With the advancement of globalization and information technology,the financial sharing mode has gradually emerged as a crucial means for enterprises to optimize their financial management.Particularly within the conte...With the advancement of globalization and information technology,the financial sharing mode has gradually emerged as a crucial means for enterprises to optimize their financial management.Particularly within the context of economic globalization,informatization,and digital transformation,enterprises find themselves navigating a rapidly evolving market environment by intensifying competition.To enhance efficiency and competitiveness,many enterprises have embraced the financial sharing model to streamline financial management processes,curtail costs,and bolster the execution of corporate strategies.This article aims to dissect the definition and essence of the financial sharing model and its significance in the realm of enterprise financial management.Drawing upon this analysis and aligning with the needs of enterprise financial management,the article proposes ideas for optimizing management practices,aspiring to foster reform and innovation in enterprise financial management while enhancing its level of financial management and ability to respond to financial risks.This contribution seeks to provide valuable insights for practitioners in the field.展开更多
Financial time series prediction,whether for classification or regression,has been a heated research topic over the last decade.While traditional machine learning algorithms have experienced mediocre results,deep lear...Financial time series prediction,whether for classification or regression,has been a heated research topic over the last decade.While traditional machine learning algorithms have experienced mediocre results,deep learning has largely contributed to the elevation of the prediction performance.Currently,the most up-to-date review of advanced machine learning techniques for financial time series prediction is still lacking,making it challenging for finance domain experts and relevant practitioners to determine which model potentially performs better,what techniques and components are involved,and how themodel can be designed and implemented.This review article provides an overview of techniques,components and frameworks for financial time series prediction,with an emphasis on state-of-the-art deep learning models in the literature from2015 to 2023,including standalonemodels like convolutional neural networks(CNN)that are capable of extracting spatial dependencies within data,and long short-term memory(LSTM)that is designed for handling temporal dependencies;and hybrid models integrating CNN,LSTM,attention mechanism(AM)and other techniques.For illustration and comparison purposes,models proposed in recent studies are mapped to relevant elements of a generalized framework comprised of input,output,feature extraction,prediction,and related processes.Among the state-of-the-artmodels,hybrid models like CNNLSTMand CNN-LSTM-AM in general have been reported superior in performance to stand-alone models like the CNN-only model.Some remaining challenges have been discussed,including non-friendliness for finance domain experts,delayed prediction,domain knowledge negligence,lack of standards,and inability of real-time and highfrequency predictions.The principal contributions of this paper are to provide a one-stop guide for both academia and industry to review,compare and summarize technologies and recent advances in this area,to facilitate smooth and informed implementation,and to highlight future research directions.展开更多
This study investigates how financial literacy and behavioral traits affect the adoption of electronic payment(ePayment)services in Japan.We construct a financial literacy index using a representative sample of 25,000...This study investigates how financial literacy and behavioral traits affect the adoption of electronic payment(ePayment)services in Japan.We construct a financial literacy index using a representative sample of 25,000 individuals from the Bank of Japan’s 2019 Financial Literacy Survey.We then analyze the relationship between this index and the extensive and intensive usage of two types of payment services:electronic money(e-money)and mobile payment apps.Using an instrumental variable approach,we find that higher financial literacy is positively associated with a higher likelihood of adopting ePayment services.The empirical results suggest that individuals with higher financial literacy use payment services more frequently.We also find that risk-averse people are less likely to adopt and use ePayment services,whereas people with herd behavior tend to adopt and use ePayment services more.Our empirical results also suggest that the effects of financial literacy on the adoption and use of ePayment differ among people with different behavioral traits.展开更多
This study proposes a social-financial approach(SFA)to fill the methodological research gap in strategic policy design for managing financial transitions during social changes.The SFA seeks to characterize inclusive t...This study proposes a social-financial approach(SFA)to fill the methodological research gap in strategic policy design for managing financial transitions during social changes.The SFA seeks to characterize inclusive transitions in response to innovation and analyze financial management in social changes.Using a multilevel perspective,we combine evolutionary finance and inclusive growth analytics into this framework.We contend that the interaction between the different levels can be summarized as spontaneous adjustments and the alignment of financial elements with the indicators.Actors who attempt to achieve their goals based on past performance evaluations and other forms of bounded rationality strive to cope with adjustments and further trigger a reorientation of the existing regime.We also developed a new configuration tool called the three-axis description to describe the evolution of financial transitions at different stages.These methods allow us to analyze the evolution of financial transition and efficiency,and we argue that market efficiency evolves in stages with the finan-cial transition.Finally,to demonstrate the capability of SFA to identify diverse financial transition pathways,we examined an example case:the establishment of the Bretton Woods System.展开更多
New technologies such as big data,artificial intelligence,mobile internet,cloud computing,Internet of Things,and blockchain have brought about significant changes and development in the financial industry.Predicting t...New technologies such as big data,artificial intelligence,mobile internet,cloud computing,Internet of Things,and blockchain have brought about significant changes and development in the financial industry.Predicting the financial situation of enterprises,reducing the probability of uncertainty risks,and reducing the likelihood of financial crises have become important issues in enterprise financial crisis warning.In view of the issues in enterprise financial early warning systems such as lag,low accuracy,and high warning costs in data analysis,a financial early warning system based on big data and deep learning technology has been established,taking into account the different situations of listed and non-listed companies.This carries significance in improving the accuracy of enterprise financial early warning and promoting timely and effective decision-making.展开更多
