstract
This research investigates the factors influencing the capital structure of 271 non-financial firms listed on the Korean Stock Exchange (KSE) over a broad period from 1995 to 2021, encompassing both stable and crisis conditions. Employing a dynamic panel data model and the generalized
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This research investigates the factors influencing the capital structure of 271 non-financial firms listed on the Korean Stock Exchange (KSE) over a broad period from 1995 to 2021, encompassing both stable and crisis conditions. Employing a dynamic panel data model and the generalized method of moments (GMM) estimation, we address the endogeneity issue introduced by the inclusion of lagged dependent variables. Our research integrates firm-specific internal factors with macroeconomic external variables to provide a comprehensive understanding of the influence of varying economic environments on capital structure. Our study suggests that in times of economic stability, the capital structure decisions of a firm are more influenced by internal factors such as profitability. However, in periods of economic downturns, it is the external macroeconomic market conditions that tend to have a greater impact on these decisions. It is also noteworthy that both book leverage (BL) and market leverage (ML) exhibit quicker adjustments during stable periods as opposed to periods of crisis. This indicates a higher agility of firms in adapting their capital structures in stable, normal conditions. Our findings contribute to the existing literature by offering a holistic view of capital structure determinants in Korean firms. They underscore the necessity of adaptable financial strategies that account for both internal dynamics and external economic conditions. This study fills a gap in current research, presenting new insights into the dynamics of capital structure in Korean firms and suggesting a multifaceted approach to understanding capital structure in diverse economic contexts.
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Open AccessArticle
Quantifying Impact, Uncovering Trends: A Comprehensive Bibliometric Analysis of Shadow Banking and Financial Contagion Dynamics
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Ionuț Nica, Camelia Delcea, Nora Chiriță and Ștefan Ionescu
Int. J. Financial Stud. 2024, 12(1), 25; https://doi.org/10.3390/ijfs12010025 - 05 Mar 2024
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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
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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.
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Open AccessArticle
Decision Rules for Corporate Investment
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Reinier de Adelhart Toorop, Dirk Schoenmaker and Willem Schramade
Int. J. Financial Stud. 2024, 12(1), 24; https://doi.org/10.3390/ijfs12010024 - 04 Mar 2024
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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
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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.
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Open AccessFeature PaperArticle
Predicting Healthcare Mutual Fund Performance Using Deep Learning and Linear Regression
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Anuwat Boonprasope and Korrakot Yaibuathet Tippayawong
Int. J. Financial Stud. 2024, 12(1), 23; https://doi.org/10.3390/ijfs12010023 - 29 Feb 2024
Abstract
Following the COVID-19 pandemic, the healthcare sector has emerged as a resilient and profitable domain amidst market fluctuations. Consequently, investing in healthcare securities, particularly through mutual funds, has gained traction. Existing research on predicting future prices of healthcare securities has been predominantly reliant
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Following the COVID-19 pandemic, the healthcare sector has emerged as a resilient and profitable domain amidst market fluctuations. Consequently, investing in healthcare securities, particularly through mutual funds, has gained traction. Existing research on predicting future prices of healthcare securities has been predominantly reliant on historical trading data, limiting predictive accuracy and scope. This study aims to overcome these constraints by integrating a diverse set of twelve external factors spanning economic, industrial, and company-specific domains to enhance predictive models. Employing Long Short-Term Memory (LSTM) and Multiple Linear Regression (MLR) techniques, the study evaluates the effectiveness of this multifaceted approach. Results indicate that incorporating various influencing factors beyond historical data significantly improves price prediction accuracy. Moreover, the utilization of LSTM alongside this comprehensive dataset yields comparable predictive outcomes to those obtained solely from historical data. Thus, this study highlights the potential of leveraging diverse external factors for more robust forecasting of mutual fund prices within the healthcare sector.
