BACKGROUND Return to work(RTW)serves as an indication for young and middle-aged colorectal cancer(CRC)survivors to resume their normal social lives.However,these survivors encounter significant challenges during their...BACKGROUND Return to work(RTW)serves as an indication for young and middle-aged colorectal cancer(CRC)survivors to resume their normal social lives.However,these survivors encounter significant challenges during their RTW process.Hence,scientific research is necessary to explore the barriers and facilitating factors of returning to work for young and middle-aged CRC survivors.AIM To examine the current RTW status among young and middle-aged CRC survivors and to analyze the impact of RTW self-efficacy(RTW-SE),fear of progression(FoP),eHealth literacy(eHL),family resilience(FR),and financial toxicity(FT)on their RTW outcomes.METHODS A cross-sectional investigation was adopted in this study.From September 2022 to February 2023,a total of 209 participants were recruited through a convenience sampling method from the gastrointestinal surgery department of a class A tertiary hospital in Chongqing.The investigation utilized a general information questionnaire alongside scales assessing RTW-SE,FoP,eHL,FR,and FT.To analyze the factors that influence RTW outcomes among young and middle-aged CRC survivors,Cox regression modeling and Kaplan-Meier survival analysis were used.RESULTS A total of 43.54%of the participants successfully returned to work,with an average RTW time of 100 days.Cox regression univariate analysis revealed that RTW-SE,FoP,eHL,FR,and FT were significantly different between the non-RTW and RTW groups(P<0.05).Furthermore,Cox regression multivariate analysis identified per capita family monthly income,job type,RTW-SE,and FR as independent influencing factors for RTW(P<0.05).CONCLUSION The RTW rate requires further improvement.Elevated levels of RTW-SE and FR were found to significantly increase RTW among young and middle-aged CRC survivors.Health professionals should focus on modifiable factors,such as RTW-SE and FR,to design targeted RTW support programs,thereby facilitating their timely reintegration into mainstream society.展开更多
The feed industry serves as a critical intermediary between agriculture and animal husbandry,providing essential support for the modern breeding industry.Utilizing the annual financial report data from 19 publicly lis...The feed industry serves as a critical intermediary between agriculture and animal husbandry,providing essential support for the modern breeding industry.Utilizing the annual financial report data from 19 publicly listed companies within the feed industry in 2023,a comprehensive evaluation index system was developed to assess the financial performance of these companies from four dimensions:debt paying ability,operational ability,profitability,and development ability.Factor analysis and hierarchical cluster analysis were employed to assess the financial performance of publicly listed companies within the feed industry.By comparing the mean classifications and comprehensive scores,this study analyzed the strengths and weaknesses of these listed feed companies.Ultimately,it offered recommendations for improvement in areas such as product optimization and enhancement,reasonable liability management,and the advancement of company governance practices.展开更多
As a key sector in advancing China’s“carbon neutrality”goal,the machinery manufacturing industry has achieved remarkable development in recent years.Against this backdrop,the scientific and objective evaluation of ...As a key sector in advancing China’s“carbon neutrality”goal,the machinery manufacturing industry has achieved remarkable development in recent years.Against this backdrop,the scientific and objective evaluation of the financial performance of machinery manufacturing enterprises has become a pressing issue in financial research.This topic is not only crucial for optimizing enterprise management and improving operational efficiency but also essential for enhancing overall industry performance and promoting sustainable development.This paper first introduces the concept of financial performance,followed by an analysis of related financial performance evaluation theories.It then focuses on the application of the entropy method in evaluating the financial performance of machinery manufacturing enterprises,detailing its analytical steps.Finally,a financial performance evaluation index system is constructed based on four dimensions:profitability,solvency,operational efficiency,and growth potential.展开更多
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
This article elaborates on the necessity of promoting the integration of business and finance based on financial sharing,analyzes the measures and effects of implementing business and finance integration in enterprise...This article elaborates on the necessity of promoting the integration of business and finance based on financial sharing,analyzes the measures and effects of implementing business and finance integration in enterprises,points out the existing problems,and proposes strategies to optimize the integration from three aspects:building big data platforms,improving talent training plans,and improving financial shared information management platforms.展开更多
