Journal Description
Journal of Risk and Financial Management
Journal of Risk and Financial Management
is an international, peer-reviewed, open access journal on risk and financial management, published monthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, EconBiz, EconLit, RePEc, and other databases.
- Journal Rank: CiteScore - Q1 (Business, Management and Accounting (miscellaneous))
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 20.1 days after submission; acceptance to publication is undertaken in 4.6 days (median values for papers published in this journal in the first half of 2024).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Latest Articles
The Influence of Personality Traits on Stock Investment Retention: Insights from Thai Investors
J. Risk Financial Manag. 2024, 17(11), 486; https://doi.org/10.3390/jrfm17110486 - 28 Oct 2024
Abstract
Understanding the psychological factors that influence investment decisions is crucial for predicting stock investment retention. This study investigates the mediating role of the Big Five personality traits in stock investment retention, utilizing a modified version of the theory of planned behavior. By examining
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Understanding the psychological factors that influence investment decisions is crucial for predicting stock investment retention. This study investigates the mediating role of the Big Five personality traits in stock investment retention, utilizing a modified version of the theory of planned behavior. By examining the influence of investors’ perceived risk and attitudes toward stock investment, data collected via an online survey with The Association of Thai Securities Companies (ASCO) were analyzed using Structural Equation Modeling (SEM). The findings reveal that extraversion, openness, and conscientiousness significantly impact attitudes toward stock investing, which in turn affects investment retention. However, personality traits do not directly influence risk perception. This research provides unique empirical evidence of the independence between the Big Five personality traits and risk perception among Thai stock investors, underscoring the importance of personality in shaping investment behavior through its effect on attitudes.
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(This article belongs to the Special Issue Advanced Studies in Empirical Asset Pricing)
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Open AccessArticle
Optimizing Multivariate Time Series Forecasting with Data Augmentation
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Seyed Sina Aria, Seyed Hossein Iranmanesh and Hossein Hassani
J. Risk Financial Manag. 2024, 17(11), 485; https://doi.org/10.3390/jrfm17110485 - 28 Oct 2024
Abstract
The convergence of data mining and deep learning has become an invaluable tool for gaining insights into evolving events and trends. However, a persistent challenge in utilizing these techniques for forecasting lies in the limited access to comprehensive, error-free data. This challenge is
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The convergence of data mining and deep learning has become an invaluable tool for gaining insights into evolving events and trends. However, a persistent challenge in utilizing these techniques for forecasting lies in the limited access to comprehensive, error-free data. This challenge is particularly pronounced in financial time series datasets, which are known for their volatility. To address this issue, a novel approach to data augmentation has been introduced, specifically tailored for financial time series forecasting. This approach leverages the power of Generative Adversarial Networks to generate synthetic data that replicate the distribution of authentic data. By integrating synthetic data with real data, the proposed approach significantly improves forecasting accuracy. Tests with real datasets have proven that this method offers a marked improvement over models that rely only on real data.
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(This article belongs to the Section Financial Markets)
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Open AccessArticle
Microcrediting and Investment Analysis in the Context of Environmental, Social, and Corporate Governance
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Ainagul Adambekova, Nurbek Adambekov, Timothy O. Randhir, Zhuldyz Adambekova and Manat Yezhebekov
J. Risk Financial Manag. 2024, 17(11), 484; https://doi.org/10.3390/jrfm17110484 - 28 Oct 2024
Abstract
This article is devoted to the analysis and development of ranking criteria for microcredit organizations to increase their investment attractiveness. The need to solve problematic issues is associated with the need to minimize risks before the start of the lending process through the
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This article is devoted to the analysis and development of ranking criteria for microcredit organizations to increase their investment attractiveness. The need to solve problematic issues is associated with the need to minimize risks before the start of the lending process through the correct selection of participants in the credit transaction. This study used the methods of content analysis and interpretation, correlation analysis and regression modeling, ranking, and clustering to assess the factors affecting the effectiveness of microcredit organizations. The most attention is paid to identifying key indicators that help improve the quality of financial services provided and their availability for various categories of borrowers. The results show that factors related to lending volumes and borrower characteristics have a significant impact on the quality of microcredit organizations. Of interest is the interpretation of classical financial indicators of microcredit organizations in the context of the principles of environmental, social, and corporate governance (ESG). The proposed approaches and conclusions can be used to improve the practice of microfinance and develop management and regulation strategies in this area.