As China’s economy has experienced rapid growth,the economic landscape for higher education institutions’financial systems has become increasingly intricate.Consequently,there has been a heightened demand for enhanc...As China’s economy has experienced rapid growth,the economic landscape for higher education institutions’financial systems has become increasingly intricate.Consequently,there has been a heightened demand for enhanced financial management in these institutions.Notably,in 2012,the country’s Ministry of Finance and Ministry of Education introduced a new financial system for higher education institutions,and in 2022,the Ministry of Finance publicly revised this system to further standardize financial practices within higher education institutions,align with financial management requirements,and foster the development of these institutions.This paper offers an extensive examination of the updated financial system for higher education institutions compared to the previous version,delving into aspects such as the financial management framework,professionalization criteria for financial directors,enhancements in managing the proceeds from technology and research achievements,and the incorporation of management accounting reports.Additionally,it provides a comprehensive analysis of the challenges faced by financial management in higher education institutions and outlines strategies for addressing these issues.展开更多
The extant literature has produced mixed evidence on the relationship between finan-cial development and ecological sustainability.This work addresses this conundrum by investigating financial development’s direct an...The extant literature has produced mixed evidence on the relationship between finan-cial development and ecological sustainability.This work addresses this conundrum by investigating financial development’s direct and indirect consequences on ecologi-cal quality utilizing the environmental Kuznets curve(EKC)methodological approach.Our empirical analysis is based on the novel dynamic autoregressive distributed lag simulations approach for South Africa between 1960 and 2020.The results,which used five distinct financial development measures,demonstrate that financial develop-ment boosts ecological integrity and environmental sustainability over the long and short terms.In the instance of South Africa,we additionally confirm the validity of the EKC theory.More importantly,the outcomes of the indirect channels demonstrate that financial development increases energy usage’s role in causing pollution while attenuating the detrimental impacts of economic growth,trade openness,and foreign direct investment on ecological quality.Moreover,the presence of an inadequate financial system is a requirement for the basis of the pollution haven hypothesis(PHH),which we examine using trade openness and foreign direct investment variables.PHH for both of these variables disappears when financial development crosses specified thresholds.Finally,industrial value addition destroys ecological quality while tech-nological innovation enhances it.This research provides some crucial policy recom-mendations and fresh perspectives for South Africa as it develops national initiatives to support ecological sustainability and reach its net zero emissions goal.展开更多
Financial crisis prediction(FCP)received significant attention in the financial sector for decision-making.Proper forecasting of the number of firms possible to fail is important to determine the growth index and stre...Financial crisis prediction(FCP)received significant attention in the financial sector for decision-making.Proper forecasting of the number of firms possible to fail is important to determine the growth index and strength of a nation’s economy.Conventionally,numerous approaches have been developed in the design of accurate FCP processes.At the same time,classifier efficacy and predictive accuracy are inadequate for real-time applications.In addition,several established techniques carry out well to any of the specific datasets but are not adjustable to distinct datasets.Thus,there is a necessity for developing an effectual prediction technique for optimum classifier performance and adjustable to various datasets.This paper presents a novel multi-vs.optimization(MVO)based feature selection(FS)with an optimal variational auto encoder(OVAE)model for FCP.The proposed multi-vs.optimization based feature selection with optimal variational auto encoder(MVOFS-OVAE)model mainly aims to accomplish forecasting the financial crisis.For achieving this,the proposed MVOFS-OVAE model primarily pre-processes the financial data using min-max normalization.In addition,the MVOFS-OVAE model designs a feature subset selection process using the MVOFS approach.Followed by,the variational auto encoder(VAE)model is applied for the categorization of financial data into financial crisis or non-financial crisis.Finally,the differential evolution(DE)algorithm is utilized for the parameter tuning of the VAE model.A series of simulations on the benchmark dataset reported the betterment of the MVOFS-OVAE approach over the recent state of art approaches.展开更多
The vigorous development of information and communications technology has accelerated reshaping of the financial industry. The COVID-19 pandemic has further catalyzed the demand for digital financial services. Digital...The vigorous development of information and communications technology has accelerated reshaping of the financial industry. The COVID-19 pandemic has further catalyzed the demand for digital financial services. Digital financial inclusion relies on information technology to overcome spatial limitations. In this case, the research question is whether it adheres to the spatial laws governing conventional financial activities. This study uses exploratory spatial data analysis and a geographical detector to elucidate the spatiotemporal characteristics and factors influencing digital financial inclusion at the county level in China(Data don’t include that of Hong Kong, Macao and Taiwan of China) from 2014 to 2020. The research findings indicate: first, China’s county-level digital financial inclusion is generally increasing and exhibits significant spatial autocorrelation. Second, population density, level of traditional financial development, government regulation, and education level are key determinants of China’s county-level digital financial inclusion. Third,policies should be differentiated by region to narrow the spatial gap in digital financial inclusion. The results provide a reference for other developing countries on using digital technology to develop financial inclusion.展开更多
