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Volume 16
Issue 6
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J. Risk Financial Manag., Volume 16, Issue 6 (June 2023) – 20 articles

Cover Story (view full-size image): This study examines the effectiveness of using a large dataset and advanced methodologies, including sentiment analysis and machine learning, to forecast foreign exchange rates (FX) and commodity prices. Using a large dataset, we explore whether combining sentiment analysis with machine learning outperforms in terms of FX. We employ techniques such as random forest, extreme gradient boosting, long short-term memory, and autoregressive integrated moving average (ARIMA) to compare their forecasting performance. The study proposes novel methodologies that integrate seasonal decomposition and wavelet transformation with ARIMA and machine learning techniques and applies them to gold futures prices and euro FX against the US dollar to demonstrate the superiority of the proposed approaches. View this paper
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13 pages, 1082 KiB  
Article
The Impacts of Shopping Tourism on Retail Sales and Rents: Lessons from the COVID-19 Quasi-Experiment of Hong Kong
by Chung Yim Yiu
J. Risk Financial Manag. 2023, 16(6), 301; https://doi.org/10.3390/jrfm16060301 - 16 Jun 2023
Cited by 1 | Viewed by 2279
Abstract
This research studies the impact of shopping tourism on retail sales and rents, using the COVID-19 pandemic as a quasi-experiment. Shopping tourism refers to individuals who travel primarily for shopping purposes, and their spending patterns can have significant effects on the retail sector. [...] Read more.
This research studies the impact of shopping tourism on retail sales and rents, using the COVID-19 pandemic as a quasi-experiment. Shopping tourism refers to individuals who travel primarily for shopping purposes, and their spending patterns can have significant effects on the retail sector. The COVID-19 pandemic disrupted global travel and resulted in a decline in shopping tourist arrivals, leading to a downturn in sales for retailers dependent on shopping tourism. Additionally, the decline in shopping tourism affected retail rents, as the reduced demand for retail spaces posed challenges for property owners in attracting tenants. The study focuses on Hong Kong, a prominent shopping destination, which experienced a significant decline in tourist arrivals and retail sales during the pandemic. The research analyses the relationship between tourist arrivals, retail sales, and rents using time series analysis and identifies the impact of shopping tourism on retail rents. The findings suggest a positive association between tourist arrivals and retail sales and rents, particularly during the period of shopping tourism growth. However, the pandemic severely reduced this effect, revealing the impact of shopping tourists on the retail sector. The study concludes by discussing the implications for retail resilience and highlighting the need for further research on the impacts of shopping tourism on retail sales and rents. Full article
(This article belongs to the Special Issue Impacts of COVID-19 on Tourism)
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29 pages, 409 KiB  
Article
Multitouch Options
by Tristan Guillaume
J. Risk Financial Manag. 2023, 16(6), 300; https://doi.org/10.3390/jrfm16060300 - 14 Jun 2023
Viewed by 748
Abstract
In this article, the multitouch option, also called the n-touch option (or the “baseball” option when n=3) is analyzed and valued in closed form. This is a kind of barrier option that has been traded for a long [...] Read more.
In this article, the multitouch option, also called the n-touch option (or the “baseball” option when n=3) is analyzed and valued in closed form. This is a kind of barrier option that has been traded for a long time on the markets, but that does not yet admit a known valuation formula. The multitouch option sets a gradual knock-out/knock-in mechanism based on the number of times the underlying asset has crossed a predefined barrier in various time intervals before expiry. The higher the number of predefined time intervals during which the barrier has been touched, the lower the value of a knock-out contract at expiry, and conversely for a knock-in one. Multitouch options can be viewed as an extension of step barrier options, preserving the ability of the latter to adjust the exposure to risk over time, while eliminating the notorious danger of “sudden death” that holders of step barrier options are faced with. They are thus less risky and more flexible than step barrier options, and all the more so when compared to standard barrier options. This article also provides closed-form valuation of multitouch options with nonstandard features such as an outside barrier or a barrier defined as a continuous function of time. Full article
(This article belongs to the Special Issue Stochastic Modeling and Statistical Analysis of Financial Data)
16 pages, 374 KiB  
Article
Financial Inclusion and Economic Growth in Sub-Saharan Africa—A Panel ARDL and Granger Non-Causality Approach
by Meshesha Demie Jima and Patricia Lindelwa Makoni
J. Risk Financial Manag. 2023, 16(6), 299; https://doi.org/10.3390/jrfm16060299 - 12 Jun 2023
Cited by 2 | Viewed by 6942
Abstract
Many earlier development finance studies have attempted to assess the relationship between financial inclusion and economic growth. However, the findings of these studies vary from economy to economy and region to region due to various social and economic factors. We, therefore, deemed it [...] Read more.