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(This article belongs to the Special Issue Sustainable Business Model for Micro Finance Institutions)
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Insider Trading and CEO Pay-Gap Induced Turnover
by
Viet Le, Ann-Ngoc Nguyen, Andros Gregoriou and William Forbes
J. Risk Financial Manag. 2024, 17(11), 483; https://doi.org/10.3390/jrfm17110483 - 27 Oct 2024
Abstract
We explore how insider trading returns, disparities in executive pay, and CEO turnover are interrelated. Our findings reveal both independent and interactive effects for insider trading returns, the CEO pay gap, and the likelihood of CEO turnover. First, an increase in abnormal returns
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We explore how insider trading returns, disparities in executive pay, and CEO turnover are interrelated. Our findings reveal both independent and interactive effects for insider trading returns, the CEO pay gap, and the likelihood of CEO turnover. First, an increase in abnormal returns from insider purchases lowers the probability of a CEO’s turnover, while an increase in abnormal returns from insider sales increases the likelihood of a CEO’s dismissal. Second, the CEO pay gap negatively affects the probability of CEO turnover for insider purchases, but it does not have a similar effect on insider sales. Third, the interaction between insider abnormal returns and any CEO pay disparity influences the impact of these returns on CEO turnover. Specifically, this interaction diminishes the positive effect of insider selling on the probability of a CEO’s dismissal, offsets the negative effect of insider purchasing on CEO dismissal, and, finally, amplifies the negative impact of CEO pay disparity on the probability of a CEO’s dismissal during periods witnessing insider purchases.
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(This article belongs to the Special Issue Featured Papers in Corporate Finance and Governance)
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Open AccessReview
CFO (Chief Financial Officer) Research: A Systematic Review Using the Bibliometric Toolbox
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Umra Rashid, Mohd Abdullah, Mosab I. Tabash, Ishrat Naaz, Javaid Akhter and Mujeeb Saif Mohsen Al-Absy
J. Risk Financial Manag. 2024, 17(11), 482; https://doi.org/10.3390/jrfm17110482 - 25 Oct 2024
Abstract
The chief financial officer (CFO) is a crucial executive position in an organisation, responsible for overseeing the financial operations and strategy of the company. Despite rising interest among academics and practitioners, the literature corpus on CFO research remains largely fragmented, which warrants the
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The chief financial officer (CFO) is a crucial executive position in an organisation, responsible for overseeing the financial operations and strategy of the company. Despite rising interest among academics and practitioners, the literature corpus on CFO research remains largely fragmented, which warrants the unpacking of the underlying intellectual knowledge structure of the domain. In response, this study aims to provide a concise overview of the trends and science relating to CFO research, comprehend potential gaps in the literature, and highlight crucial future research pathways. A quantitative bibliometric overview of 669 research articles from 1982 to 2022 provides a spectrum of intellectual clout that helps decipher performance trends and delineates six significant clusters of knowledge in CFO research. We selectively discuss the empirical findings and theoretical and conceptual advancements within each cluster. This study offers recommendations for future research, emphasising the growing role of CFOs in leadership and addressing the fragmentation in current research. The findings and contributions of this study could further elevate CFOs’ importance in the C-suite.
Full article
(This article belongs to the Special Issue Featured Papers in Corporate Finance and Governance)
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Open AccessArticle
Informativeness of Performance Measures: Coefficients or R-Squareds?
by
Ken Li
J. Risk Financial Manag. 2024, 17(11), 481; https://doi.org/10.3390/jrfm17110481 - 24 Oct 2024
Abstract
Measuring the informativeness of earnings is of fundamental importance to accounting research. Both coefficients and R-squareds have been proposed as candidates for measuring the informativeness of earnings. However, recent research has focused substantially more on using coefficients, rather than R-squareds, to draw inferences.
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Measuring the informativeness of earnings is of fundamental importance to accounting research. Both coefficients and R-squareds have been proposed as candidates for measuring the informativeness of earnings. However, recent research has focused substantially more on using coefficients, rather than R-squareds, to draw inferences. This paper first documents in a small theoretical model that under some circumstances, R-squareds map more closely to informativeness than coefficients. Second, this paper documents that in archival data, coefficients and R-squareds can draw opposite inferences regarding the informativeness of earnings and other performance measures up to 50% of the time. Third, this paper proposes an approach to provide statistical inference using R-squareds. Taken together, this paper suggests that rather than solely relying on coefficients, as is common in prior literature, R-squareds can also be used to measure the informativeness of earnings and other performance measures.
