Internal Control Managers’ Accounting Experiences on Audit Quality—Focus on ESG
Islamic Finance in the Era of Financial Technology: A Bibliometric Review of Future Trends
Political Uncertainty and Initial Public Offerings: A Literature Review

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 28.1 days after submission; acceptance to publication is undertaken in 5.4 days (median values for papers published in this journal in the first 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)

Imprint Information Journal Flyer Open Access ISSN: 2227-7072

Latest Articles

Open AccessArticle

The Impact of Artificial Intelligence Disclosure on Financial Performance

Fadi Shehab Shiyyab

Abdallah Bader Alzoubi

Qais Mohammad Obidat

and

Hashem Alshurafat

Int. J. Financial Stud. 2023, 11(3), 115; https://doi.org/10.3390/ijfs11030115 - 14 Sep 2023

Abstract

This study determines to what extent Jordanian banks refer to and use artificial intelligence (AI) technologies in their operation process and examines the impact of AI-related terms disclosure on financial performance. Content analysis is used to analyze the spread of AI and related information in the annual report textual data. Based on content analysis and regression analysis of data from 115 annual reports for 15 Jordanian banks listed in the Amman Stock Exchange for the period 2014 to 2021, the study reveals a consistent increase in the mention of AI-related terms disclosure since 2014. However, the level of AI-related disclosure remains weak for some banks, suggesting that Jordanian banks are still in the early stages of adopting and implementing AI technologies. The results indicate that AI-related keywords disclosure has an influence on banks’ financial performance. AI has a positive effect on accounting performance in terms of ROA and ROE and a negative impact on total expenses, which supports the dominant view that AI improves revenue and reduces cost and is also consistent with past literature findings. This study contributes to the growing body of AI literature, specifically the literature on AI voluntary disclosure, in several aspects. First, it provides an objective measure of the uses of AI by formulating an AI disclosure index that captures the status of AI adoption in practice. Second, it provides insights into the relationship between AI disclosure and financial performance. Third, it supports policymakers’, international authorities’, and supervisory organizations’ efforts to address AI disclosure issues and highlights the need for disclosure guidance requirements. Finally, it provides a contribution to banking sector practitioners who are transforming their operations using AI mechanisms and supports the need for more AI disclosure and informed decision making in a manner that aligns with the objectives of financial institutions. Full article

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

Open AccessArticle

Green Electronic Auditing and Accounting Information Reliability in the Jordanian Social Security Corporation: The Mediating Role of Cloud Computing

Ali Mahmoud Alrabei

Int. J. Financial Stud. 2023, 11(3), 114; https://doi.org/10.3390/ijfs11030114 - 13 Sep 2023

Abstract

The purpose of this research is to examine the impact of green electronic auditing on accounting information reliability and the mediating role of cloud computing in the Jordanian Social Security Corporation. A survey of 500 employees in the Jordanian Social Security Corporation was used to gather data, with a response rate of 31.4% (157 employees). The researcher used structural equation modeling to investigate the connections between cloud computing, auditing on data processing processes, auditing the inputs, auditing the outputs, prior auditing on inputs, and accounting information reliability. The findings revealed that auditing data processing activities, auditing outputs, cloud computing, and earlier auditing on inputs all have a substantial impact on accounting information reliability. However, auditing the inputs and the link between cloud computing and accounting information reliability were not significant. This study’s conclusions have ramifications for policymakers and auditing and accounting practitioners. The Jordanian Social Security Corporation must consider the significance of adequate auditing methods to assure correct accounting information, particularly in the context of cloud computing. This report also highlights the need for more research on the influence of cloud computing on accounting and auditing processes in underdeveloped countries. Full article

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Open AccessArticle

The Dynamic Return and Volatility Spillovers among Size-Based Stock Portfolios in the Saudi Market and Their Portfolio Management Implications during Different Crises

Nassar S. Al-Nassar

Int. J. Financial Stud. 2023, 11(3), 113; https://doi.org/10.3390/ijfs11030113 - 12 Sep 2023