Many earlier development finance studies have attempted to assess the relationship between financial inclusion and economic growth. However, the findings of these studies vary from economy to economy and region to region due to various social and economic factors. We, therefore, deemed it pertinent to examine the relationship between financial inclusion and economic growth while further identifying the direction of causality between the two variables in twenty-six (26) Sub-Saharan African (SSA) economies using annual secondary data over the 2000–2019 period. In our paper, we used the principal component analysis (PCA) technique to develop a single composite index to proxy financial inclusion while adopting panel unit root, system generalised method of moment (GMM), and ARDL cointegration tests to assess the stationarity properties, assess the factors that affect economic growth, and examine the long-run relationships between financial inclusion and economic growth, respectively. In addition, a Granger non-causality test is used to verify the direction and magnitude of causality. Our study revealed that financial inclusion and economic growth share a strong long-run relationship and that there is bi-directional causality, indicating synergy between these two variables. In order to ensure sustainable economic growth, we thus recommend that developing countries develop macroeconomic policies that will promote financial inclusion while enhancing the functioning and regulation of the domestic financial markets to ensure that all citizens are catered for in the available instruments, products, and service offerings. Within the same policy framework, efforts must be made to further support productive sectors of the economy to ensure economic growth. Full article
(This article belongs to the Section Economics and Finance)
25 pages, 4561 KiB  
Article
Do Large Datasets or Hybrid Integrated Models Outperform Simple Ones in Predicting Commodity Prices and Foreign Exchange Rates?
by Jin Shang and Shigeyuki Hamori
J. Risk Financial Manag. 2023, 16(6), 298; https://doi.org/10.3390/jrfm16060298 - 09 Jun 2023
Viewed by 1690
Abstract
With the continuous advancement of machine learning and the increasing availability of internet-based information, there is a belief that these approaches and datasets enhance the accuracy of price prediction. However, this study aims to investigate the validity of this claim. The study examines [...] Read more.
With the continuous advancement of machine learning and the increasing availability of internet-based information, there is a belief that these approaches and datasets enhance the accuracy of price prediction. However, this study aims to investigate the validity of this claim. The study examines the effectiveness of a large dataset and sophisticated methodologies in forecasting foreign exchange rates (FX) and commodity prices. Specifically, we employ sentiment analysis to construct a robust sentiment index and explore whether combining sentiment analysis with machine learning surpasses the performance of a large dataset when predicting FX and commodity prices. Additionally, we apply machine learning methodologies such as random forest (RF), eXtreme gradient boosting (XGB), and long short-term memory (LSTM), alongside the classical statistical model autoregressive integrated moving average (ARIMA), to forecast these prices and compare the models’ performance. Based on the results, we propose novel methodologies that integrate wavelet transformation with classical ARIMA and machine learning techniques (seasonal-decomposition-ARIMA-LSTM, wavelet-ARIMA-LSTM, wavelet-ARIMA-RF, wavelet-ARIMA-XGB). We apply this analysis procedure to the commodity gold futures prices and the euro foreign exchange rates against the US dollar. Full article
(This article belongs to the Special Issue Commodity Market Finance)
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5 pages, 228 KiB  
Editorial
Corporate Finance, Governance, and Social Responsibility
by Ștefan Cristian Gherghina
J. Risk Financial Manag. 2023, 16(6), 297; https://doi.org/10.3390/jrfm16060297 - 08 Jun 2023
Viewed by 2005
Abstract
Corporate finance is a branch of finance that focuses on how companies handle their cash flow, raise capital, make investments, and implement accounting systems [...] Full article
(This article belongs to the Special Issue Corporate Finance, Governance, and Social Responsibility)
19 pages, 603 KiB  
Article
Developing a Multidimensional Financial Inclusion Index: A Comparison Based on Income Groups
by Inès Gharbi and Aïda Kammoun
J. Risk Financial Manag. 2023, 16(6), 296; https://doi.org/10.3390/jrfm16060296 - 08 Jun 2023
Cited by 1 | Viewed by 2353
Abstract
The aim of our paper is to construct a multidimensional financial inclusion (FI) index to measure the level of FI in 91 countries across different income groups. In order to address our research problem, we use the principal component analysis method. This approach [...] Read more.