In that paper,we new study has been carried out on previous studies of one of the most important mathematical models that describe the global economic movement,and that is described as a non-linear fractional financia...In that paper,we new study has been carried out on previous studies of one of the most important mathematical models that describe the global economic movement,and that is described as a non-linear fractional financial model of awareness,where the studies are represented at the steps following:One:The schematic of the model is suggested.Two:The disease-free equilibrium point(DFE)and the stability of the equilibrium point are discussed.Three:The stability of the model is fulfilled by drawing the Lyapunov exponents and Poincare map.Fourth:The existence of uniformly stable solutions have discussed.Five:The Caputo is described as the fractional derivative.Six:Fractional optimal control for NFFMA is discussed by clarifying the fractional optimal control through drawing before and after control.Seven:Reduced differential transform method(RDTM)and Sumudu Decomposition Method(SDM)are used to take the resolution of an NFFMA.Finally,we display that SDM and RDTM are highly identical.展开更多
Eye tracking can facilitate understanding irrational decision-making in contexts such as financial risk-taking.For this purpose,we develop an experimental framework in which participants trade a risky asset in a simul...Eye tracking can facilitate understanding irrational decision-making in contexts such as financial risk-taking.For this purpose,we develop an experimental framework in which participants trade a risky asset in a simulated bubble market to maximize individual returns while their eye movements are recorded.Returns are sensitive to eye movement dynamics,depending on the presented visual stimuli.Using eye-tracking data,we investigated the effects of arousal,attention,and disengagement on individual payoffs using linear and nonlinear approaches.By estimating a nonlinear model using attention as a threshold variable,our results suggest that arousal positively influences trading returns,but its effect becomes smaller when attention exceeds a certain threshold,whereas disengagement has a higher negative impact on reduced attention levels and becomes almost irrelevant when attention increases.Hence,we provide a neurobehavioral metric as a function of attention that predicts financial gains in boomand-bust scenarios.This study serves as a proof-of-concept for developing future psychometric measures to enhance decision-making.展开更多
In recent times,financial globalization has drastically increased in different ways to improve the quality of services with advanced resources.The successful applications of bitcoin Blockchain(BC)techniques enable the...In recent times,financial globalization has drastically increased in different ways to improve the quality of services with advanced resources.The successful applications of bitcoin Blockchain(BC)techniques enable the stockholders to worry about the return and risk of financial products.The stockholders focused on the prediction of return rate and risk rate of financial products.Therefore,an automatic return rate bitcoin prediction model becomes essential for BC financial products.The newly designed machine learning(ML)and deep learning(DL)approaches pave the way for return rate predictive method.This study introduces a novel Jellyfish search optimization based extreme learning machine with autoencoder(JSO-ELMAE)for return rate prediction of BC financial products.The presented JSO-ELMAE model designs a new ELMAE model for predicting the return rate of financial products.Besides,the JSO algorithm is exploited to tune the parameters related to the ELMAE model which in turn boosts the classification results.The application of JSO technique assists in optimal parameter adjustment of the ELMAE model to predict the bitcoin return rates.The experimental validation of the JSO-ELMAE model was executed and the outcomes are inspected in many aspects.The experimental values demonstrated the enhanced performance of the JSO-ELMAE model over recent state of art approaches with minimal RMSE of 0.1562.展开更多
The main purpose of the study is to present a numerical approach to investigate the numerical performances of the fractional 4-D chaotic financial system using a stochastic procedure.The stochastic procedures mainly d...The main purpose of the study is to present a numerical approach to investigate the numerical performances of the fractional 4-D chaotic financial system using a stochastic procedure.The stochastic procedures mainly depend on the combination of the artificial neural network(ANNs)along with the Levenberg-Marquardt Backpropagation(LMB)i.e.,ANNs-LMB technique.The fractional-order term is defined in the Caputo sense and three cases are solved using the proposed technique for different values of the fractional orderα.The values of the fractional order derivatives to solve the fractional 4-D chaotic financial system are used between 0 and 1.The data proportion is applied as 73%,15%,and 12%for training,testing,and certification to solve the chaotic fractional system.The acquired results are verified through the comparison of the reference solution,which indicates the proposed technique is efficient and robust.The 4-D chaotic model is numerically solved by using the ANNs-LMB technique to reduce the mean square error(MSE).To authenticate the exactness,and consistency of the technique,the obtained performances are plotted in the figures of correlation measures,error histograms,and regressions.From these figures,it can be witnessed that the provided technique is effective for solving such models to give some new insight into the physical behavior of the model.展开更多
This study aims to shed light on the effects of financial development and accumula-tion of capital on the productivity of labor in the sub-Sahara African region within the period of 1990–2018.In this work,we used the...This study aims to shed light on the effects of financial development and accumula-tion of capital on the productivity of labor in the sub-Sahara African region within the period of 1990–2018.In this work,we used the(dynamic)common correlated effects estimator-mean group and additional techniques such as cross-section autoregressive distributed lag to calibrate the sample into the African subregion to ensure robustness.The findings reveal that financial progress in the region over time leads to an increase in productivity of labor and also the accumulation of capital.Furthermore,financial markets have a progressive impact on the productivity of labor within sub-Saharan African regions.We extend the very limited literature on the nexus between financial development and labor productivity by incorporating capital accumulation into our model which has not been previously studied.展开更多
The purpose of the paper is to identify the factors of financial development that have the greatest impact on open innovation in 7 emerging countries.The analysis was performed featuring the MF-X-DMA method,as well as...The purpose of the paper is to identify the factors of financial development that have the greatest impact on open innovation in 7 emerging countries.The analysis was performed featuring the MF-X-DMA method,as well as its further verification for auto-correlation and heteroscedasticity.The time period covers years from 2002 to 2020.The article states that the main indicators to improve financial development should enhance the process of bank lending and equity market development.An important area is the development of competition by providing equal access to information to all market participants in a continuously refining technical infrastructure.Regression analysis with the MF-X-DMA method confirms the statistical significance of this influ-ence.The article fills the knowledge gap into the link between open innovations and the relatively low capitalization of the modern emerging countries’financial market,low liquidity in small cap stocks at the financial market and concentration of the banking sector,as well as risks arising in the process of globalization.Another analysis has also been conducted by generating a novel fuzzy decision-making model.In the first stage,the determinants of open innovation-based fintech potential are weighted for the emerging economies.For this purpose,M-SWARA methodology is taken into consideration based on bipolar q-ROFSs and golden cut.The second stage of the analysis includes evaluating the emerging economies with the determinants of open innovation-based fintech potential.In this context,emerging seven countries are examined with ELECTRE methodology.It found the most significant factor is the open innovation-based fintech potential.展开更多