Preventing financial risk is an important topic that academic circles and the government have paid attention to for a long time.The development of fintech and the improvement of financial regulation will affect the le...Preventing financial risk is an important topic that academic circles and the government have paid attention to for a long time.The development of fintech and the improvement of financial regulation will affect the level of financial risk.The relationship between the degree of matching between fintech and financial regulation and financial risk is explored,which is crucial for reducing financial risk.Panel data from 31 provinces in China from 2011 to 2020 is used to explore the impact of fintech and financial regulatory matching levels on financial risk.The study finds that the improved matching level between fintech and financial regulation helps reduce financial risk.The degree of matching between fintech and financial regulation affects financial risk through financial efficiency.展开更多
This paper examines the financial risk evaluation system in the context of the“Great Intelligence Movement Cloud”and employs the hierarchical analysis method as the primary research tool.With the rapid advancement o...This paper examines the financial risk evaluation system in the context of the“Great Intelligence Movement Cloud”and employs the hierarchical analysis method as the primary research tool.With the rapid advancement of“Great Intelligence Movement Cloud”technology,enterprise financial risks have expanded from the offline domain to the information domain,encompassing a broader scope and more diverse channels.The traditional approach to risk identification,relying solely on single financial indicators,no longer meets current demands.Therefore,it is essential to integrate a non-financial early warning indicator system and adopt a combination of quantitative and qualitative analysis methods.Hierarchical analysis enables the decomposition of complex problems into multiple components and organizes them into a hierarchical structure based on their relationships,facilitating a more accurate assessment of financial risk.This study seeks to establish a comprehensive financial risk evaluation system suited to the“Great Intelligence Movement Cloud”context,offering enterprises more precise risk assessments to better address financial risks and achieve steady development.展开更多
The rapid pace of economic globalization has presented both unprecedented opportunities and challenges for the construction industry.Management accounting and financial accounting,as integral components of enterprise ...The rapid pace of economic globalization has presented both unprecedented opportunities and challenges for the construction industry.Management accounting and financial accounting,as integral components of enterprise management,play indispensable roles in the development of construction companies.While both disciplines possess distinct characteristics,the evolving business landscape necessitates a more integrated approach.By combining the strengths and values of both,construction companies can gain valuable insights and make informed decisions.This paper delves into the concepts of management accounting and financial accounting,explores the feasibility of their integration within construction companies,and provides recommendations for implementation to foster sustainable development.The insights and strategies presented in this paper can serve as a valuable reference for other construction companies seeking to optimize their management and operations.展开更多
The dynamic analysis of financial systems is a developing field that combines mathematics and economics to understand and explain fluctuations in financial markets.This paper introduces a new three-dimensional(3D)frac...The dynamic analysis of financial systems is a developing field that combines mathematics and economics to understand and explain fluctuations in financial markets.This paper introduces a new three-dimensional(3D)fractional financial map and we dissect its nonlinear dynamics system under commensurate and incommensurate orders.As such,we evaluate when the equilibrium points are stable or unstable at various fractional orders.We use many numerical methods,phase plots in 2D and 3D projections,bifurcation diagrams and the maximum Lyapunov exponent.These techniques reveal that financial maps exhibit chaotic attractor behavior.This study is grounded on the Caputo-like discrete operator,which is specifically influenced by the variance of the commensurate and incommensurate orders.Furthermore,we confirm the presence and measure the complexity of chaos in financial maps by the 0-1 test and the approximate entropy algorithm.Additionally,we offer nonlinear-type controllers to stabilize the fractional financial map.The numerical results of this study are obtained using MATLAB.展开更多
The increasing data pool in finance sectors forces machine learning(ML)to step into new complications.Banking data has significant financial implications and is confidential.Combining users data from several organizat...The increasing data pool in finance sectors forces machine learning(ML)to step into new complications.Banking data has significant financial implications and is confidential.Combining users data from several organizations for various banking services may result in various intrusions and privacy leakages.As a result,this study employs federated learning(FL)using a flower paradigm to preserve each organization’s privacy while collaborating to build a robust shared global model.However,diverse data distributions in the collaborative training process might result in inadequate model learning and a lack of privacy.To address this issue,the present paper proposes the imple-mentation of Federated Averaging(FedAvg)and Federated Proximal(FedProx)methods in the flower framework,which take advantage of the data locality while training and guaranteeing global convergence.Resultantly improves the privacy of the local models.This analysis used the credit card and Canadian Institute for Cybersecurity Intrusion Detection Evaluation(CICIDS)datasets.Precision,recall,and accuracy as performance indicators to show the efficacy of the proposed strategy using FedAvg and FedProx.The experimental findings suggest that the proposed approach helps to safely use banking data from diverse sources to enhance customer banking services by obtaining accuracy of 99.55%and 83.72%for FedAvg and 99.57%,and 84.63%for FedProx.展开更多