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(This article belongs to the Topic Artificial Intelligence Applications in Financial Technology)
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Revisiting the Effect of Dividend Policy on Firm Performance and Value: Empirical Evidence from the Korean Market
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Okechukwu Enyeribe Njoku and Younghwan Lee
Int. J. Financial Stud. 2024, 12(1), 22; https://doi.org/10.3390/ijfs12010022 - 28 Feb 2024
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
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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.
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(This article belongs to the Special Issue Corporate Finance)
Open AccessArticle
The Use of Economic Indicators as Early Signals of Stock Market Progress: Perspectives from Market Potential Index
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Tarek Eldomiaty, Islam Azzam, Mostafa Fouad and Yasmeen Said
Int. J. Financial Stud. 2024, 12(1), 21; https://doi.org/10.3390/ijfs12010021 - 26 Feb 2024
Abstract
The progress of financial markets depends on the way world investors foresee the market potential of the country of choice. Countries that are associated with favorable economic incentives are able to motivate investments in their respective stock markets. The objective of this paper
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The progress of financial markets depends on the way world investors foresee the market potential of the country of choice. Countries that are associated with favorable economic incentives are able to motivate investments in their respective stock markets. The objective of this paper is to examine the role of the many economic components which constitute the Market Potential Index in enhancing stock market progress. The methodology goes through testing and estimation. The tests include linearity versus nonlinearity (RESET), normality, and cointegration. The estimation includes cointegration regression and discriminant analysis to distinguish between high and low stock market progress. This study examines unbalanced panel data that covers the years 1996–2022 for 54 countries where a stock market exists. The results show the following: (a) increases in people’s expenditure result in decreases in consumption of investment in financial securities; (b) the investments in infrastructure technology is positively associated with stock market progress; (c) the positive effect of economic freedom indicates that further adaptive trading regulations are beneficial to stock market progress; (d) increases in imports consume large proportions of people’s income, coming at the expense of investment in financial securities; (e) stock markets that are associated with high country risk are characterized by a positive risk–return tradeoff, i.e., a high risk premium; (f) the stock markets listed in the MPI can reach high progress by improving three indicators, namely commercial infrastructure, market receptivity, and country risk. This paper offers a thorough and unique examination of the institutional arrangements and stock market progress. The paper offers a guide to policy makers about how economic institutional arrangements can be promoted in order to reach high stock market progress.
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Open AccessArticle
Assessing Energy Mutual Funds: Performance, Risks, and Managerial Skills
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Davinder Malhotra and Srinivas Nippani
Int. J. Financial Stud. 2024, 12(1), 20; https://doi.org/10.3390/ijfs12010020 - 26 Feb 2024
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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
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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.
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Open AccessArticle
Synthetic Central Bank Digital Currencies and Systemic Liquidity Risks
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John E. Marthinsen and Steven R. Gordon
Int. J. Financial Stud. 2024, 12(1), 19; https://doi.org/10.3390/ijfs12010019 - 18 Feb 2024
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
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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.
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Open AccessArticle
Impacts of Investor Attention and Accounting Information Comparability on Stock Returns: Empirical Evidence from Chinese Listed Companies
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Li Zhao, Nathee Naktnasukanjn, Ahmad Yahya Dawod and Bin Zhang
Int. J. Financial Stud. 2024, 12(1), 18; https://doi.org/10.3390/ijfs12010018 - 14 Feb 2024
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The efficient capital markets hypothesis (EMH) posits that security prices incorporate all available information in capital markets. Nevertheless, real stock markets often exhibit speculative behavior due to information asymmetry and the limited rationality of investors. This paper employs statistical analysis, a multiple regression
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The efficient capital markets hypothesis (EMH) posits that security prices incorporate all available information in capital markets. Nevertheless, real stock markets often exhibit speculative behavior due to information asymmetry and the limited rationality of investors. This paper employs statistical analysis, a multiple regression approach, and robustness tests to investigate the impact of investor attention and accounting information comparability on stock returns. We collected monthly data from all Chinese A-share stocks listed on the main board of the Shanghai Stock Exchange for the period 2017–2021. Our findings reveal a significant positive correlation between current investor attention and current monthly stock returns and a significant negative correlation between lagged investor attention and current monthly stock returns. Moreover, accounting information comparability serves as a substantial moderator, amplifying the positive effect of current investor attention on current stock returns and mitigating the negative impact of lagged investor attention. We investigate the indicator of accounting information comparability from the perspective of investor attention. Significantly, we use accounting information comparability as a moderating variable for the first time to assess its influence on stock returns. Our results demonstrate that accounting information comparability significantly contributes to mitigating excessive share price declines and stimulating share price increases. This discovery also acts as an internal driver for listed companies to proactively improve accounting information comparability.