This study aims to examine the time-varying efficiency of the Turkish stock market’s major stock index and eight sectoral indices,including the industrial,financial,service,information technology,basic metals,tourism...This study aims to examine the time-varying efficiency of the Turkish stock market’s major stock index and eight sectoral indices,including the industrial,financial,service,information technology,basic metals,tourism,real estate investment,and chemical petrol plastic,during the COVID-19 outbreak and the global financial crisis(GFC)within the framework of the adaptive market hypothesis.This study employs multifractal detrended fluctuation analysis to illustrate these sectors’multifractality and short-and long-term dependence.The results show that all sectoral returns have greater persis-tence during the COVID-19 outbreak than during the GFC.Second,the real estate and information technology industries had the lowest levels of efficiency during the GFC and the COVID-19 outbreak.Lastly,the fat-tailed distribution has a greater effect on multifractality in these industries.Our results validate the conclusions of the adaptive market hypothesis,according to which arbitrage opportunities vary over time,and contribute to policy formulation for future outbreak-induced economic crises.展开更多
Previous literature showed mixed results about the impact of CEOs’financial literacy(CFL)on small and medium-sized enterprises’(SMEs)innovation.This relationship can be motivated by relevant variables,which are miss...Previous literature showed mixed results about the impact of CEOs’financial literacy(CFL)on small and medium-sized enterprises’(SMEs)innovation.This relationship can be motivated by relevant variables,which are missing in the previous literature and make a difference as mediators.In this sense,based on the theoretical framework related to upper echelon theory and resource-based view,this study focuses on the mediating effect of risk-taking attitude and management control systems(MCS)varia-bles.Empirical data from 310 SMEs gathered using a qualitative research questionnaire are analyzed using structural equation modeling methodology.Specifically,estimations are carried out considering the partial least square method.Findings show that MCS and managers’risk attitudes fully mediate the relationship between financial literacy(FL)and innovation.Between these two mediating variables,the implementation of MCS stands out because it also enables the mediating effect of CEOs’risk-taking in the CFL–technological innovation relationship.As the results do not support the significant direct relationship between FL and risk attitude,they confirm an indirect effect through MCS.Furthermore,based on the study findings,SMEs’directors and owners,business associations,and public authorities can improve SMEs’technological innovation by implementing training programs and policies to foster CFL.They can also acknowledge the interdependency between organizational factors and individual characteristics to enhance SMEs’technological innovation.展开更多
This study analyzes the role of financial development(FD)on the impact of technologi-cal innovation(TI)on six environmental quality indicators for the 25 economies that are part of the Organization for Economic Cooper...This study analyzes the role of financial development(FD)on the impact of technologi-cal innovation(TI)on six environmental quality indicators for the 25 economies that are part of the Organization for Economic Cooperation and Development for the period from 2000 to 2019.We use a two-step dynamic generalized method of moments approach to understand this relationship.The results show that FD augments the posi-tive effects of TI on four of the six environmental indicators,namely ecological foot-print,adjusted net savings,pressure on nature,and environmental performance.However,no significant effects on environmental sustainability and environmental vulnerability indices were found.When considering all of the environmental quality indicators,TI appears to enhance environmental quality.We find evidence to support the existence of the environmental Kuznets curve in the context of each environmen-tal indicator and economic growth.Moreover,FD and energy consumption appear to accelerate environmental degradation.Based on these results,FD should be viewed as an important parameter in designing policies for innovation to achieve the goal of net-zero carbon emissions.Highlights.Technological innovation and environmental quality nexus is studied.The moderating role of financial development is analyzed.Six different environmental quality indicators are used for OECD countries.Financial development intensifies the environmental benefits of innovation.•The EKC hypothesis is confirmed for all six environmental indicators.展开更多
Central Asian States(CAS)have diverse natural resources.This research aims to shed light on the finance–natural resource’s association in the context of CAS namely Kazakhstan,Kyrgyzstan,Tajikistan,Turkmenistan,and U...Central Asian States(CAS)have diverse natural resources.This research aims to shed light on the finance–natural resource’s association in the context of CAS namely Kazakhstan,Kyrgyzstan,Tajikistan,Turkmenistan,and Uzbekistan in 1996–2020 using the cross-sectionally augmented autoregressive distributed lag technique.It seeks to examine the research question,“What is the effect of natural resource wealth on the financial expansion(FE)of Central Asia?”The results demonstrated an inverted U-shaped association between financial growth and natural resource rents.It implies that natural resources are initially a“resource blessing”that later becomes a“resource curse.”Additionally,the effect of institutional quality(INQ)and human development(HD)on financial growth is examined.The results reveal that INQ and HD positively affect FE.Moreover,a bidirectional causal relationship exists between FE and INQ.Finally,all variables contribute to a long term FE.Based on these outcomes,the major policy recommendations are that the CAS authorities diversify their financial services and products and direct the proceeds from natural resource rents to effective invest-ments particularly in HD.In addition,the social and political infrastructures in CAS must be restructured to achieve a high-quality institutional environment,which is necessary to increase the role of the private sector.展开更多