In the rapidly evolving landscape of today’s digital economy,Financial Technology(Fintech)emerges as a trans-formative force,propelled by the dynamic synergy between Artificial Intelligence(AI)and Algorithmic Trading...In the rapidly evolving landscape of today’s digital economy,Financial Technology(Fintech)emerges as a trans-formative force,propelled by the dynamic synergy between Artificial Intelligence(AI)and Algorithmic Trading.Our in-depth investigation delves into the intricacies of merging Multi-Agent Reinforcement Learning(MARL)and Explainable AI(XAI)within Fintech,aiming to refine Algorithmic Trading strategies.Through meticulous examination,we uncover the nuanced interactions of AI-driven agents as they collaborate and compete within the financial realm,employing sophisticated deep learning techniques to enhance the clarity and adaptability of trading decisions.These AI-infused Fintech platforms harness collective intelligence to unearth trends,mitigate risks,and provide tailored financial guidance,fostering benefits for individuals and enterprises navigating the digital landscape.Our research holds the potential to revolutionize finance,opening doors to fresh avenues for investment and asset management in the digital age.Additionally,our statistical evaluation yields encouraging results,with metrics such as Accuracy=0.85,Precision=0.88,and F1 Score=0.86,reaffirming the efficacy of our approach within Fintech and emphasizing its reliability and innovative prowess.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
As a novel economic form,the digital economy is reshaping the financial regulatory landscape and significantly impacting regulatory costs.This paper incorporates the digital economy and financial regulatory costs into...As a novel economic form,the digital economy is reshaping the financial regulatory landscape and significantly impacting regulatory costs.This paper incorporates the digital economy and financial regulatory costs into the classic Solow growth model,uncovering an inverted U-shaped relationship between them.A subsequent mechanism analysis explains the rationale behind this relationship.To empirically examine this relationship in China,the paper utilizes inter-provincial panel data from 2013 to 2021 and employs methodologies such as the two-way fixed effects and moderating effects models.These analyses have important implications for the sound and sustainable development of China’s financial industry.The findings indicate:(a)As China’s digital economy develops,its impact on financial regulatory costs follows an inverted U-shaped pattern,initially increasing and then declining.This conclusion remains valid after robustness tests.(b)The influence of the digital economy on regulatory costs depends on favorable external conditions.Specifically,the impact is more pronounced in regions and periods with better digital infrastructure and more abundant human capital.(c)Additionally,redundant resources moderate this impact,which can weaken the inverted U-shaped relationship.Our findings not only provide a theoretical foundation for understanding the impact of the digital economy on financial regulatory costs but also offer valuable policy insights for optimizing financial regulation in China.展开更多
With intensifying global climate change,humanity is confronted with unparalleled environmental challenges and risks.This study employs the staggered difference-in-difference model to examine the relationship between c...With intensifying global climate change,humanity is confronted with unparalleled environmental challenges and risks.This study employs the staggered difference-in-difference model to examine the relationship between climate policy and green innovation in the corporate financialization context.Using Chinese-listed company data from 2008 to 2020,our analysis reveals a favorable correlation between China’s carbon emission trading policy(CCTP)and advancements in green innovation.Furthermore,we find that the level of corporate financialization moderates this correlation,diminishing the driving effect of CCTP on green innovation.Additionally,results of heterogeneity analysis show that this moderating consequence is more evident in non-state owned and low-digitization enterprises compared with state-owned and high-digitization ones.Our findings contribute to the existing literature by clarifying the interaction between CCTP,green innovation,and corporate financialization.Our research provides valuable insights for policymakers and stakeholders seeking to strengthen climate policies and encourages green innovation in different types of businesses.展开更多