Abstract

This study contributes to the ongoing debate on the size effect and size-based investment styles by investigating the return and volatility spillovers and time-varying conditional correlations among Saudi large-, mid-, and small-cap indices. To this end, we utilize the weekly returns on the MSCI Saudi large-, mid-, and small-cap indices over a long sample period, spanning several crises. The econometric approach that we use is a VAR-asymmetric BEKK-GARCH model which accounts for structural breaks. On the basis of the VAR-asymmetric BEKK-GARCH model estimation results, we calculate portfolio weights and hedge ratios, and discuss their risk management implications. The empirical results confirm the presence of unilateral return spillovers running from mid- to small-cap stocks, while multilateral volatility spillovers are documented, albeit substantially weakened when accounting for structural breaks. The time-varying conditional correlations display clear spikes around crises, which translate to higher hedge ratios, increasing the cost of hedging during turbulent times. The optimal portfolio weights suggest that investors generally overweight large caps in their portfolios during uncertain times to minimize risk without lowering expected returns. The main takeaway from our results is that passively confining fund managers to a particular size category regardless of the prevailing market conditions may lead to suboptimal performance. Full article

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Open AccessArticle

Unveiling Market Connectedness: Dynamic Returns Spillovers in Asian Emerging Stock Markets

Maaz Khan

Mrestyal Khan

Umar Nawaz Kayani

Khurrum Shahzad Mughal

and

Roohi Mumtaz

Int. J. Financial Stud. 2023, 11(3), 112; https://doi.org/10.3390/ijfs11030112 - 12 Sep 2023

Abstract

This study investigates the returns spillovers across the equity markets of Asian emerging economies (China, India, Indonesia, Malaysia, Pakistan, Philippines, South Korea, Taiwan, and Thailand). To achieve this objective, we used two different spillover methodologies (DY 2012 and BK 2018). Moreover, this study used the daily closing prices of equity indices ranging from 5 January 2005 to 13 November 2021. The empirical findings revealed that the total spillover index using DY 2012, and the short-term frequency index using BK 2018, are close to each other, with values of 46.92% and 43.04%, respectively. However, the spillover index value is high, with a value of 56.25% in the long run. Furthermore, the results showed that the stock markets of South Korea and Taiwan are the major spillover transmitters in the Asian emerging markets. Also, the financial association among all emerging Asian equities is at its peak, subject to the mobility of cash flows across the global economies. The results of this study provide meaningful insight for policymakers and investors to implement an effective strategy to overcome the possible influence of any financial crisis in the future. Our paper provides a potential contribution to the financial literature by examining the transmission of spillovers across the Asian emerging stock markets. Furthermore, it provides in-depth information regarding stock market interdependence. Full article

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

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Open AccessArticle

Market Reaction to Corporate Releases and News Articles: Evidence from Thailand’s Stock Market

Likittanawong Supawat

and

Leemakdej Arnat

Int. J. Financial Stud. 2023, 11(3), 111; https://doi.org/10.3390/ijfs11030111 - 06 Sep 2023

Abstract

Studies that quantify the price impact of the information in corporate press releases and news articles mainly focus on quantitative news, such as earnings announcements, dividends, and financial performance-related events, but leave out other corporate news events. Those that do so generally focus on one source of information and do not compare the price impacts from different information sources. Our study aimed to extend previous studies by quantifying and comparing market reactions to corporate press releases and news articles across different news categories. We classified and categorized 100,960 news items, encompassing 26,546 corporate press releases and 74,414 news articles, of 615 firms in the Stock Exchange of Thailand between 1 January 2017 and 31 December 2019. These news items were classified into categories based on the information contained in corporate press releases and news articles. We then studied the market reactions to these news categories. We found that the price impact from corporate releases is sustained for both positive and negative news categories. Our results also show that the positive price impact for news reported by the media tends to reverse, consistent with prior studies. In contrast, the negative price impact from news articles holds; this result differs from previous studies. Our data also show that managers tend to leak and recycle good news while the release of bad news is delayed. Full article