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Open AccessArticle
Board Expertise Background and Firm Performance
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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
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
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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.
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(This article belongs to the Topic Artificial Intelligence Applications in Financial Technology)
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Open AccessArticle
Exploring the Dynamics of Profitability–Liquidity Relations in Crisis, Pre-Crisis and Post-Crisis
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Piotr Ratajczak, Dawid Szutowski and Jarosław Nowicki
Int. J. Financial Stud. 2024, 12(1), 16; https://doi.org/10.3390/ijfs12010016 - 10 Feb 2024
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The aim of this study is to verify the stability of the profitability–liquidity relationship over time, as well as to determine this relationship in terms of its level and structure. In this context, three main research questions were formulated. First, is the profitability–liquidity
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The aim of this study is to verify the stability of the profitability–liquidity relationship over time, as well as to determine this relationship in terms of its level and structure. In this context, three main research questions were formulated. First, is the profitability–liquidity relationship stable in times of crisis? Second, what is the profitability of companies with high and low liquidity? Third, what is the liquidity of companies with high and low profitability? This study uses a self-organizing map (SOM), a data visualization technique that is a type of artificial neural network trained in an unsupervised manner. A dataset covering the period from 2019 to 2021, consisting of 300 Polish companies from the wholesale and retail sectors, was used. The main results of this study indicate that: (1) companies with a balanced profitability–liquidity relationship in the pre-crisis period (2019) maintained this relationship in the crisis (2020) and post-crisis periods (2021); (2) companies in the clusters with the relatively highest and lowest profitability have the relatively lowest and moderate liquidity both before and after the crisis period; (3) the majority of companies during non-crisis periods demonstrate that profitability is not reliant on liquidity, suggesting an absence of a clear relationship; (4) in the post-crisis period, companies with the relatively lowest operating cash flow margin (OCFM) exhibited the relatively highest net profit margin (NPM) and other profitability ratios, as opposed to the pre-crisis and crisis periods. This study fills the gap resulting from the incomplete—most of all static—understanding of the relationship between profitability and liquidity. Moreover, this study employs a self-organizing map (SOM) which has not been used in the literature regarding the research area undertaken.
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Open AccessArticle
Velocity of Money and Productivity Growth: Explaining the 2% Inflation Target in the U.S. (1959–2007)
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Christophe Faugere
Int. J. Financial Stud. 2024, 12(1), 15; https://doi.org/10.3390/ijfs12010015 - 08 Feb 2024
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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
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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.
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Open AccessArticle
Impact of the COVID-19 Market Turmoil on Investor Behavior: A Panel VAR Study of Bank Stocks in Borsa Istanbul
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Cumhur Ekinci and Oğuz Ersan
Int. J. Financial Stud. 2024, 12(1), 14; https://doi.org/10.3390/ijfs12010014 - 04 Feb 2024
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Assuming that investors can be foreign or local, do high-frequency trading (HFT) or not, and submit orders through a bank-owned or non-bank-owned broker, we associated trades to various investors. Then, building a panel vector autoregressive model, we analyzed the dynamic relation of these
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Assuming that investors can be foreign or local, do high-frequency trading (HFT) or not, and submit orders through a bank-owned or non-bank-owned broker, we associated trades to various investors. Then, building a panel vector autoregressive model, we analyzed the dynamic relation of these investors with returns and among each other before and during the COVID-19 market crash. Results show that investor groups have influence on each other. Their net purchases also interact with returns. Moreover, during the turmoil caused by the pandemic, except foreign investors not involved in HFT, the response of any investor group (retail/institutional, domestic investors doing HFT and those not doing HFT, and foreign investors doing HFT) significantly altered. This shows that the interrelation among investor groups is dynamic and sensitive to market conditions.