In 2022,the United States stepped up its sanctions on Russia.Most notably,it restricted the flow of the Russian Central Bank's foreign exchange(forex)assets,using financial administrative power as a source of stra...In 2022,the United States stepped up its sanctions on Russia.Most notably,it restricted the flow of the Russian Central Bank's foreign exchange(forex)assets,using financial administrative power as a source of strategic leverage.This move should have reduced the appeal of US dollar assets but in reality has not accelerated as expected the decline of the greenback as a store of value.The US dollar's share of global forex reserves increased instead of decreased during 2022 and 2023.Despite the rise of economic costs caused by tightened US financial sanctions,countries that recognize the geopolitical role of the United States have further accepted the dollar's international status;their continued willingness to live with the dollar's“security premium”has given a fillip to the US dollar in the short term,boosting its appeal as a reserve currency.Meanwhile,de-dollarization of forex reserves has yet to reach a sufficient scale,thus falling short of significantly challenging the dollar's reign.From a longer-term perspective,as economic and security conditions shift,countries that accept the dollar's international role or seek de-dollarization may change their choices.As a result,four possible scenarios may arise:(i)the preeminence of the US dollar remains unthreatened;(ii)the international monetary system splits into blocs;(iii)the international monetary system fragments;and(iv)the dollar loses its throne.The author believes that the last scenario is the most likely outcome.展开更多
We present a new methodology to statistically determine the net present value(NPV)and internal rate of return(IRR)as financial estimators of shale gas investments.Our method allows us to forecast,in a fully probabilis...We present a new methodology to statistically determine the net present value(NPV)and internal rate of return(IRR)as financial estimators of shale gas investments.Our method allows us to forecast,in a fully probabilistic setting,financial performance risk and to understand the importance of the different factors that impact investment.The methodology developed in this study combines,through Monte Carlo simulation,the computational modeling of gas production from shale gas wells with a stochastic simulation of gas price as a geometric Brownian motion(GMB).To illustrate the methodology's validity,we apply it to an analysis of investments in shale gas wells.Our results show that gas price volatility is a key variable in the performance of an investment of this type,in such a way that at high volatilities,the potential return on an investment in shale gas increases significantly,but so do the risks of economic loss.This finding is consistent with the history of shale gas operations in which huge investment successes coexist with unexpected investment failures.展开更多
There is a broad connection between finance and human rights,with finance having both positive and negative impacts on human rights.Everyone has a need for access to financial services.Documents in both the internatio...There is a broad connection between finance and human rights,with finance having both positive and negative impacts on human rights.Everyone has a need for access to financial services.Documents in both the international human rights and international finance fields address the relationship between financial services and human rights.Among financial services,microcredit and inclusive finance have the closest connection to human rights and potentially the greatest impact on human rights.Access to financial services promotes economic,social,and cultural rights as well as the rights of specific groups.The conditions for access to financial services to promote human rights require the state to assume obligations to recognize,respect,protect,and fulfill the need for individuals to access financial services,and to ensure the availability,accessibility,acceptability,and adaptability of basic financial services.Access to financial services has played a significant role in China’s comprehensive victory in the battle of poverty alleviation,providing valuable experience for the international community in poverty eradication,achieving sustainable development goals,and protecting and promoting human rights.展开更多
The study focuses on assessing the financial management practices and accounting mechanisms in agricultural cooperatives in Tulsipur Sub-Metropolitan,Dang District,Nepal with a focus on understanding their implication...The study focuses on assessing the financial management practices and accounting mechanisms in agricultural cooperatives in Tulsipur Sub-Metropolitan,Dang District,Nepal with a focus on understanding their implications for financial performance and organizational effectiveness.The sample size of total cooperatives(n=46)was divided into Savings and Credit Cooperatives(n=18)and Multipurpose Cooperatives(n=28),respectively,with a total number of respondents(n=138)categorized into managing directors,employees,and general members.Using a mixed-methods approach that combines quantitative analysis of financial data with qualitative insights gathered through interviews and surveys,the study emphasizes the importance of modern financial practices,improved reporting mechanisms,and relevant staff training for long-term sustainability.Recommendations include the integration of criteria and evaluation tools to assess cooperative performance,with Hamro Pahunch Multipurpose Cooperative identified as a high performer.Emphasizing the need for robust financial management strategies to navigate the complexity of the agricultural sector,manage risks,and achieve sustainable development,the study notes frequent preparation of financial management reports on a monthly and annual basis,and predominantly annual accounting management.Most cooperatives are using computerized models to present financial positions,but face challenges such as lack of marketing infrastructure,cooperative skills,and technical support.Ultimately,the study advocates for educating policy makers,cooperative leaders,practitioners and stakeholders on the role of effective financial management and accounting in enhancing the resilience,expansion and socio-economic impact of agricultural cooperatives,thereby fostering their long-term prosperity and viability as drivers of rural development and empowerment.展开更多