The aim of our paper is to construct a multidimensional financial inclusion (FI) index to measure the level of FI in 91 countries across different income groups. In order to address our research problem, we use the principal component analysis method. This approach addresses the criticism of the arbitrary selection of weights and reflects the degree of financial inclusion in depth. The data are drawn from the International Monetary Fund (IMF) Financial Access Survey (FAS), the World Development Indicators (World Bank) and the Global Findex Database during the period of 2004–2020. This paper is the first to consider so many indicators of financial inclusion (13 indicators), belonging to three different dimensions of FI, in order to take into account the maximum number of aspects related to this concept. In addition, unlike previous work, this paper considers both developing and developed countries, which makes it possible to identify differences between them. The proposed index has some advantages. First, it is robust, comparable across countries and has good predictive power in tracking household microeconomic indicators (accounts and savings). It is also well correlated with macroeconomic variables such as literacy rate, poverty, GINI index, real interest rate and employers. Second, our results clearly show that, as a country’s income level grows higher, its level of financial inclusion also grows higher. Full article
(This article belongs to the Section Sustainability and Finance)
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20 pages, 961 KiB  
Article
The Effect of Relative Advantage, Top Management Support and IT Infrastructure on E-Filing Adoption
by Samer Aqel AbuAkel and Marhaiza Ibrahim
J. Risk Financial Manag. 2023, 16(6), 295; https://doi.org/10.3390/jrfm16060295 - 07 Jun 2023
Cited by 1 | Viewed by 1727
Abstract
Electronic filing (e-filing) adoption for tax income purposes is limited in developing countries as the practices of financial accounting and reporting, as well as digitalization in accounting systems, are more prevalent in developed countries. This paper investigates the determinants of e-filing usage in [...] Read more.
Electronic filing (e-filing) adoption for tax income purposes is limited in developing countries as the practices of financial accounting and reporting, as well as digitalization in accounting systems, are more prevalent in developed countries. This paper investigates the determinants of e-filing usage in the context of emerging economies such as Jordan. Building on the Technology–Organization–Environment framework (TOE), the study proposes that the effects of relative advantage, top management support, and IT infrastructure as new variables on e-filing adoption and trust in the e-filing systems are positive. The study also proposes that trust in the e-filing system affects e-filing adoption and mediates the influence of relative advantage, top management support, and IT infrastructure on e-filing adoption. Data were collected from 315 respondents and analyzed via Smart PLS. Relative advantage and top management were found to affect the adoption of and trust in e-filing. In addition, trust in the e-filing system affects e-filing adoption and mediates the impact of relative advantage and top management support for e-filing. Therefore, decision-makers should develop a mechanism to increase trust and the benefits of using e-filing for income tax purposes. Full article
(This article belongs to the Section Sustainability and Finance)
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25 pages, 1601 KiB  
Article
How Do Financial Market Outcomes Affect Gambling?
by Cyrus A. Ramezani and James J. Ahern
J. Risk Financial Manag. 2023, 16(6), 294; https://doi.org/10.3390/jrfm16060294 - 07 Jun 2023
Viewed by 2266
Abstract
A large literature in behavioral finance explores how gambling sentiments influences trading in stocks. This paper considers the reverse phenomena; the impact of financial market outcomes on aggregate gambling expenditures. We expect the wealth effect of higher realized stock returns will increase gambling [...] Read more.
A large literature in behavioral finance explores how gambling sentiments influences trading in stocks. This paper considers the reverse phenomena; the impact of financial market outcomes on aggregate gambling expenditures. We expect the wealth effect of higher realized stock returns will increase gambling (entertainment good). Similarly, we expect rising volatility will attract gamblers to equity markets seeking thrill and skewed payouts. Utilizing novel horse wagering data (1934–2020), we study the impact of these forces on gambling expenditures. Using corporate bond spreads as a proxy for business cycles, we find that, in addition to financial market outcomes, price of wagering, incomes, and availability of competing betting products are important drivers of gambling. We also find that, ceteris paribus, gambling rises during recessions. Our findings will be of interest to policy makers and the finance industry, particularly as day trading, sports betting, online casinos, and other gambling gains broad public acceptance. Full article
(This article belongs to the Special Issue Applied Econometrics and Time Series Analysis)
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17 pages, 343 KiB  
Article
A Data Valuation Model to Estimate the Investment Value of Platform Companies: Based on Discounted Cash Flow
by Hyongmook Cheong, Boyoung Kim and Ivan Ureta Vaquero
J. Risk Financial Manag. 2023, 16(6), 293; https://doi.org/10.3390/jrfm16060293 - 07 Jun 2023
Viewed by 2866
Abstract
As both investment attraction and mergers and acquisitions targeting information technology and platform companies are becoming more important in the digital-centric economic environment, interest in valuing corporate data assets is increasing. Accordingly, among the income approaches used in business valuation, this study presents [...] Read more.