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Open AccessArticle
Board Structure, CEO Equity-Based Compensation, and Financial Performance: Evidence from MENA Countries
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Abdullah A. Aljughaiman, Abdulateif A. Almulhim and Abdulaziz S. Al Naim
Int. J. Financial Stud. 2024, 12(1), 13; https://doi.org/10.3390/ijfs12010013 - 31 Jan 2024
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This paper investigates the association between board of director (BOD) structures and CEO equity-based compensation (long-term incentive) for commercial banks (conventional and Islamic banks) in MENA countries. Specifically, we take board size and board independence to measure the board structure. Furthermore, we investigate
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This paper investigates the association between board of director (BOD) structures and CEO equity-based compensation (long-term incentive) for commercial banks (conventional and Islamic banks) in MENA countries. Specifically, we take board size and board independence to measure the board structure. Furthermore, we investigate the influence of board structure on the association between CEO equity-based compensation and financial performance. Moreover, we compare conventional and Islamic banks in testing these relationships. Using a sample of 65 banks in MENA countries for the period between 2009 and 2020, we show a significant positive association between board size and CEO compensation. However, we find the same association between these variables for IBs, but the effect of board size on CEO compensation is less. We also show that board independence is negatively correlated with CEO compensation. Nevertheless, the relationship between board independence and CEO ownership is positive for IBs. For the moderating test, we find that effective board structure provides more incentives to the CEO, leading them to achieve higher financial performance. The Islamic bank’s business model (based on Shari’ah principles) contributes to the different influences of board structure on CEO compensation. Our results provide the insight that a strong and effective board is important for managing the executive’s compensation system. The findings of this study have implications for financial firms, policymakers, and regulators. Specifically, the study may help in understanding the benefits of different compensation structures relative to different types of financial firms.
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Open AccessArticle
Determinants of Operating Efficiency for the Jordanian Banks: A Panel Data Econometric Approach
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Rasha Istaiteyeh, Maysa’a Munir Milhem, Farah Najem and Ahmed Elsayed
Int. J. Financial Stud. 2024, 12(1), 12; https://doi.org/10.3390/ijfs12010012 - 31 Jan 2024
Abstract
This paper presents a comprehensive analysis of key financial indicators influencing the operational efficiency of banks in Jordan over the period 2006 to 2021. The study, focusing on fifteen commercial banks, employs seven regression models to assess the impact of selected variables on
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This paper presents a comprehensive analysis of key financial indicators influencing the operational efficiency of banks in Jordan over the period 2006 to 2021. The study, focusing on fifteen commercial banks, employs seven regression models to assess the impact of selected variables on bank operating efficiency. Our findings reveal novel insights with substantial contributions to banking practice. We identify a statistically significant influence of both bank-specific factors and temporal effects, demonstrating the nuanced dynamics shaping the operational efficiency of Jordanian banks. Notably, a positive and significant correlation is established between the operating efficiency ratio and return on assets, bank size, and the ratio of loan loss provisions to net interest income, providing valuable strategic guidance for effective management. Conversely, a significant negative relationship is observed between the operating efficiency ratio and the total expense ratio, underscoring the critical importance of careful cost management. No significant associations are found between the operating efficiency ratio and credit risk, the equity-to-asset ratio, the deposit-to-liability ratio, and the equity-to-liability ratio. This study makes a unique contribution by shedding light on these previously unexplored correlations, offering actionable insights for enhancing operational efficiency in the banking sector. Additionally, our research advocates for the Central Bank of Jordan (CBJ) to persist in adaptive policy measures, which are crucial for ongoing banking reforms and improved monitoring practices. Based on our empirical findings, these recommendations aim to fortify the resilience and adaptability of Jordan’s banking sector, contributing both academically and practically. Importantly, they reinforce the symbiotic link between a stable banking sector and sustained economic development in Jordan.