From the perspective of the digital economy,enterprise financial management is facing unprecedented challenges and opportunities.Traditional financial management models are no longer suited to current development need...From the perspective of the digital economy,enterprise financial management is facing unprecedented challenges and opportunities.Traditional financial management models are no longer suited to current development needs.Fine-tuning financial management is essential to support the modernization of enterprises,guard against operational risks,and promote coordination across the entire value chain for greater economic efficiency.With the help of digital technology,data-driven,highly interconnected,and intelligent decision-making processes are becoming more prominent,profoundly transforming the operational and financial management models of enterprises.This enables financial management to keep pace with modern developments.In light of this,the paper explores the connotations and mechanisms of the digital economy and enterprise financial management,clarifies relevant conceptual characteristics,and identifies problems in financial management under the digital economy.It also offers strategies for optimization and problem-solving,with the aim of providing valuable insights for educators and practitioners.展开更多
In the context of the rapid development of big data technology,the financial management model of Internet financial enterprises is undergoing a profound transformation.This paper analyzes the key aspects of applying b...In the context of the rapid development of big data technology,the financial management model of Internet financial enterprises is undergoing a profound transformation.This paper analyzes the key aspects of applying big data technology in Internet finance,including its basic concepts,characteristics,and current state of development in the field.It examines the current situation and primary challenges faced by financial management in Internet financial enterprises,such as risk management,cost control,and data integration.To address these challenges,optimization strategies based on big data are proposed,focusing on areas such as risk control and cost optimization.By constructing a financial data analysis model,this study provides an in-depth analysis of relevant data,demonstrating the role of big data technology in improving financial management.Finally,through a case study,the effectiveness of big data applications in financial management is verified,and future development directions are discussed.展开更多
基金Supported by the Chongqing Medical University Program for Youth Innovation in Future Medicine,No.W0019Chongqing Municipal Education Commission’s 14th Five-Year Key Discipline Support Project,No.20240101 and No.20240102。
文摘BACKGROUND Return to work(RTW)serves as an indication for young and middle-aged colorectal cancer(CRC)survivors to resume their normal social lives.However,these survivors encounter significant challenges during their RTW process.Hence,scientific research is necessary to explore the barriers and facilitating factors of returning to work for young and middle-aged CRC survivors.AIM To examine the current RTW status among young and middle-aged CRC survivors and to analyze the impact of RTW self-efficacy(RTW-SE),fear of progression(FoP),eHealth literacy(eHL),family resilience(FR),and financial toxicity(FT)on their RTW outcomes.METHODS A cross-sectional investigation was adopted in this study.From September 2022 to February 2023,a total of 209 participants were recruited through a convenience sampling method from the gastrointestinal surgery department of a class A tertiary hospital in Chongqing.The investigation utilized a general information questionnaire alongside scales assessing RTW-SE,FoP,eHL,FR,and FT.To analyze the factors that influence RTW outcomes among young and middle-aged CRC survivors,Cox regression modeling and Kaplan-Meier survival analysis were used.RESULTS A total of 43.54%of the participants successfully returned to work,with an average RTW time of 100 days.Cox regression univariate analysis revealed that RTW-SE,FoP,eHL,FR,and FT were significantly different between the non-RTW and RTW groups(P<0.05).Furthermore,Cox regression multivariate analysis identified per capita family monthly income,job type,RTW-SE,and FR as independent influencing factors for RTW(P<0.05).CONCLUSION The RTW rate requires further improvement.Elevated levels of RTW-SE and FR were found to significantly increase RTW among young and middle-aged CRC survivors.Health professionals should focus on modifiable factors,such as RTW-SE and FR,to design targeted RTW support programs,thereby facilitating their timely reintegration into mainstream society.
文摘The feed industry serves as a critical intermediary between agriculture and animal husbandry,providing essential support for the modern breeding industry.Utilizing the annual financial report data from 19 publicly listed companies within the feed industry in 2023,a comprehensive evaluation index system was developed to assess the financial performance of these companies from four dimensions:debt paying ability,operational ability,profitability,and development ability.Factor analysis and hierarchical cluster analysis were employed to assess the financial performance of publicly listed companies within the feed industry.By comparing the mean classifications and comprehensive scores,this study analyzed the strengths and weaknesses of these listed feed companies.Ultimately,it offered recommendations for improvement in areas such as product optimization and enhancement,reasonable liability management,and the advancement of company governance practices.