Full article
(This article belongs to the Special Issue Advances in Accounting & Auditing Research)
Open AccessArticle
Environmental, Social and Governance Awareness and Organisational Risk Perception Amongst Accountants
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Hok-Ko Pong and Chun-Cheong Fong
J. Risk Financial Manag. 2024, 17(11), 480; https://doi.org/10.3390/jrfm17110480 - 24 Oct 2024
Abstract
The relationships between accountants’ environmental, social and governance (ESG) awareness and their perceptions of organisational risk are examined in this study. The emphasis is on the operational, strategic, financial and compliance risks of business organisations. A total of 462 accountants in Hong Kong
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The relationships between accountants’ environmental, social and governance (ESG) awareness and their perceptions of organisational risk are examined in this study. The emphasis is on the operational, strategic, financial and compliance risks of business organisations. A total of 462 accountants in Hong Kong were included via stratified random sampling and snowball sampling to ensure population diversity. A stratified random approach was used to include factors such as age, gender, income and experience, and snowball sampling amongst professional networks was used to ensure representativeness. A significant positive relationship exists between ESG awareness and risk perception, with environmental and governance factors emerging as the strongest predictors. Accountants with deep ESG awareness, especially in the aforementioned areas, can successfully identify and manage nontraditional risks such as regulatory changes and environmental threats. The findings highlight the need for institutionalising ESG-focused education in accounting and corporate governance to improve risk management capabilities. Increased ESG awareness can ensure responsible and sustainable business behaviour. Future research can expand the sample of accountants to executives and use longitudinal designs to capture the dynamic nature of ESG awareness and risk perception.
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(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)
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Open AccessArticle
Market Volatility vs. Economic Growth: The Role of Cognitive Bias
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Neha Parashar, Rahul Sharma, S. Sandhya and Apoorva Joshi
J. Risk Financial Manag. 2024, 17(11), 479; https://doi.org/10.3390/jrfm17110479 - 24 Oct 2024
Abstract
This study aims to investigate the interaction between market volatility, economic growth, and cognitive biases over the period from April 2006 to March 2024. Market volatility and economic growth are critical indicators that influence economic stability and investment behavior. Financial market volatility, defined
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This study aims to investigate the interaction between market volatility, economic growth, and cognitive biases over the period from April 2006 to March 2024. Market volatility and economic growth are critical indicators that influence economic stability and investment behavior. Financial market volatility, defined by abrupt and erratic changes in asset values, can have a big impact on the expansion and stability of the economy. According to conventional economic theory, there should be an inverse relationship between market volatility and economic growth since high volatility can discourage investment and erode trust. Market participants’ cognitive biases are a major aspect that complicates this connection. Due to our innate susceptibility to cognitive biases, including herd mentality, overconfidence, and loss aversion, humans can make poor decisions and increase market volatility. These prejudices frequently cause investors to behave erratically and irrationally, departing from reasonable expectations and causing inefficiencies in the market. Cognitive biases have the capacity to sustain feedback loops, which heighten market turbulence and may hinder economic expansion. Similarly, cognitive biases have the potential to cause investors to misread economic indicators or ignore important details, which would increase volatility. This study uses the generalized autoregressive conditional heteroskedasticity (GARCH) model on GDP growth data from the US, the UK, and India, alongside S&P 500, FTSE 100, and NIFTY 50 data sourced from Bloomberg, to examine evidence of these biases. The results show evidence of the predictive nature of market fluctuations on economic performance across the markets and highlight the substantial effects of cognitive biases on market volatility, disregarding economic fundamentals and growth, emphasizing the necessity of considering psychological factors in financial market analyses and developing strategies to mitigate their adverse effects.