As both investment attraction and mergers and acquisitions targeting information technology and platform companies are becoming more important in the digital-centric economic environment, interest in valuing corporate data assets is increasing. Accordingly, among the income approaches used in business valuation, this study presents a data valuation model based on discounted cash flow. This model is expected to be useful for corporate investment decision-making. The assumptions used in this study for the estimation of data income include intangible asset value, exclude net asset value, and data attribution is centered on technology, human resources, and market factors. In particular, data attribution accounts comprise ordinary data research and development, data labor costs, and data advertising expenses. Data costs were divided into those incurred during collection, storage, curation, analysis, and utilization. Financial statements and related data from a real estate information platform operator over three years were collected and used to simulate the data valuation model. The simulation reveals that the operator possesses KRW 472.6 billion in data assets. Ultimately, the data valuation model developed in this study can contribute to strengthening platform operators’ investment attraction, guaranteeing financial sustainability, and transparency and data assetization. Full article
(This article belongs to the Special Issue Corporate Governance in Global Shocks and Risk Management (Volume II))
22 pages, 807 KiB  
Article
The Effect of Corporate Governance in Islamic Banking on the Agility of Iraqi Banks
by Jabbar Sehen Issa and Mohammad Reza Abbaszadeh
J. Risk Financial Manag. 2023, 16(6), 292; https://doi.org/10.3390/jrfm16060292 - 02 Jun 2023
Viewed by 1355
Abstract
The primary purpose of the research is to investigate the effect of the quality of corporate governance in Islamic banking on the agility of Iraqi banks. For this purpose, the structural-equation-modeling (SEM) method was used to investigate the effect of independent variables on [...] Read more.
The primary purpose of the research is to investigate the effect of the quality of corporate governance in Islamic banking on the agility of Iraqi banks. For this purpose, the structural-equation-modeling (SEM) method was used to investigate the effect of independent variables on the dependent variable. The statistical population of this study is all managers, employees, and customers of the public and private banks of Iraq, and a total of 70 questionnaires were included and analyzed to test the paper’s hypotheses. The research results indicate that corporate governance in Islamic banking has a positive impact on the agility of Iraqi banks, meaning that with an increase in corporate-governance mechanisms in Iraqi Islamic banking, the capability of banks to make timely reactions to potential changes is likely to increase. In this regard, the provision of various services in a flexible and snap manner to a wide range of customers, the acceptance of innovation and IT-related processes, the identification and application of environmental opportunities, and having a culture of learning and cooperating are expected to be realized by improving the quality of corporate-governance mechanisms. Our findings may apply to policymakers to improve market efficiency through designing regulations and bank managers to increase their general performance. The current paper is among the initial attempts to determine the influential factors on bank agility in emerging markets. Full article
(This article belongs to the Special Issue Accounting and Auditing during the World Crisis)
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17 pages, 3741 KiB  
Article
Delineating Housing Submarkets Using Space–Time House Sales Data: Spatially Constrained Data-Driven Approaches
by Meifang Chen, Yongwan Chun and Daniel A. Griffith
J. Risk Financial Manag. 2023, 16(6), 291; https://doi.org/10.3390/jrfm16060291 - 02 Jun 2023
Cited by 1 | Viewed by 1200
Abstract
With the increasing availability of large volumes of space–time house data, delineating space–time housing submarkets is of interest to real estate agents, homebuyers, urban policymakers, and spatial researchers, among others. Appropriately delineated housing submarkets can help nurture submarket monitoring and housing policy developments. [...] Read more.