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Open AccessArticle

Enhancing Financial Fraud Detection through Addressing Class Imbalance Using Hybrid SMOTE-GAN Techniques

Patience Chew Yee Cheah

Yue Yang

and

Boon Giin Lee

Int. J. Financial Stud. 2023, 11(3), 110; https://doi.org/10.3390/ijfs11030110 - 05 Sep 2023

Abstract

The class imbalance problem in finance fraud datasets often leads to biased prediction towards the nonfraud class, resulting in poor performance in the fraud class. This study explores the effects of utilizing the Synthetic Minority Oversampling TEchnique (SMOTE), a Generative Adversarial Network (GAN), and their combinations to address the class imbalance issue. Their effectiveness was evaluated using a Feed-forward Neural Network (FNN), Convolutional Neural Network (CNN), and their hybrid (FNN+CNN). This study found that regardless of the data generation techniques applied, the classifier’s hyperparameters can affect classification performance. The comparisons of various data generation techniques demonstrated the effectiveness of the hybrid SMOTE and GAN, including SMOTified-GAN, SMOTE+GAN, and GANified-SMOTE, compared with SMOTE and GAN. The SMOTified-GAN and the proposed GANified-SMOTE were able to perform equally well across different amounts of generated fraud samples. Full article

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

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Open AccessArticle

Effects of Contract Governance on the Relation of Partnership Critical Success Factors and the Performance of Malaysia Public-Private Partnership Initiatives

Azlan Shah Abdul Latif

and

Int. J. Financial Stud. 2023, 11(3), 109; https://doi.org/10.3390/ijfs11030109 - 04 Sep 2023

Abstract

Much research has been carried out to discover partnership critical success factors that influence public-private partnership success. Since most public-private partnership projects are long-term in nature and include contractual arrangements, there is still a lot to learn about contract governance’s role in public-private partnership performance. Therefore, this study examines the effect of contract governance on the relationship between partnership critical success factors and partnership performance in Malaysia. Stakeholder Theory serves as the underpinning theory for this study. This study employed a quantitative method based on the positivist paradigm to distribute questionnaires. The information was collected from 261 contracting parties’ officials in Malaysian public-private partnership projects regulated by the Malaysian Public-Private Partnership Unit, and a stratified random sampling method was employed. The structural equation model analysis found that eight out of ten hypotheses were supported. According to this study, it has been established that contract governance has a direct favorable influence on partnership performance. However, it is also found that contract governance does not moderate the relationship between partnership critical success factors and partnership performance. Due to time constraints and the emergence of the COVID-19 pandemic, this study was from a cross-sectional viewpoint and adopted a quantitative methodology. The findings of this study are important in the contract governance and partnership performance literature, providing policymakers and concessionaires with new information on the impact of contract governance on public-private partnership project performance. Managers of public-private partnership projects should also be able to enhance their projects’ performance by understanding how contract governance influences the performance of their projects. Full article

(This article belongs to the Special Issue Cross-Cultural Corporate Governance, Firm Performance and Firm Value)

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Open AccessReview

A Review of the Implementation of Financial Technology (Fintech) in the Indonesian Agricultural Sector: Issues, Access, and Challenges

and

Int. J. Financial Stud. 2023, 11(3), 108; https://doi.org/10.3390/ijfs11030108 - 04 Sep 2023