The tremendous impact of the coronavirus pandemic on the global aviation industry has led to many cases of airline financial distress and bankruptcy.The Asia–Pacific region(APAC)contains more than half of the world’...The tremendous impact of the coronavirus pandemic on the global aviation industry has led to many cases of airline financial distress and bankruptcy.The Asia–Pacific region(APAC)contains more than half of the world’s population,and its airlines had the highest profit margin of any region.In this study,we investigate whether corporate sustainability practice can reduce the financial distress risk of air carriers,and,if so,what would the effect be in APAC?We first examine the relationship between environmental,social,and governance disclosure and the likelihood of financial distress of airlines as measured by the Altman Z″-score.Second,we analyze the moderating role of being an APAC airline in this relationship.The findings support the claim that implementing environmental actions may increase financial distress risk,and by improving social and governance activities,airlines can mitigate the risk of financial distress.The negative influence of the environmental pillar and the positive influence of the social pillar can be smaller for APAC airlines.Our study provides empirical evidence of the influence of environmental,social,and governance(ESG)on the likelihood of financial distress in the airline industry.Moreover,we analyze the moderating role of being an APAC airline in the relationship between sustainability and financial distress.This study has significant implications for executives,managers,and policymakers in the aviation industry on ESG strategy decisions and the general issue of sustainability.展开更多
文摘With the advancement of globalization and information technology,the financial sharing mode has gradually emerged as a crucial means for enterprises to optimize their financial management.Particularly within the context of economic globalization,informatization,and digital transformation,enterprises find themselves navigating a rapidly evolving market environment by intensifying competition.To enhance efficiency and competitiveness,many enterprises have embraced the financial sharing model to streamline financial management processes,curtail costs,and bolster the execution of corporate strategies.This article aims to dissect the definition and essence of the financial sharing model and its significance in the realm of enterprise financial management.Drawing upon this analysis and aligning with the needs of enterprise financial management,the article proposes ideas for optimizing management practices,aspiring to foster reform and innovation in enterprise financial management while enhancing its level of financial management and ability to respond to financial risks.This contribution seeks to provide valuable insights for practitioners in the field.
基金funded by the Natural Science Foundation of Fujian Province,China (Grant No.2022J05291)Xiamen Scientific Research Funding for Overseas Chinese Scholars.
文摘Financial time series prediction,whether for classification or regression,has been a heated research topic over the last decade.While traditional machine learning algorithms have experienced mediocre results,deep learning has largely contributed to the elevation of the prediction performance.Currently,the most up-to-date review of advanced machine learning techniques for financial time series prediction is still lacking,making it challenging for finance domain experts and relevant practitioners to determine which model potentially performs better,what techniques and components are involved,and how themodel can be designed and implemented.This review article provides an overview of techniques,components and frameworks for financial time series prediction,with an emphasis on state-of-the-art deep learning models in the literature from2015 to 2023,including standalonemodels like convolutional neural networks(CNN)that are capable of extracting spatial dependencies within data,and long short-term memory(LSTM)that is designed for handling temporal dependencies;and hybrid models integrating CNN,LSTM,attention mechanism(AM)and other techniques.For illustration and comparison purposes,models proposed in recent studies are mapped to relevant elements of a generalized framework comprised of input,output,feature extraction,prediction,and related processes.Among the state-of-the-artmodels,hybrid models like CNNLSTMand CNN-LSTM-AM in general have been reported superior in performance to stand-alone models like the CNN-only model.Some remaining challenges have been discussed,including non-friendliness for finance domain experts,delayed prediction,domain knowledge negligence,lack of standards,and inability of real-time and highfrequency predictions.The principal contributions of this paper are to provide a one-stop guide for both academia and industry to review,compare and summarize technologies and recent advances in this area,to facilitate smooth and informed implementation,and to highlight future research directions.
基金National Foundation for Science and Technology Development(No.502.01-2020.308).
文摘This study investigates how financial literacy and behavioral traits affect the adoption of electronic payment(ePayment)services in Japan.We construct a financial literacy index using a representative sample of 25,000 individuals from the Bank of Japan’s 2019 Financial Literacy Survey.We then analyze the relationship between this index and the extensive and intensive usage of two types of payment services:electronic money(e-money)and mobile payment apps.Using an instrumental variable approach,we find that higher financial literacy is positively associated with a higher likelihood of adopting ePayment services.The empirical results suggest that individuals with higher financial literacy use payment services more frequently.We also find that risk-averse people are less likely to adopt and use ePayment services,whereas people with herd behavior tend to adopt and use ePayment services more.Our empirical results also suggest that the effects of financial literacy on the adoption and use of ePayment differ among people with different behavioral traits.
文摘This study proposes a social-financial approach(SFA)to fill the methodological research gap in strategic policy design for managing financial transitions during social changes.The SFA seeks to characterize inclusive transitions in response to innovation and analyze financial management in social changes.Using a multilevel perspective,we combine evolutionary finance and inclusive growth analytics into this framework.We contend that the interaction between the different levels can be summarized as spontaneous adjustments and the alignment of financial elements with the indicators.Actors who attempt to achieve their goals based on past performance evaluations and other forms of bounded rationality strive to cope with adjustments and further trigger a reorientation of the existing regime.We also developed a new configuration tool called the three-axis description to describe the evolution of financial transitions at different stages.These methods allow us to analyze the evolution of financial transition and efficiency,and we argue that market efficiency evolves in stages with the finan-cial transition.Finally,to demonstrate the capability of SFA to identify diverse financial transition pathways,we examined an example case:the establishment of the Bretton Woods System.