With the increasing availability of large volumes of space–time house data, delineating space–time housing submarkets is of interest to real estate agents, homebuyers, urban policymakers, and spatial researchers, among others. Appropriately delineated housing submarkets can help nurture submarket monitoring and housing policy developments. Although submarkets are often expected to represent areas with similar houses, neighborhoods, and amenities characteristics, delineating spatially contiguous areas with virtually no fragmented small areas remains challenging. Furthermore, housing submarkets can potentially change over time along with concomitant urban transformations, such as urban sprawl, gentrification, and infrastructure improvements, even in large metropolitan areas, which can complicate delineating submarkets with data for lengthy time periods. This study proposes a new method for integrating a random effects model with spatially constrained data-driven approaches in order to identify stable and reliable space–time housing submarkets, instead of their dynamic changes. This random effects model specification is expected to capture time-invariant spatial patterns, which can help identify stable submarkets over time. It highlights two spatially constrained data-driven approaches, ClustGeo and REDCAP, which perform equally well and produce similar space–time housing submarket structures. This proposed method is utilized for a case study of Franklin County, Ohio, using 19 years of space–time private house transaction data (2001–2019). A comparative analysis using a hedonic model demonstrates that the resulting submarkets generated by the proposed method perform better than popular alternative submarket creators in terms of model performances and house price predictions. Enhanced space–time housing delineation can furnish a way to better understand the sophisticated housing market structures, and to help enhance their modeling and housing policy. This paper contributes to the literature on space–time housing submarket delineations with enhanced approaches to effectively generate spatially constrained housing submarkets using data-driven methods. Full article
(This article belongs to the Special Issue Shocks, Public Policies and Housing Markets)
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14 pages, 915 KiB  
Article
Predicting the REIT Corporate Life Cycle Phase on a Financial Accounting Basis
by Panagiotis Petris
J. Risk Financial Manag. 2023, 16(6), 290; https://doi.org/10.3390/jrfm16060290 - 31 May 2023
Viewed by 907
Abstract
This study investigates the effect of financial–accounting variables on a firm’s distinct life cycle phase. The study concentrates on the real estate sector and uses data of publicly listed REITs which are traded in the European market. To assess the empirical argument, a [...] Read more.
This study investigates the effect of financial–accounting variables on a firm’s distinct life cycle phase. The study concentrates on the real estate sector and uses data of publicly listed REITs which are traded in the European market. To assess the empirical argument, a multinomial panel logit model is employed. The empirical results show that leverage, dividend distribution, the size and the sales variable have significant predictive power over the corporate life cycle classification of an REIT. Higher leverage is associated with an elevated probability of the REIT being classified in the early stage of its corporate life cycle, as opposed to the maturity stage. Positive leverage variation is also a significant predictor of the REIT being categorized in the shake–out stage, while lower dividend distribution, negative sales and size variation are all associated with an increased probability of the REIT being classified in the decline stage, rather than in the maturity phase. Full article
(This article belongs to the Special Issue Global Trends and Challenges in Economics and Finance)
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25 pages, 885 KiB  
Article
National and International Financial Market Regulation and Supervision Systems: Challenges and Solutions
by Viacheslav M. Shavshukov and Natalia A. Zhuravleva
J. Risk Financial Manag. 2023, 16(6), 289; https://doi.org/10.3390/jrfm16060289 - 30 May 2023
Cited by 3 | Viewed by 2285
Abstract
The purpose of this original study is to critically analyse the emergence and development of the national models of financial regulation, international standards and codes, and regional and national financial regulation and supervision (for the cases of the UK, USA, Sweden, the EU, [...] Read more.