Abstract

Technological developments, especially in the financial sector, are slowly changing the financial industry through digitalization towards fintech. The application of fintech has been introduced to Indonesia in the last few years; however, the existence and development of fintech in Indonesia still needs to be studied further. This review provided a comprehensive overview of farmer technology accessibility, fintech preferences, fintech application impacts, fintech application problems, and challenges in the future. The review data are taken from the primary and secondary data related to fintech from numerous publications in Google Scholar, the interview of Indonesian farmers, and Indonesian Government data, including the Central Statistics Agency. This study confirmed that a fintech provider has been developed in Indonesia. The farmers’ accessibility to fintech was different between urban and rural areas due to the farmers’ education levels and the availability of the infrastructure. Fintech can provide practicality, ease of access, comfort, and cost-effectiveness, and can solve existing problems in Indonesian society. However, several problems arise, including infrastructure and internet access that is less supportive, as well as a lack of education, competent workers, and regulation. Agricultural fintech is a promising business in the future, despite the many challenges that need to be overcome for a stronger agricultural sector. Full article

(This article belongs to the Special Issue Literature Reviews in Finance)

Open AccessArticle

Hidden Ownership and Firm Performance: Evidence from Thailand’s Initial Public Offering Firms

Natthawut Wangwan

and

Arnat Leemakdej

Int. J. Financial Stud. 2023, 11(3), 107; https://doi.org/10.3390/ijfs11030107 - 04 Sep 2023

Abstract

Previous studies have overlooked hidden ownership in their analysis, which could result in biased findings. This research utilizes unique data sources to uncover hidden ownership patterns and employs ordinary least square regression to investigate the relationship between hidden ownership and firm performance. The findings indicate that hidden ownership affects a firm’s performance, but not in the same manner as previously thought. Firms with hidden ownership actually perform better than those without. These results contradict the belief that hidden ownership leads to wealth expropriation from minority shareholders and negatively impacts a firm’s performance. The study also remains robust after accounting for potential endogeneity using an instrumental variable approach. The findings provide policy implications and contribute to the ownership and firm performance literatures. Full article

(This article belongs to the Special Issue Cross-Cultural Corporate Governance, Firm Performance and Firm Value)

Open AccessReview

A Systematic Bibliometric Analysis of the Real Estate Bubble Phenomenon: A Comprehensive Review of the Literature from 2007 to 2022

José-Francisco Vergara-Perucich

Int. J. Financial Stud. 2023, 11(3), 106; https://doi.org/10.3390/ijfs11030106 - 23 Aug 2023

Abstract

This article presents the results of a bibliometric review of the study of real estate bubbles in the scientific literature indexed in Web of Science and Scopus, from 2007 to 2022. The analysis was developed using a sample of 2276 documents, which were reviewed in R software and analyzed with the assistance of the Bibliometrix package of the same software. The results indicate that there has been considerable productivity on the topic of real estate bubbles since 2007, with an emphasis on housing price formation processes and the social effects when bubbles burst. The authors found that there were not many case studies located in Latin America or Africa, nor were there approaches with advanced predictive modeling techniques using machine learning or artificial intelligence. The article provides an understanding of the state of the art in real estate bubble research and situates new research in front of the influential literature previously published. Full article

(This article belongs to the Special Issue Literature Reviews in Finance)

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Open AccessArticle

What Influenced Hanoi’s Apartment Price Bubble between 2010 and 2021?

Phuong Lan Le

Anh Tuan Do

and

Anh Ngoc Pham

Int. J. Financial Stud. 2023, 11(3), 105; https://doi.org/10.3390/ijfs11030105 - 17 Aug 2023

Abstract

This study focused on testing the existence of an apartment price bubble in Hanoi (Vietnam) and on determining the factors that affected it in the period between 2010 and 2021. Using the fundamental factor approach, the authors applied VAR regression using time series data. Specifically, we used the ADF unit test to test the stationarity of the variables based on the following criteria: AIC (Akaike information criterion); LR (likelihood ratio); FPE (final prediction error); HQ (Hanan–Quinn information criterion); and Schwarz (SC) to find the optimal lag (Lag) for the model. We also applied the Granger causality test to determine the correlation between the economic variables that appeared in the model with the PR index. We present the results of the research model through the push–response function and the variance decomposition to consider and evaluate the impact of the PR index shock on itself and the other variables. The literature in this field includes many studies that are similar to this one; however, no research has been conducted that has focused on analysing whether variables, such as per capita income and the urbanisation rate, influence the formation of real estate bubbles. This focus is especially relevant in Hanoi, which is an important part of the Vietnamese real estate market. Through this study, we aimed to fill this gap and to contribute to the references on the Hanoi real estate market and its influencing factors. Full article