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(This article belongs to the Special Issue Globalization and Economic Integration)
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Intellectual Capital: Revisiting an Analytical Model
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António Eduardo Martins and Albino Lopes
J. Risk Financial Manag. 2024, 17(11), 478; https://doi.org/10.3390/jrfm17110478 - 23 Oct 2024
Abstract
The world’s economy is experiencing important changes brought on by diverse factors, namely technological advancements, the appearance and diffusion of personal computers, high-speed telecommunications, and the Internet. These technological changes have influenced the corporate environment, with recent decades denominated as the information economy,
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The world’s economy is experiencing important changes brought on by diverse factors, namely technological advancements, the appearance and diffusion of personal computers, high-speed telecommunications, and the Internet. These technological changes have influenced the corporate environment, with recent decades denominated as the information economy, the digital economy, the economy of knowledge, a risk society, and the age of quality and innovation. To designate the key concept of the new economic era as “intellectual capital” implies a classification and evaluation effort in order to proceed with its generalization. In today’s world, the study of a model capable of adding explanatory diversity to intellectual capital is very relevant. We observed a true panoply of concepts in the analyzed models based on a literature review. The conceptual evolution during recent decades has motivated many investigations in this field, resulting from the phenomenon of globalization, growing technological innovation, and the observation of significant disparities between the market value and the accounting value of companies. This article describes an investigation carried out, presenting an explicative model of intellectual capital based on four distinct patterns, which are the aggregating factors of the existing conceptual diversity. We present the identification of a model with two axes, x (the type of knowledge, from tacit to explicit) and y (the capital of knowledge, from human to structural), which represents the conceptual diversity mirrored in four quadrants resulting from the research carried out with an initial exploratory study and two following studies with 45 and 72 specialists. In this article we analyze the Martins model, which proves to be essential for systematizing and mapping the dimensions that intellectual capital includes. This model can be used to identify the different aspects of intellectual capital in an organization and thus contribute to its understanding, optimization and good management.
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(This article belongs to the Section Business and Entrepreneurship)
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Open AccessArticle
Exploring the Role of AI in Improving VAT Reporting Quality: Experimental Study in Emerging Markets
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Moustafa Al Najjar, Rasha Mahboub, Bilal Nakhal and Mohamed Gaber Ghanem
J. Risk Financial Manag. 2024, 17(11), 477; https://doi.org/10.3390/jrfm17110477 - 22 Oct 2024
Abstract
In recent years, artificial intelligence has increasingly been interesting for its role in improving accounting practices. This research investigates whether there is a significant difference in value-added tax (VAT) reporting quality between traditional methods and those assisted by artificial intelligence (AI) in emerging
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In recent years, artificial intelligence has increasingly been interesting for its role in improving accounting practices. This research investigates whether there is a significant difference in value-added tax (VAT) reporting quality between traditional methods and those assisted by artificial intelligence (AI) in emerging markets. The experiment introduces an AI intervention using ChatGPT-4 to analyze data for accounting errors. The results demonstrate that AI-assisted reporting significantly improves reporting quality, as the AI effectively identified accounting errors that were missed in traditional reporting. This study makes a valuable contribution by providing novel, practical insights into the role and capabilities of AI in tax reporting, employing a rarely used experimental methodology to explore this topic.
Full article
(This article belongs to the Special Issue Sustainable Tax and Accounting Reporting in Building a New Tax Culture)
Open AccessArticle
CFO Compensation and Audit Fees
by
Jing Jiang, Charles T. Fagan and Linda Hughen
J. Risk Financial Manag. 2024, 17(11), 476; https://doi.org/10.3390/jrfm17110476 - 22 Oct 2024
Abstract
Executive compensation contracts may influence financial reporting quality, and the CFO plays a key role in preparing the financial statements. This study examines whether the structure and components of CFO compensation are associated with audit risk as measured by audit fees for a
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Executive compensation contracts may influence financial reporting quality, and the CFO plays a key role in preparing the financial statements. This study examines whether the structure and components of CFO compensation are associated with audit risk as measured by audit fees for a sample of S&P 1500 companies during the period 2012–2022. We find that the percentage of total compensation composed of either stock or options is significant and positively related to audit fees, while non-equity incentive plan compensation is significant and negatively related to audit fees. We also find that the dollar amount of equity compensation is significant and positively related to audit fees, while the dollar amount of non-equity compensation is not related to audit fees. These results suggest that CFO compensation structure is an important factor in the assessment of audit risk, which is important for compensation committees as well as regulators. This is the first study, to our knowledge, that examines the relationship between the dollar amount and composition of CFO compensation and audit fees.