The purpose of this original study is to critically analyse the emergence and development of the national models of financial regulation, international standards and codes, and regional and national financial regulation and supervision (for the cases of the UK, USA, Sweden, the EU, and Finland). The research raises both academic and regulatory concerns. The relevance and purpose of this research arise from a need for an academic analysis of the economic nature and classification of financial market regulation systems. They represent a theoretical justification for changes in the policies and supervisory practices of national and international regulatory authorities in response to innovations in financial technologies and instruments, digital products, and risks. Secondly, it will stimulate more systematic work on regulatory databases, registration, and reporting procedures in various economies in different financial markets. The author identifies five main systems of national financial regulatory markets: the multi-tiered, multi-agency US system, the twin peaks model (UK), and the mega-regulatory model (Sweden). There is a thorough review of the international standards and institutions that work for the stability of financial systems. The analysis of the regional and national systems of financial regulation and supervision is based on the examples of the EU and Finnish institutions. National macro- and micro-economic regulation and supervision have been examined, with a focus on the US Federal Reserve and the US Treasury. An important result of the study is the systematisation of the directions of the development of national and international regulatory institutions (since the 1980s). First, the minimum capital and credit risk requirements for banks (the 1980s) were complemented in the 21st century by buffer reserves, liquidity, and leverage standards. Second, regulation focuses on ensuring the sustainability of the national economy. The regulatory focus is on ensuring the sustainability of national and global financial systems. Third, there is an increase in the number of supervised institutions. Fourth, there is a division of the functions between central banks (macro-economic regulation) and one or two mega-regulators (micro-economic regulation and supervision). Fifth, there is a division of labour between the international financial institutions (BIS, IMF, and WB) and national regulators. Sixth, the focus is on protecting consumers and investors and countering money laundering and the financing of terrorism. Seventh, there is an understanding based on a common approach by central banks to new financial technologies and cybersecurity. Full article
(This article belongs to the Special Issue Business, Finance and Economic Development)
34 pages, 2240 KiB  
Article
How Company Characteristics Influence Measurement Practices and Disclosure Level Prescribed within IAS 41
by Mohammad Saleh Altarawneh
J. Risk Financial Manag. 2023, 16(6), 288; https://doi.org/10.3390/jrfm16060288 - 29 May 2023
Viewed by 1419
Abstract
This research paper describes the accounting practices of Jordanian companies engaged in agricultural activities, and identifies the influence of company characteristics on measurement practices related to asset pricing and level of disclosure required by IAS 41. Company characteristics were considered as: size, intensity [...] Read more.
This research paper describes the accounting practices of Jordanian companies engaged in agricultural activities, and identifies the influence of company characteristics on measurement practices related to asset pricing and level of disclosure required by IAS 41. Company characteristics were considered as: size, intensity of biological assets (BA), level of international activities, and audit for the Big Four. Dependent variables were considered measurement practices related to valuing BA as well as resultant harvest and disclosure level, the latter being measured by mandatory and voluntary disclosures. The entire population of companies that include one or more agricultural activities in their purposes and are considered reporting companies formed the research sample, giving a total of 259 companies. The findings revealed that both intensity of BA and level of international activities have a positive impact on measurement practices. Audit for the Big Four was the strongest variable influence, the overall disclosure level prescribed by IAS 41, followed by the level of international activities variable. However, the intensity of the BA variable affects only the overall disclosure level for companies that measure their BA based on the cost method. Firm size was found to have no influence on either measurement practices or disclosure level. The key value of this paper is its examination of the role of company characteristics on measurement practices and level of disclosure required by IAS 41 in the context of Jordanian companies. Through this examination, this study is helpful to standards setters and regulators who obligate and issue the financial regulation and reporting standards at a national or international level, supporting their understanding of measurement and disclosure practices adopted in agricultural companies in the developing country context of Jordan. Full article
(This article belongs to the Special Issue Advances in Accounting, Auditing and Finance)
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32 pages, 458 KiB  
Article
(How) Does Mutual Fund Dual Ownership Affect Shareholder and Creditor Conflict of Interest? Evidence from Corporate Innovation
by Lei Gao, Ying Wang and Jing Zhao
J. Risk Financial Manag. 2023, 16(6), 287; https://doi.org/10.3390/jrfm16060287 - 25 May 2023
Cited by 1 | Viewed by 1363
Abstract
We examine the impact of mutual fund dual ownership (i.e., simultaneous holdings of stocks and bonds of the same company by mutual fund families) on corporate innovation. Our findings indicate that dual ownership is positively associated with innovation quantity, quality, generality, and originality. [...] Read more.
We examine the impact of mutual fund dual ownership (i.e., simultaneous holdings of stocks and bonds of the same company by mutual fund families) on corporate innovation. Our findings indicate that dual ownership is positively associated with innovation quantity, quality, generality, and originality. This effect is mainly driven by non-index funds, which are more likely to be active monitors. Consequently, both stocks and bonds held by dual owners tend to generate higher returns, particularly for more significant, groundbreaking innovations. These results suggest that mutual fund dual ownership mitigates conflicts of interest between shareholders and creditors, thereby enhancing innovation and firm value. However, the relation between dual ownership and innovation turns negative during the recent financial crisis, suggesting that shareholder-creditor conflicts culminate in extreme financial distress, exacerbating dual holders’ risk aversion, and hence, hindering corporate innovation. Full article
(This article belongs to the Special Issue Practical Applications of Investments’ Assessment in Organizations and Economies)
23 pages, 1401 KiB  
Article
Does Previous Experience with the Unified Payments Interface (UPI) Affect the Usage of Central Bank Digital Currency (CBDC)?