文摘New technologies such as big data,artificial intelligence,mobile internet,cloud computing,Internet of Things,and blockchain have brought about significant changes and development in the financial industry.Predicting the financial situation of enterprises,reducing the probability of uncertainty risks,and reducing the likelihood of financial crises have become important issues in enterprise financial crisis warning.In view of the issues in enterprise financial early warning systems such as lag,low accuracy,and high warning costs in data analysis,a financial early warning system based on big data and deep learning technology has been established,taking into account the different situations of listed and non-listed companies.This carries significance in improving the accuracy of enterprise financial early warning and promoting timely and effective decision-making.
文摘As China’s economy has experienced rapid growth,the economic landscape for higher education institutions’financial systems has become increasingly intricate.Consequently,there has been a heightened demand for enhanced financial management in these institutions.Notably,in 2012,the country’s Ministry of Finance and Ministry of Education introduced a new financial system for higher education institutions,and in 2022,the Ministry of Finance publicly revised this system to further standardize financial practices within higher education institutions,align with financial management requirements,and foster the development of these institutions.This paper offers an extensive examination of the updated financial system for higher education institutions compared to the previous version,delving into aspects such as the financial management framework,professionalization criteria for financial directors,enhancements in managing the proceeds from technology and research achievements,and the incorporation of management accounting reports.Additionally,it provides a comprehensive analysis of the challenges faced by financial management in higher education institutions and outlines strategies for addressing these issues.
文摘The extant literature has produced mixed evidence on the relationship between finan-cial development and ecological sustainability.This work addresses this conundrum by investigating financial development’s direct and indirect consequences on ecologi-cal quality utilizing the environmental Kuznets curve(EKC)methodological approach.Our empirical analysis is based on the novel dynamic autoregressive distributed lag simulations approach for South Africa between 1960 and 2020.The results,which used five distinct financial development measures,demonstrate that financial develop-ment boosts ecological integrity and environmental sustainability over the long and short terms.In the instance of South Africa,we additionally confirm the validity of the EKC theory.More importantly,the outcomes of the indirect channels demonstrate that financial development increases energy usage’s role in causing pollution while attenuating the detrimental impacts of economic growth,trade openness,and foreign direct investment on ecological quality.Moreover,the presence of an inadequate financial system is a requirement for the basis of the pollution haven hypothesis(PHH),which we examine using trade openness and foreign direct investment variables.PHH for both of these variables disappears when financial development crosses specified thresholds.Finally,industrial value addition destroys ecological quality while tech-nological innovation enhances it.This research provides some crucial policy recom-mendations and fresh perspectives for South Africa as it develops national initiatives to support ecological sustainability and reach its net zero emissions goal.
文摘Financial crisis prediction(FCP)received significant attention in the financial sector for decision-making.Proper forecasting of the number of firms possible to fail is important to determine the growth index and strength of a nation’s economy.Conventionally,numerous approaches have been developed in the design of accurate FCP processes.At the same time,classifier efficacy and predictive accuracy are inadequate for real-time applications.In addition,several established techniques carry out well to any of the specific datasets but are not adjustable to distinct datasets.Thus,there is a necessity for developing an effectual prediction technique for optimum classifier performance and adjustable to various datasets.This paper presents a novel multi-vs.optimization(MVO)based feature selection(FS)with an optimal variational auto encoder(OVAE)model for FCP.The proposed multi-vs.optimization based feature selection with optimal variational auto encoder(MVOFS-OVAE)model mainly aims to accomplish forecasting the financial crisis.For achieving this,the proposed MVOFS-OVAE model primarily pre-processes the financial data using min-max normalization.In addition,the MVOFS-OVAE model designs a feature subset selection process using the MVOFS approach.Followed by,the variational auto encoder(VAE)model is applied for the categorization of financial data into financial crisis or non-financial crisis.Finally,the differential evolution(DE)algorithm is utilized for the parameter tuning of the VAE model.A series of simulations on the benchmark dataset reported the betterment of the MVOFS-OVAE approach over the recent state of art approaches.
基金Under the auspices of National Natural Science Foundation of China (No.42171188)Natural Science Foundation of Guangdong Province (No.2022A1515010992)。
文摘The vigorous development of information and communications technology has accelerated reshaping of the financial industry. The COVID-19 pandemic has further catalyzed the demand for digital financial services. Digital financial inclusion relies on information technology to overcome spatial limitations. In this case, the research question is whether it adheres to the spatial laws governing conventional financial activities. This study uses exploratory spatial data analysis and a geographical detector to elucidate the spatiotemporal characteristics and factors influencing digital financial inclusion at the county level in China(Data don’t include that of Hong Kong, Macao and Taiwan of China) from 2014 to 2020. The research findings indicate: first, China’s county-level digital financial inclusion is generally increasing and exhibits significant spatial autocorrelation. Second, population density, level of traditional financial development, government regulation, and education level are key determinants of China’s county-level digital financial inclusion. Third,policies should be differentiated by region to narrow the spatial gap in digital financial inclusion. The results provide a reference for other developing countries on using digital technology to develop financial inclusion.
文摘In that paper,we new study has been carried out on previous studies of one of the most important mathematical models that describe the global economic movement,and that is described as a non-linear fractional financial model of awareness,where the studies are represented at the steps following:One:The schematic of the model is suggested.Two:The disease-free equilibrium point(DFE)and the stability of the equilibrium point are discussed.Three:The stability of the model is fulfilled by drawing the Lyapunov exponents and Poincare map.Fourth:The existence of uniformly stable solutions have discussed.Five:The Caputo is described as the fractional derivative.Six:Fractional optimal control for NFFMA is discussed by clarifying the fractional optimal control through drawing before and after control.Seven:Reduced differential transform method(RDTM)and Sumudu Decomposition Method(SDM)are used to take the resolution of an NFFMA.Finally,we display that SDM and RDTM are highly identical.