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(This article belongs to the Special Issue Financial Reporting and Auditing)
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Open AccessArticle
Forecasting Orange Juice Futures: LSTM, ConvLSTM, and Traditional Models Across Trading Horizons
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Apostolos Ampountolas
J. Risk Financial Manag. 2024, 17(11), 475; https://doi.org/10.3390/jrfm17110475 - 22 Oct 2024
Abstract
This study evaluated the forecasting accuracy of various models over 5-day and 10-day trading horizons to predict the prices of orange juice futures (OJ = F). The analysis included traditional models like Autoregressive Integrated Moving Average (ARIMA) and advanced neural network models such
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This study evaluated the forecasting accuracy of various models over 5-day and 10-day trading horizons to predict the prices of orange juice futures (OJ = F). The analysis included traditional models like Autoregressive Integrated Moving Average (ARIMA) and advanced neural network models such as Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), Backpropagation Neural Network (BPNN), Support Vector Regression (SVR), and Convolutional Long Short-Term Memory (ConvLSTM), incorporating factors like the Commodities Index and the S&P500 Index. We employed loss function metrics and various tests to assess model performance. The results indicated that for the 5-day horizon, the LSTM and ConvLSTM consistently outperformed the other models. LSTM achieved the lowest error rates and demonstrated superior capability in capturing temporal dependencies, especially in single-factor and S&P500 Index predictions. ConvLSTM also performed strongly, effectively modeling spatial and temporal data patterns. In the 10-day horizon, similar trends were observed. LSTM and ConvLSTM models had significantly lower errors and better alignment with actual values. The BPNN model performed well when all factors were included, and the SVR model maintained consistent accuracy, particularly for single-factor predictions. The Diebold–Mariano (DM) test indicated significant differences in forecasting accuracy, favoring advanced neural network models. In addition, incorporating multiple influencing factors further improved predictive performance, enhancing investment outcomes and reducing risk.
Full article
(This article belongs to the Special Issue Machine Learning Applications in Finance, 2nd Edition)
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Dynamic Spillovers from US (Un)Conventional Monetary Policy to African Equity Markets: A Time-Varying Parameter Frequency Connectedness and Wavelet Coherence Analysis
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Andrew Phiri and Izunna Anyikwa
J. Risk Financial Manag. 2024, 17(11), 474; https://doi.org/10.3390/jrfm17110474 - 22 Oct 2024
Abstract
Since the implementation of unconventional monetary policies (UMPs) by the US in response to the global financial crisis (GFC) and the COVID-19 pandemic, there have been increasing concerns that these forward guidance and quantitative easing programmes have had spillover effects on global equity
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Since the implementation of unconventional monetary policies (UMPs) by the US in response to the global financial crisis (GFC) and the COVID-19 pandemic, there have been increasing concerns that these forward guidance and quantitative easing programmes have had spillover effects on global equity markets. We specifically question whether the implementation of these UMPs have had spillovers to African equities, which have been previously speculated to be decoupled from global markets and shocks. Time-varying-parameter (TVP) frequency connectedness and wavelet coherency methods were used to examine the dynamic time-frequency spillovers between daily time series of the US shadow short rate and African equities returns/volatility between 1 January 2007 and 31 March 2023. On one hand, the TVP frequency connectedness analysis reveals robust long-run spillovers from US monetary policy to African equity markets during specific periods: 2009, 2013, 2020, and 2021. These coincide with instances when the Federal Reserve announced their transition from conventional to unconventional monetary practices and vice versa. On the other hand, the wavelet analysis provides insights into the ‘sign’ of the spillovers, indicating mixed phase dynamics during UMPs responding to the GFC. In contrast, anti-phase or negative co-movements characterize UMPs implemented during the COVID-19 pandemic, implying that these policies increased both returns and volatilities to African equities. Altogether, we conclude that US UMP has increasing deteriorated market efficiency and amplified portfolio risk in African equities whilst during ‘normalization’ periods US monetary policy has little transmission effect.