by Munish Gupta, Sanjay Taneja, Vikas Sharma, Amandeep Singh, Ramona Rupeika-Apoga and Kshitiz Jangir
J. Risk Financial Manag. 2023, 16(6), 286; https://doi.org/10.3390/jrfm16060286 - 25 May 2023
Cited by 37 | Viewed by 4363
Abstract
In this study, we examined the influence of users’ experiences with the unified payments interface (UPI) system on the usage behavior of central bank digital currency (CBDC) in India. Our research developed a novel conceptual framework that investigated the relationships between technology, cognitive [...] Read more.
In this study, we examined the influence of users’ experiences with the unified payments interface (UPI) system on the usage behavior of central bank digital currency (CBDC) in India. Our research developed a novel conceptual framework that investigated the relationships between technology, cognitive factors, and behavioral intentions towards CBDC use. The framework integrated UPI usage experience as a moderator within existing models of behavioral intentions and use behaviors. We collected data through a survey conducted in major Indian cities during the pilot launch of CBDC. By utilizing a partial least squares structural equation model (PLS-SEM), we analyzed the proposed model and the relationships between the constructs. Our findings revealed the significant impact of hedonic motivation and performance expectancy on users’ behavioral intentions towards CBDC. Social influence also played a significant role in CBDC usage. Furthermore, we identified that prior UPI usage negatively moderated the relationship between performance expectancy and behavioral intention, as well as the relationship between social influence and use behavior. However, prior UPI usage did not significantly moderate the relationships between perceived risk, hedonic motivation, behavioral intention, and use behavior. These findings contribute to our understanding of the factors influencing CBDC adoption and usage behavior in India. Full article
(This article belongs to the Special Issue The Future of Money: Central Bank Digital Currencies, Cryptocurrencies and Stablecoins)
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12 pages, 1971 KiB  
Article
RCML: A Novel Algorithm for Regressing Price Movement during Commodity Futures Stress Testing Based on Machine Learning
by Caifeng Liu, Wenfeng Pan and Hongcheng Zhou
J. Risk Financial Manag. 2023, 16(6), 285; https://doi.org/10.3390/jrfm16060285 - 25 May 2023
Viewed by 952
Abstract
Stress testing, an essential part of the risk management toolkit of financial institutions, refers to the evaluation of a portfolio’s potential risk under an extreme, but plausible, scenario. The most representative method for performing stress testing is historical scenario simulation, which aims to [...] Read more.
Stress testing, an essential part of the risk management toolkit of financial institutions, refers to the evaluation of a portfolio’s potential risk under an extreme, but plausible, scenario. The most representative method for performing stress testing is historical scenario simulation, which aims to evaluate historical adverse market events on the current portfolios of financial institutions. However, some current commodities were not listed in the commodity futures market at the time of the historical event, causing a lack of the necessary price information to revalue the current positions of these commodities. To avoid over reliance on human hypothesis for these non-existent commodity futures, we propose a novel approach, RCML, to infer reasonable price movements for commodities unlisted in historical events. Unlike the previous methods, based on subjective hypothesis, RCML takes advantage of not only machine learning algorithms, but also multi-view information. Back testing and hypothesis testing are adopted to prove the rationality of RCML results. Full article
(This article belongs to the Special Issue Financial Technology (Fintech) and Sustainable Financing Volume II)
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15 pages, 508 KiB  
Article
Social Performance Disclosed by European Companies: The Role of the Board Attributes and the Country’s Legal System
by Albertina Paula Monteiro, Catarina Cepêda, Cláudia Pereira and Amélia Silva
J. Risk Financial Manag. 2023, 16(6), 284; https://doi.org/10.3390/jrfm16060284 - 25 May 2023
Viewed by 1523
Abstract
This paper aims to analyze factors that influence social performance-related information disclosure in European countries. Specifically, the objective is to investigate the Board’s attributes (Diversity, Inclusion, People Development and Controversies). To achieve the goal, an empirical analysis was conducted with 2494 listed companies [...] Read more.