文摘Eye tracking can facilitate understanding irrational decision-making in contexts such as financial risk-taking.For this purpose,we develop an experimental framework in which participants trade a risky asset in a simulated bubble market to maximize individual returns while their eye movements are recorded.Returns are sensitive to eye movement dynamics,depending on the presented visual stimuli.Using eye-tracking data,we investigated the effects of arousal,attention,and disengagement on individual payoffs using linear and nonlinear approaches.By estimating a nonlinear model using attention as a threshold variable,our results suggest that arousal positively influences trading returns,but its effect becomes smaller when attention exceeds a certain threshold,whereas disengagement has a higher negative impact on reduced attention levels and becomes almost irrelevant when attention increases.Hence,we provide a neurobehavioral metric as a function of attention that predicts financial gains in boomand-bust scenarios.This study serves as a proof-of-concept for developing future psychometric measures to enhance decision-making.
基金supported in part by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(NRF-2021R1A6A1A03039493)by the NRF grant funded by the Korea government(MSIT)(NRF-2022R1A2C1004401).
文摘In recent times,financial globalization has drastically increased in different ways to improve the quality of services with advanced resources.The successful applications of bitcoin Blockchain(BC)techniques enable the stockholders to worry about the return and risk of financial products.The stockholders focused on the prediction of return rate and risk rate of financial products.Therefore,an automatic return rate bitcoin prediction model becomes essential for BC financial products.The newly designed machine learning(ML)and deep learning(DL)approaches pave the way for return rate predictive method.This study introduces a novel Jellyfish search optimization based extreme learning machine with autoencoder(JSO-ELMAE)for return rate prediction of BC financial products.The presented JSO-ELMAE model designs a new ELMAE model for predicting the return rate of financial products.Besides,the JSO algorithm is exploited to tune the parameters related to the ELMAE model which in turn boosts the classification results.The application of JSO technique assists in optimal parameter adjustment of the ELMAE model to predict the bitcoin return rates.The experimental validation of the JSO-ELMAE model was executed and the outcomes are inspected in many aspects.The experimental values demonstrated the enhanced performance of the JSO-ELMAE model over recent state of art approaches with minimal RMSE of 0.1562.
基金National Research Council of Thailand(NRCT)and Khon Kaen University:N42A650291.
文摘The main purpose of the study is to present a numerical approach to investigate the numerical performances of the fractional 4-D chaotic financial system using a stochastic procedure.The stochastic procedures mainly depend on the combination of the artificial neural network(ANNs)along with the Levenberg-Marquardt Backpropagation(LMB)i.e.,ANNs-LMB technique.The fractional-order term is defined in the Caputo sense and three cases are solved using the proposed technique for different values of the fractional orderα.The values of the fractional order derivatives to solve the fractional 4-D chaotic financial system are used between 0 and 1.The data proportion is applied as 73%,15%,and 12%for training,testing,and certification to solve the chaotic fractional system.The acquired results are verified through the comparison of the reference solution,which indicates the proposed technique is efficient and robust.The 4-D chaotic model is numerically solved by using the ANNs-LMB technique to reduce the mean square error(MSE).To authenticate the exactness,and consistency of the technique,the obtained performances are plotted in the figures of correlation measures,error histograms,and regressions.From these figures,it can be witnessed that the provided technique is effective for solving such models to give some new insight into the physical behavior of the model.
文摘This study aims to shed light on the effects of financial development and accumula-tion of capital on the productivity of labor in the sub-Sahara African region within the period of 1990–2018.In this work,we used the(dynamic)common correlated effects estimator-mean group and additional techniques such as cross-section autoregressive distributed lag to calibrate the sample into the African subregion to ensure robustness.The findings reveal that financial progress in the region over time leads to an increase in productivity of labor and also the accumulation of capital.Furthermore,financial markets have a progressive impact on the productivity of labor within sub-Saharan African regions.We extend the very limited literature on the nexus between financial development and labor productivity by incorporating capital accumulation into our model which has not been previously studied.
文摘The purpose of the paper is to identify the factors of financial development that have the greatest impact on open innovation in 7 emerging countries.The analysis was performed featuring the MF-X-DMA method,as well as its further verification for auto-correlation and heteroscedasticity.The time period covers years from 2002 to 2020.The article states that the main indicators to improve financial development should enhance the process of bank lending and equity market development.An important area is the development of competition by providing equal access to information to all market participants in a continuously refining technical infrastructure.Regression analysis with the MF-X-DMA method confirms the statistical significance of this influ-ence.The article fills the knowledge gap into the link between open innovations and the relatively low capitalization of the modern emerging countries’financial market,low liquidity in small cap stocks at the financial market and concentration of the banking sector,as well as risks arising in the process of globalization.Another analysis has also been conducted by generating a novel fuzzy decision-making model.In the first stage,the determinants of open innovation-based fintech potential are weighted for the emerging economies.For this purpose,M-SWARA methodology is taken into consideration based on bipolar q-ROFSs and golden cut.The second stage of the analysis includes evaluating the emerging economies with the determinants of open innovation-based fintech potential.In this context,emerging seven countries are examined with ELECTRE methodology.It found the most significant factor is the open innovation-based fintech potential.