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(This article belongs to the Section Financial Markets)
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Open AccessArticle
The Strategic Impact of Service Quality and Environmental Sustainability on Financial Performance: A Case Study of 5-Star Hotels in Athens
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Michalis Skordoulis, Angelos-Stavros Stavropoulos, Aristidis Papagrigoriou and Petros Kalantonis
J. Risk Financial Manag. 2024, 17(10), 473; https://doi.org/10.3390/jrfm17100473 - 19 Oct 2024
Abstract
This study explores the impact of guest satisfaction on the financial performance of 5-star hotels, with a focus on both service quality and environmental sustainability. The purpose of the research is to understand how improvements in key satisfaction dimensions influence hotel profitability, as
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This study explores the impact of guest satisfaction on the financial performance of 5-star hotels, with a focus on both service quality and environmental sustainability. The purpose of the research is to understand how improvements in key satisfaction dimensions influence hotel profitability, as measured by EBITDA, ROA, and ROE. Satisfaction was measured across SERVQAUL dimensions and the dimension of environmental sustainability. The data were analyzed using the Multicriteria Satisfaction Analysis (MUSA) method and linear regression models to determine the effect of satisfaction on financial performance. Results indicate that responsiveness is the most important factor for guests, while environmental sustainability ranks high in importance but shows lower satisfaction scores. The findings suggest that investing in both service quality and sustainability can significantly enhance a hotel’s financial returns. The study concludes that hotel managers should prioritize improvements in environmental sustainability and responsiveness to optimize guest satisfaction and financial performance.
Full article
(This article belongs to the Special Issue Advances in Financial and Hospitality Management Accounting)
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Open AccessReview
The Role of Technology in Promoting Green Finance: A Systematic Literature Survey and the Development of a Framework
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Mitra Saeedi and Badar Nadeem Ashraf
J. Risk Financial Manag. 2024, 17(10), 472; https://doi.org/10.3390/jrfm17100472 - 18 Oct 2024
Abstract
Green finance, defined as channeling money into sustainable development activities, is still far lower than needed to achieve net-zero emissions objectives. In this paper, we discuss the role of technologies in developing green finance. We identify that green finance faces three major challenges,
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Green finance, defined as channeling money into sustainable development activities, is still far lower than needed to achieve net-zero emissions objectives. In this paper, we discuss the role of technologies in developing green finance. We identify that green finance faces three major challenges, including the risk management of green projects, the scarcity of innovative green financing products, and compliance with the regulations. Then, in the context of the existing literature, we explore recent technologies, including blockchain, artificial intelligence (AI), machine learning (ML), data analytics, Internet of Things (IoT), and robotics that are helping to deal with the challenges in green finance. We show that data-driven approaches utilizing AI and ML help in the risk assessment of green projects; FinTech-based crowdfunding platforms provide innovative green financial products and regulatory technologies (RegTech) support in compliance with regulations. We also identify that the environmental footprint of cryptocurrencies is an emerging area in the technologies and green finance domain. Our framework could be helpful to further extend the debate on the role of technology in green finance.
Full article
(This article belongs to the Special Issue FinTech, Blockchain and Cryptocurrencies)
Open AccessArticle
Time–Frequency Co-Movement of South African Asset Markets: Evidence from an MGARCH-ADCC Wavelet Analysis
by
Fabian Moodley, Sune Ferreira-Schenk and Kago Matlhaku
J. Risk Financial Manag. 2024, 17(10), 471; https://doi.org/10.3390/jrfm17100471 - 18 Oct 2024
Abstract
The growing prominence of generating a well-diversified portfolio by holding securities from multi-asset markets has, over the years, drawn criticism. Various financial market events have caused asset markets to co-move, especially in emerging markets, which reduces portfolio diversification and enhances return losses. Consequently,
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The growing prominence of generating a well-diversified portfolio by holding securities from multi-asset markets has, over the years, drawn criticism. Various financial market events have caused asset markets to co-move, especially in emerging markets, which reduces portfolio diversification and enhances return losses. Consequently, this study examines the time–frequency co-movement of multi-asset classes in South Africa by using the Multivariate Generalized Autoregressive Conditional Heteroscedastic–Asymmetrical Dynamic Conditional Correlation (MGARCH-DCC) model, Maximal Overlap Discrete Wavelet Transformation (MODWT), and the Continuous Wavelet Transform (WTC) for the period 2007 to 2024. The findings demonstrate that the equity–bond, equity–property, equity–gold, bond–property, bond–gold, and property–gold markets depict asymmetrical time-varying correlations. Moreover, correlation in these asset pairs varies at investment periods (short-term, medium-term, and long-term), with historical events such as the 2007/2008 Global Financial Crisis (GFC) and the COVID-19 pandemic causing these asset pairs to co-move at different investment periods, which reduces diversification properties. The findings suggest that South African multi-asset markets co-move, affecting the diversification properties of holding multi-asset classes in a portfolio at different investment periods. Consequently, investors should consider the holding periods of each asset market pair in a portfolio as they dictate the level of portfolio diversification. Investors should also remember that there are lead–lag relationships and risk transmission between asset market pairs, enhancing portfolio volatility. This study assists investors in making more informed investment decisions and identifying optimal entry or exit points within South African multi-asset markets.