(This article belongs to the Special Issue Asset Pricing, Investments and Portfolio Management)

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Open AccessReview

Bibliometric Review of Participatory Budgeting: Current Status and Future Research Agenda

Miloš Milosavljević

Željko Spasenić

and

Jovan Krivokapić

Int. J. Financial Stud. 2023, 11(3), 104; https://doi.org/10.3390/ijfs11030104 - 17 Aug 2023

Abstract

Participatory budgeting has been advocated as an advanced tool of civic participation and a travelling innovation for more than three decades. This paper provides a bibliometric review of the concurrent body of knowledge on participatory budgeting (PB), explaining how this democratic innovation ‘travelled’ through time and over different scientific fields. This study was based on a dataset of 396 papers on PB published from 1989 to January 2023. The study finds that research in PB has reached its peak of scholarly attention in pre-COVID-19 pandemic years. The study also finds that the research on PB has migrated from the field of political science to other fields, such as economics, management science, law, urban planning, environmental science, and technology. Full article

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Open AccessReview

Bibliometric Review of Blended Finance and Partial Risk Guarantee: Establishing Needs and Advantages

and

Int. J. Financial Stud. 2023, 11(3), 103; https://doi.org/10.3390/ijfs11030103 - 11 Aug 2023

Abstract

A partial risk guarantee (PRG) is one of the critical instruments in the blended finance approach that provides partial assurance to the risk investor to lend leveraged capital to the borrower. Under the PRG scheme, philanthropic capital is employed as a risk guarantee to create financial and economic additionality through the multiplier effect. This study examines the current trends in PRG and blended finance ecosystem research. This study also aims to identify future research areas to work upon. The bibliometric analysis highlights the need and advantages of blended finance and PRG. The study highlights themes, such as climate finance, SDGs, impact investments, and blended finance/PRGs, from the literature on blended finance. This study illustrates the impact for researchers and managers regarding the future direction to undertake and the domains where PRG can work wonders. The research allows for a comprehensive view of the leading trends, such as utilising blended finance tools such as PRG in funding the work in climate financing, SDGs, water, sanitation, and impact investment. This is perhaps the first study to conduct a bibliometric analysis of the developing area of blended finance partial risk guarantee literature to highlight its importance and advantages. Full article

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Open AccessArticle

Nexus of Financing Constraints and Supply Chain Finance: Evidence from Listed SMEs in China

and

Int. J. Financial Stud. 2023, 11(3), 102; https://doi.org/10.3390/ijfs11030102 - 10 Aug 2023

Abstract

As opposed to developed markets, financing constraints are a more pressing issue among Small and Medium-Sized Enterprises (SMEs) in emerging markets. We explore the severity of financing constraints on SMEs, and examine the role of supply chain finance (SCF) in alleviating those constraints, with the focus on a large emerging market: China. Using the panel data of SMEs listed on Shenzhen Stock Exchange from 2014 to 2020, we employ robust estimations of panel-corrected standard errors (PCSEs) and robust fixed-effects methods to analyze the issue. Our cash–cash-flow sensitivity model points out that listed SMEs in China show significant cash–cash-flow sensitivity, and financing constraints are prevalent. We document that the development of SCF has a mitigation effect on the financing constraints on the SMEs. Our robustness test with Yohai’s MM-estimator is also supportive of the main finding. Our study indicates the importance of supply chain finance development in alleviating the financing constraints on SMEs and, subsequently, supporting their sustainability journey. Overall, our findings have important policy implications for the stakeholders involved in emerging markets, and there are lessons to be learned from the Chinese experience. There is still much to be explored in the nexus of SCF and the financing difficulties of SMEs in China at present, with much of the extant literature concentrating only on specific financing mechanisms. Thus, our study fills the gap by providing a broad and comprehensive analysis of the issue. Full article