文摘This study aims to examine the time-varying efficiency of the Turkish stock market’s major stock index and eight sectoral indices,including the industrial,financial,service,information technology,basic metals,tourism,real estate investment,and chemical petrol plastic,during the COVID-19 outbreak and the global financial crisis(GFC)within the framework of the adaptive market hypothesis.This study employs multifractal detrended fluctuation analysis to illustrate these sectors’multifractality and short-and long-term dependence.The results show that all sectoral returns have greater persis-tence during the COVID-19 outbreak than during the GFC.Second,the real estate and information technology industries had the lowest levels of efficiency during the GFC and the COVID-19 outbreak.Lastly,the fat-tailed distribution has a greater effect on multifractality in these industries.Our results validate the conclusions of the adaptive market hypothesis,according to which arbitrage opportunities vary over time,and contribute to policy formulation for future outbreak-induced economic crises.
文摘Previous literature showed mixed results about the impact of CEOs’financial literacy(CFL)on small and medium-sized enterprises’(SMEs)innovation.This relationship can be motivated by relevant variables,which are missing in the previous literature and make a difference as mediators.In this sense,based on the theoretical framework related to upper echelon theory and resource-based view,this study focuses on the mediating effect of risk-taking attitude and management control systems(MCS)varia-bles.Empirical data from 310 SMEs gathered using a qualitative research questionnaire are analyzed using structural equation modeling methodology.Specifically,estimations are carried out considering the partial least square method.Findings show that MCS and managers’risk attitudes fully mediate the relationship between financial literacy(FL)and innovation.Between these two mediating variables,the implementation of MCS stands out because it also enables the mediating effect of CEOs’risk-taking in the CFL–technological innovation relationship.As the results do not support the significant direct relationship between FL and risk attitude,they confirm an indirect effect through MCS.Furthermore,based on the study findings,SMEs’directors and owners,business associations,and public authorities can improve SMEs’technological innovation by implementing training programs and policies to foster CFL.They can also acknowledge the interdependency between organizational factors and individual characteristics to enhance SMEs’technological innovation.
基金This research paper did not receive any financial aid from any source.
文摘This study analyzes the role of financial development(FD)on the impact of technologi-cal innovation(TI)on six environmental quality indicators for the 25 economies that are part of the Organization for Economic Cooperation and Development for the period from 2000 to 2019.We use a two-step dynamic generalized method of moments approach to understand this relationship.The results show that FD augments the posi-tive effects of TI on four of the six environmental indicators,namely ecological foot-print,adjusted net savings,pressure on nature,and environmental performance.However,no significant effects on environmental sustainability and environmental vulnerability indices were found.When considering all of the environmental quality indicators,TI appears to enhance environmental quality.We find evidence to support the existence of the environmental Kuznets curve in the context of each environmen-tal indicator and economic growth.Moreover,FD and energy consumption appear to accelerate environmental degradation.Based on these results,FD should be viewed as an important parameter in designing policies for innovation to achieve the goal of net-zero carbon emissions.Highlights.Technological innovation and environmental quality nexus is studied.The moderating role of financial development is analyzed.Six different environmental quality indicators are used for OECD countries.Financial development intensifies the environmental benefits of innovation.•The EKC hypothesis is confirmed for all six environmental indicators.
文摘Central Asian States(CAS)have diverse natural resources.This research aims to shed light on the finance–natural resource’s association in the context of CAS namely Kazakhstan,Kyrgyzstan,Tajikistan,Turkmenistan,and Uzbekistan in 1996–2020 using the cross-sectionally augmented autoregressive distributed lag technique.It seeks to examine the research question,“What is the effect of natural resource wealth on the financial expansion(FE)of Central Asia?”The results demonstrated an inverted U-shaped association between financial growth and natural resource rents.It implies that natural resources are initially a“resource blessing”that later becomes a“resource curse.”Additionally,the effect of institutional quality(INQ)and human development(HD)on financial growth is examined.The results reveal that INQ and HD positively affect FE.Moreover,a bidirectional causal relationship exists between FE and INQ.Finally,all variables contribute to a long term FE.Based on these outcomes,the major policy recommendations are that the CAS authorities diversify their financial services and products and direct the proceeds from natural resource rents to effective invest-ments particularly in HD.In addition,the social and political infrastructures in CAS must be restructured to achieve a high-quality institutional environment,which is necessary to increase the role of the private sector.
文摘The tremendous impact of the coronavirus pandemic on the global aviation industry has led to many cases of airline financial distress and bankruptcy.The Asia–Pacific region(APAC)contains more than half of the world’s population,and its airlines had the highest profit margin of any region.In this study,we investigate whether corporate sustainability practice can reduce the financial distress risk of air carriers,and,if so,what would the effect be in APAC?We first examine the relationship between environmental,social,and governance disclosure and the likelihood of financial distress of airlines as measured by the Altman Z″-score.Second,we analyze the moderating role of being an APAC airline in this relationship.The findings support the claim that implementing environmental actions may increase financial distress risk,and by improving social and governance activities,airlines can mitigate the risk of financial distress.The negative influence of the environmental pillar and the positive influence of the social pillar can be smaller for APAC airlines.Our study provides empirical evidence of the influence of environmental,social,and governance(ESG)on the likelihood of financial distress in the airline industry.Moreover,we analyze the moderating role of being an APAC airline in the relationship between sustainability and financial distress.This study has significant implications for executives,managers,and policymakers in the aviation industry on ESG strategy decisions and the general issue of sustainability.