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(This article belongs to the Special Issue Portfolio Selection and Risk Analytics)
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Open AccessArticle
Enhancing Financial Advisory Services with GenAI: Consumer Perceptions and Attitudes Through Service-Dominant Logic and Artificial Intelligence Device Use Acceptance Perspectives
by
Qin Yang and Young-Chan Lee
J. Risk Financial Manag. 2024, 17(10), 470; https://doi.org/10.3390/jrfm17100470 - 17 Oct 2024
Abstract
Financial institutions are currently undergoing a significant shift from traditional robo-advisors to more advanced generative artificial intelligence (GenAI) technologies. This transformation has motivated us to investigate the factors influencing consumer responses to GenAI-driven financial advice. Despite extensive research on the adoption of robo-advisors,
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Financial institutions are currently undergoing a significant shift from traditional robo-advisors to more advanced generative artificial intelligence (GenAI) technologies. This transformation has motivated us to investigate the factors influencing consumer responses to GenAI-driven financial advice. Despite extensive research on the adoption of robo-advisors, there is a gap in our understanding of the specific contributors to, and differences in, consumer attitudes and reactions to GenAI-based financial guidance. This study aims to address this gap by analyzing the impact of personalized investment suggestions, human-like empathy, and the continuous improvement of GenAI-provided financial advice on its authenticity as perceived by consumers, their utilitarian attitude toward the use of GenAI for financial advice, and their reactions to GenAI-generated financial suggestions. A comprehensive research model was developed based on service-dominant logic (SDL) and Artificial Intelligence Device Use Acceptance (AIDUA) frameworks. The model was subsequently employed in a structural equation modeling (SEM) analysis of survey data from 822 mobile banking users. The findings indicate that personalized investment suggestions, human-like empathy, and the continuous improvement of GenAI’s recommendations positively influence consumers’ perception of its authenticity. Moreover, we discovered a positive correlation between utilitarian attitudes and perceived authenticity, which ultimately influences consumers’ responses to GenAI’s financial advisory solutions. This is manifested as either a willingness to engage or resistance to communication. This study contributes to the research on GenAI-powered financial services and underscores the significance of integrating GenAI financial guidance into the routine operations of financial institutions. Our work builds upon previous research on robo-advisors, offering practical insights for financial institutions seeking to leverage GenAI-driven technologies to enhance their services and customer experiences.
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(This article belongs to the Section Financial Technology and Innovation)
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Open AccessArticle
Economic Freedom, Budget Deficits, and Perceived Risk from Larger National Debt-to-GDP Ratios: An Exploratory Analysis of Their Real Interest Rate Effects
by
Richard J. Cebula
J. Risk Financial Manag. 2024, 17(10), 469; https://doi.org/10.3390/jrfm17100469 - 17 Oct 2024
Abstract
Since the early 1980s, there have been a number of principally empirical studies of the impact of government budget deficits on interest rates that have typically tested the hypothesis that larger deficits raise interest rates. However, in more recent years, this topic has
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Since the early 1980s, there have been a number of principally empirical studies of the impact of government budget deficits on interest rates that have typically tested the hypothesis that larger deficits raise interest rates. However, in more recent years, this topic has received far less attention. Accordingly, this study seeks to “update” the findings of such studies and to do so for the dominant North American economies of Canada and the U.S. Furthermore, in the pursuit of further insights into interest rates, the present study also investigates an effectively heretofore overlooked variable that arguably also might influence interest rates, namely, economic freedom. Finally, given the increased upward trend of government debt (relative to GDP) in recent years in Canada and the U.S., this study investigates the interest rate impact of rising national debt-to-GDP ratios. For the 1995–2024 period (and also in one estimate for the 1985–2001 period), this exploratory study finds compelling evidence (1) that the real interest rate yield on 10-year Treasuries in Canada and the real interest rate yield on 10-year U.S. Treasury notes are increasing functions of the central government budget deficits in both Canada and the U.S., respectively, and (2) the real interest rate yields on 10-year Treasuries in Canada and 10-year U.S. Treasury notes are both decreasing functions of economic freedom in Canada and the U.S., respectively. On the other hand, regarding the impact of a higher national debt-to-GDP ratio on the real ten-year Treasury yield, there is only very mixed support for an impact, with support for its impact coming from the Canadian estimates but no support whatsoever coming from the U.S. estimates.
Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Journal of Risk and Financial Management)
Open AccessArticle
Digital Financial Literacy and Its Impact on Financial Decision-Making of Women: Evidence from India
by
Deepak Mishra, Naveen Agarwal, Sanawi Sharahiley and Vinay Kandpal
J. Risk Financial Manag. 2024, 17(10), 468; https://doi.org/10.3390/jrfm17100468 - 17 Oct 2024
Abstract
Despite the increasing accessibility of digital financial instruments globally, a number of women encounter obstacles in properly using these platforms due to insufficient digital financial literacy, which profoundly affects their financial decision-making and economic empowerment. This study aims to promote digital financial literacy
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Despite the increasing accessibility of digital financial instruments globally, a number of women encounter obstacles in properly using these platforms due to insufficient digital financial literacy, which profoundly affects their financial decision-making and economic empowerment. This study aims to promote digital financial literacy and Fintech adoption for women in India by examining the effects of digital financial literacy on financial decision-making while considering the mediating effect of government support and digital financial literacy. Furthermore, in this study, we analyzed the relationship between independent variables such as financial attitude (FAtt), subjective norms (SNs), perceived behavior control (PBC), digital financial literacy (DFL), and financial accessibility (FA) on the dependent variable, i.e., financial decision-making (FDM). We also explored how financial decision-making impacts women’ intention towards investment (INT). By analyzing 385 Indian women respondents using Structural Equation Modeling (SEM), this study revealed that financial attitude (FAtt) leads to higher financial decision-making (FDM), exerting moderate effects. Similarly, subjective norms (SNs), perceived behavioral control (PBC), digital financial literacy (DFL), and financial accessibility (FA) significantly lead to financial decision-making. Overall, the five predictors of financial decision-making explained around 71% of the variance. Financial decision-making exerted a significant and robust effect on women’s intention towards investment. Financial resilience significantly moderated the effects of financial decision-making on women’s intention towards investment. These findings emphasize the necessity of implementing a distinct government strategy and programs to enhance the adoption of Fintech among women living in urban and rural regions across India. This study is aligned with UN Sustainable Development Goals, especially Sustainable Development Goal (SDG) 1: No Poverty, SDG 5: Gender Equality, and SDG 8: Decent Work and Economic Growth.
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(This article belongs to the Special Issue Fintech, Business, and Development)
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Open AccessArticle
The Cryptocurrencies in Emerging Markets: Enhancing Financial Inclusion and Economic Empowerment
by
Mohammad El Hajj and Imad Farran
J. Risk Financial Manag. 2024, 17(10), 467; https://doi.org/10.3390/jrfm17100467 - 17 Oct 2024
Abstract
The present study discusses how adopting cryptos affects financial inclusion in developing economies. Primary constructs like financial inclusion (FI), perceived economic empowerment (PEE), trust in financial institutions (TFI), user satisfaction (US), and cryptocurrency adoption (CA) were tested through Structural Equation Modeling (SEM). The
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The present study discusses how adopting cryptos affects financial inclusion in developing economies. Primary constructs like financial inclusion (FI), perceived economic empowerment (PEE), trust in financial institutions (TFI), user satisfaction (US), and cryptocurrency adoption (CA) were tested through Structural Equation Modeling (SEM). The results indicated that CA significantly and positively influenced FI, US, TFI, and PEE. These relationships extend to the interaction effects: US, TFI, and PEE, all positively related to FI. This is a reflection of cryptocurrencies as an opportunity to redress most of the afflictions characteristic of traditional finance systems and to promote financial inclusion and economic empowerment in developing countries. Future research should also investigate whether digital literacy and regulatory environments support cryptocurrency access.
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(This article belongs to the Special Issue The Future of Money: Central Bank Digital Currencies, Cryptocurrencies and Stablecoins)
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