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Open AccessArticle
Predicting Operating Income via a Generalized Operating-Leverage Model
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Sherwood Lane Lambert, Kevin Krieger and Nathan Mauck
Int. J. Financial Stud. 2024, 12(1), 11; https://doi.org/10.3390/ijfs12010011 - 23 Jan 2024
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We propose a generalized, practitioner-oriented operating-leverage model for predicting operating income using net sales, cost of sales, depreciation, and SG&A. Prior research links operating income directly to these items; hence, our model includes all aggregate revenues and expenses that comprise operating income. Prior
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We propose a generalized, practitioner-oriented operating-leverage model for predicting operating income using net sales, cost of sales, depreciation, and SG&A. Prior research links operating income directly to these items; hence, our model includes all aggregate revenues and expenses that comprise operating income. Prior research finds that the cost of sales is “much less” sticky than depreciation and SG&A; hence, we use the cost of sales as a proxy for the total variable costs and depreciation and SG&A as proxies for the sticky fixed costs. We introduce a new adjustment to the textbook operating-leverage model so that the ratio of sales to the cost of sales remains constant for the reference and forecast periods. Inspired by prior research, we adjust depreciation and SG&A for cost stickiness. We find that using our generalized operating-leverage model improves the forecast accuracy of next-quarter and next-year operating income predictions compared to predictions made using textbook operating leverage, which is a special case of our model.
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Open AccessArticle
How Local Finance and Enforcement Shaped SME Credit Choices before and during the COVID Crisis
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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
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
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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.
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(This article belongs to the Special Issue Bank Funding and Corporate Financial Policies during COVID-19 and FinTech Period)
Open AccessArticle
Firms’ Investment Level and (In)Efficiency: The Role of Accounting Information System Quality
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Cláudia Pereira, Beatriz Castro, Luís Gomes and Helena Canha
Int. J. Financial Stud. 2024, 12(1), 9; https://doi.org/10.3390/ijfs12010009 - 18 Jan 2024
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We investigate whether accounting information system quality has an impact on the level and efficiency of firms’ investments. While firms’ growth depends on investment and financing decisions, accounting information is fundamental for the decision-making of several stakeholders. We assess the accounting information system
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We investigate whether accounting information system quality has an impact on the level and efficiency of firms’ investments. While firms’ growth depends on investment and financing decisions, accounting information is fundamental for the decision-making of several stakeholders. We assess the accounting information system quality by discretionary accruals, whereas the investment inefficiency is estimated by the residuals of an investment regression for a sample of 3073 Portuguese SMEs from 27 industries, over the period from 2016 to 2021 using a panel regression analysis. The empirical evidence suggests that firms exhibiting higher accounting information system quality tend to invest more. In addition, firms with a lower accounting information system quality have more inefficient investments, as they tend to engage in more overinvestment, although this is not significant for underinvestment. Therefore, this study provides new evidence regarding the impact of accounting information systems on investment that may be useful for several stakeholders, such as managers, creditors, regulators, and academics, by providing evidence for SMEs, where empirical studies are scarce.
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(This article belongs to the Special Issue Accounting and Financial/Non-financial Reporting Developments)
Open AccessArticle
Is Artificial Intelligence Really More Accurate in Predicting Bankruptcy?
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Stanislav Letkovský, Sylvia Jenčová and Petra Vašaničová
Int. J. Financial Stud. 2024, 12(1), 8; https://doi.org/10.3390/ijfs12010008 - 18 Jan 2024
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
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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?
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Bank Market Power, Firm Performance, Financing Costs and Capital Structure
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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
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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
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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.
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