Open AccessArticle

Sentiments Extracted from News and Stock Market Reactions in Vietnam

and

Int. J. Financial Stud. 2023, 11(3), 101; https://doi.org/10.3390/ijfs11030101 - 07 Aug 2023

Abstract

News on the stock market contains positive or negative sentiments depending on whether the information provided is favorable or unfavorable to the stock market. This study aims to discover news sentiments and classify news according to its sentiments with the application of PhoBERT, a Natural Language Processing model designed for the Vietnamese language. A collection of nearly 40,000 articles on financial and economic websites is used to train the model. After training, the model succeeds in assigning news to different classes of sentiments with an accuracy level of over 81%. The research also aims to investigate how investors are concerned with the daily news by testing the movements of the market before and after the news is released. The results of the analysis show that there is an insignificant difference in the stock price as a response to the news. However, negative news sentiments can alter the variance of market returns. Full article

(This article belongs to the Special Issue Financial Econometrics and Machine Learning)

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Open AccessArticle

The Effect of Capital Structure on Firm Value: A Study of Companies Listed on the Vietnamese Stock Market

Thi Ngoc Bui

Xuan Hung Nguyen

and

Kieu Trang Pham

Int. J. Financial Stud. 2023, 11(3), 100; https://doi.org/10.3390/ijfs11030100 - 04 Aug 2023

Cited by 1

Abstract

This research investigates the relationship between capital structure and firm value for companies listed on the Vietnamese stock market. The study utilizes data from audited financial statements of 769 companies spanning from 2012 to 2022, amounting to 8459 observations. Employing various estimation methods, such as ordinary least squares (OLS), fixed effects model (FEM), random effects model (REM), and generalized least squares (GLS), the impact of capital structure on key financial indicators, namely, return on assets (ROA), return on equity (ROE), and Tobin’s Q, is assessed. The findings indicate that the debt ratio exhibits a positive influence on ROA, ROE, and Tobin’s Q, with Tobin’s Q displaying the most pronounced impact (0.450) and ROA showing the weakest impact (0.011). However, the long-term debt ratio does not significantly affect firm value. Interestingly, both short-term and long-term debt ratios have negative effects on ROA, ROE, and Tobin’s Q, with the most substantial impact on Tobin’s Q reduction (0.562). Based on these research outcomes, the authors offer valuable recommendations to companies, investors, business leaders, and policymakers to make informed decisions in selecting an optimal and sensible capital structure. Full article

Open AccessArticle

Uncovering the Effect of News Signals on Daily Stock Market Performance: An Econometric Analysis

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Int. J. Financial Stud. 2023, 11(3), 99; https://doi.org/10.3390/ijfs11030099 - 04 Aug 2023

Abstract

The stock markets in developing countries are highly responsive to breaking news and events. Our research explores the impact of economic conditions, financial policies, and politics on the KSE-100 index through daily market news signals. Utilizing simple OLS regression and ARCH/GARCH regression methods, we determine the best model for analysis. The results reveal that political and global news has a significant impact on KSE-100 index. Blue chip stocks are considered safer investments, while short-term panic responses often overshadow rational decision-making in the stock market. Investors tend to quickly react to negative news, making them risk-averse. Our findings suggest that the ARCH/GARCH models are better at predicting stock market fluctuations compared to the simple OLS method. Full article

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

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Open AccessArticle

The Changing Landscape of Financial Credit Risk Models

Tanja Verster

and

Erika Fourie

Int. J. Financial Stud. 2023, 11(3), 98; https://doi.org/10.3390/ijfs11030098 - 04 Aug 2023