This paper aims to analyze factors that influence social performance-related information disclosure in European countries. Specifically, the objective is to investigate the Board’s attributes (Diversity, Inclusion, People Development and Controversies). To achieve the goal, an empirical analysis was conducted with 2494 listed companies in Europe as support for the economic year 2021. To measure a possible link between the variables under study, a regression analysis was performed. Our results show that Board Diversity, Inclusion and People Development contribute positively to social performance disclosure, whereas Board Controversies negatively affect the dependent variable. Furthermore, the study results reveal that the country’s legal system is relevant to the company’s transparency. The model variables determine 62% of the social performance reporting variance. Our Results are useful for all non-financial information users, governments and organizations in developing sustainability reporting standards. Full article
(This article belongs to the Special Issue Financial and Sustainability Reporting in a Digital Era)
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19 pages, 1606 KiB  
Article
How Efficient and Socially Sensitive Are Fiscal Incentives for Electric Cars in Europe?
by Krešimir Jurlin
J. Risk Financial Manag. 2023, 16(6), 283; https://doi.org/10.3390/jrfm16060283 - 24 May 2023
Viewed by 2273
Abstract
The main aim of the study was to analyse the impact of fiscal incentives on the share of electric passenger cars in total sales in 31 European countries in 2021 and 2022. Research methods included an assessment of the active fiscal incentives and [...] Read more.
The main aim of the study was to analyse the impact of fiscal incentives on the share of electric passenger cars in total sales in 31 European countries in 2021 and 2022. Research methods included an assessment of the active fiscal incentives and passive financial gain on fuel of owning electric over petrol-powered vehicles, calculating the ratio of these variables to the net savings in emissions, and conducting regression analysis of the impact of these two variables, as well as indicators of national wealth and the distribution of population by urbanization, on the share of electric vehicles in total sales. The most important finding of the research is that, in the countries under review, incentives are not well designed. For a saving of 1 ton of CO2 for business-owned plug-in hybrid electric sports utility vehicles, tax incentives stood at EUR 3400, as compared to only EUR 106 for small battery powered electric vehicles, with very high differences between countries. Applied panel data regressions with random effects indicated that active tax incentives had a rather low impact on the share of battery electric vehicles (BEVs) in total passenger car sales in 31 European countries in 2021 and 2022, while the difference in electricity price over petrol price combined with the share of the population living in houses in towns and suburbs may be a rather strong stimulus for buying BEVs (R2 = 0.452 for the total sample and R2 = 0.579 for the reduced sample). However, national wealth between countries, measured by relative final consumption expenditure per capita, had the highest impact on the share of battery electric vehicles in total sales (R2 = 0.634). The study suggests that fiscal incentives for electricity powered vehicles in Europe were too large, and neither well designed nor directed towards less wealthy households. Full article
(This article belongs to the Section Sustainability and Finance)
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32 pages, 2210 KiB  
Article
Duration of the Membership in the GATT/WTO, Structural Economic Vulnerability and Trade Costs
by Sena Kimm Gnangnon
J. Risk Financial Manag. 2023, 16(6), 282; https://doi.org/10.3390/jrfm16060282 - 24 May 2023
Cited by 1 | Viewed by 1251
Abstract
This paper assesses the effects of the duration of membership in the General Agreement on Tariffs and Trade (GATT)/World Trade Organization (WTO) and structural economic vulnerability on trade costs in developing countries. The analysis is performed on an unbalanced panel dataset of 121 [...] Read more.
This paper assesses the effects of the duration of membership in the General Agreement on Tariffs and Trade (GATT)/World Trade Organization (WTO) and structural economic vulnerability on trade costs in developing countries. The analysis is performed on an unbalanced panel dataset of 121 countries over the period 1996–2018 and primarily utilizes the two-step system generalized method of moments estimator. It has established several findings. We obtain that longstanding GATT/WTO members enjoy a larger reduction in trade costs than relatively new GATT/WTO members. Concomitantly, a higher degree of structural economic vulnerability leads to higher trade costs. Moreover, the membership duration exerts a higher trade costs reduction effect in countries that are highly “structurally” vulnerable, including those that face high levels of exposure to shocks and high magnitudes of shocks. Finally, longstanding GATT/WTO members that receive higher amounts of development aid (including total development aid flows, Aid for Trade flows, and NonAfT flows) enjoy a larger trade costs reduction than relatively new GATT/WTO members. Full article
(This article belongs to the Special Issue Foreign Direct Investment & International Trade)
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