Abstract

The landscape of financial credit risk models is changing rapidly. This study takes a brief look into the future of predictive modelling by considering some factors that influence financial credit risk modelling. The first factor is machine learning. As machine learning expands, it becomes necessary to understand how these techniques work and how they can be applied. The second factor is financial crises. Where predictive models view the future as a reflection of the past, financial crises can violate this assumption. This creates a new field of research on how to adjust predictive models to incorporate forward-looking conditions, which include future expected financial crises. The third factor considers the impact of financial technology (Fintech) on the future of predictive modelling. Fintech creates new applications for predictive modelling and therefore broadens the possibilities in the financial predictive modelling field. This changing landscape causes some challenges but also creates a wealth of opportunities. One way of exploiting these opportunities and managing the associated risks is via industry collaboration. Academics should join hands with industry to create industry-focused training and industry-focused research. In summary, this study made three novel contributions to the field of financial credit risk models. Firstly, it conducts an investigation and provides a comprehensive discussion on three factors that contribute to rapid changes in the credit risk predictive models’ landscape. Secondly, it presents a unique discussion of the challenges and opportunities arising from these factors. Lastly, it proposes an innovative solution, specifically collaboration between academic and industry partners, to effectively manage the challenges and take advantage of the opportunities for mutual benefits. Full article

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Open AccessArticle

Impact of Liquidity and Investors Sentiment on Herd Behavior in Cryptocurrency Market

Siniša Bogdan

Natali Brmalj

and

Elvis Mujačević

Int. J. Financial Stud. 2023, 11(3), 97; https://doi.org/10.3390/ijfs11030097 - 31 Jul 2023

Abstract

This research addresses the impact of individual investors on the cryptocurrency market, focusing specifically on the development of herd behavior. Although the phenomenon of herd behavior has been studied extensively in the stock market, it has received limited research in the context of cryptocurrencies. This study aims to fill this research gap by examining the impact of liquidity and sentiment on herd behavior using the CSAD model, considering small, medium, and large cryptocurrencies. The results show different outcomes for cryptocurrencies of different sizes, consistently demonstrating that the herding effect is more pronounced under conditions of lower liquidity, as determined by the turnover volume and liquidity ratio of cryptocurrencies. Proxy measures such as the Twitter Hedonometer and CBOE VIX were used to measure investor sentiment and show the prevalence of herding behavior in optimistic times for all cryptocurrencies, regardless of their market capitalization. Consequently, this study provides valuable insights into the manifestation of herd behavior in the cryptocurrency market and highlights the importance of liquidity and sentiment as influencing factors. These findings improve our understanding of investor behavior and provide guidance to market participants and policymakers on how to effectively manage the risks associated with herd effects. Full article

Open AccessArticle

Opening a New Era with Machine Learning in Financial Services? Forecasting Corporate Credit Ratings Based on Annual Financial Statements

Mustafa Pamuk

and

Matthias Schumann

Int. J. Financial Stud. 2023, 11(3), 96; https://doi.org/10.3390/ijfs11030096 - 30 Jul 2023

Abstract

Corporate credit ratings provide multiple strategic, financial, and managerial benefits for decision-makers. Therefore, it is essential to have accurate and up-to-date ratings to continuously monitor companies’ financial situations when making financial credit decisions. Machine learning (ML)-based internal models can be used for the assessment of companies’ financial situations using annual statements. Particularly, it is necessary to check whether these ML models achieve better results compared to statistical methods. Due to the multi-class classification problem when forecasting corporate credit ratings, the development, monitoring, and maintenance of ML-based systems are more challenging compared to simple classifications. This problem becomes even more complex due to the required coordination with financial regulators (e.g., OECD, EBA, BaFin, etc.). Furthermore, the ML models must be updated regularly due to the periodic nature of annual statements as a dataset. To address the problem of the limited dataset, multiple sampling strategies and machine learning algorithms can be combined for accurate and up-to-date forecasting of credit ratings. This paper provides various implications for ML-based forecasting of credit ratings and presents an approach for combining sampling strategies and ML techniques. It also provides design recommendations for ML-based services in the finance industry on how to fulfill the existing regulations. Full article

(This article belongs to the Special Issue Financial Econometrics and Machine Learning)

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