文摘As a key sector in advancing China’s“carbon neutrality”goal,the machinery manufacturing industry has achieved remarkable development in recent years.Against this backdrop,the scientific and objective evaluation of the financial performance of machinery manufacturing enterprises has become a pressing issue in financial research.This topic is not only crucial for optimizing enterprise management and improving operational efficiency but also essential for enhancing overall industry performance and promoting sustainable development.This paper first introduces the concept of financial performance,followed by an analysis of related financial performance evaluation theories.It then focuses on the application of the entropy method in evaluating the financial performance of machinery manufacturing enterprises,detailing its analytical steps.Finally,a financial performance evaluation index system is constructed based on four dimensions:profitability,solvency,operational efficiency,and growth potential.
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Research on Enterprise Finance Integration Based on Financial Sharing Model,2022 Jiangsu Province Philosophy and Social Science Project(Project No.2022SJYB1560)Research on Transformation of Applied Undergraduate Accounting Talent Training Model in the Digital Era,2022 School Education Reform Project(Project No.SJY20230119)。
文摘This article elaborates on the necessity of promoting the integration of business and finance based on financial sharing,analyzes the measures and effects of implementing business and finance integration in enterprises,points out the existing problems,and proposes strategies to optimize the integration from three aspects:building big data platforms,improving talent training plans,and improving financial shared information management platforms.
文摘Preventing financial risk is an important topic that academic circles and the government have paid attention to for a long time.The development of fintech and the improvement of financial regulation will affect the level of financial risk.The relationship between the degree of matching between fintech and financial regulation and financial risk is explored,which is crucial for reducing financial risk.Panel data from 31 provinces in China from 2011 to 2020 is used to explore the impact of fintech and financial regulatory matching levels on financial risk.The study finds that the improved matching level between fintech and financial regulation helps reduce financial risk.The degree of matching between fintech and financial regulation affects financial risk through financial efficiency.
文摘This paper examines the financial risk evaluation system in the context of the“Great Intelligence Movement Cloud”and employs the hierarchical analysis method as the primary research tool.With the rapid advancement of“Great Intelligence Movement Cloud”technology,enterprise financial risks have expanded from the offline domain to the information domain,encompassing a broader scope and more diverse channels.The traditional approach to risk identification,relying solely on single financial indicators,no longer meets current demands.Therefore,it is essential to integrate a non-financial early warning indicator system and adopt a combination of quantitative and qualitative analysis methods.Hierarchical analysis enables the decomposition of complex problems into multiple components and organizes them into a hierarchical structure based on their relationships,facilitating a more accurate assessment of financial risk.This study seeks to establish a comprehensive financial risk evaluation system suited to the“Great Intelligence Movement Cloud”context,offering enterprises more precise risk assessments to better address financial risks and achieve steady development.
文摘The rapid pace of economic globalization has presented both unprecedented opportunities and challenges for the construction industry.Management accounting and financial accounting,as integral components of enterprise management,play indispensable roles in the development of construction companies.While both disciplines possess distinct characteristics,the evolving business landscape necessitates a more integrated approach.By combining the strengths and values of both,construction companies can gain valuable insights and make informed decisions.This paper delves into the concepts of management accounting and financial accounting,explores the feasibility of their integration within construction companies,and provides recommendations for implementation to foster sustainable development.The insights and strategies presented in this paper can serve as a valuable reference for other construction companies seeking to optimize their management and operations.
文摘The dynamic analysis of financial systems is a developing field that combines mathematics and economics to understand and explain fluctuations in financial markets.This paper introduces a new three-dimensional(3D)fractional financial map and we dissect its nonlinear dynamics system under commensurate and incommensurate orders.As such,we evaluate when the equilibrium points are stable or unstable at various fractional orders.We use many numerical methods,phase plots in 2D and 3D projections,bifurcation diagrams and the maximum Lyapunov exponent.These techniques reveal that financial maps exhibit chaotic attractor behavior.This study is grounded on the Caputo-like discrete operator,which is specifically influenced by the variance of the commensurate and incommensurate orders.Furthermore,we confirm the presence and measure the complexity of chaos in financial maps by the 0-1 test and the approximate entropy algorithm.Additionally,we offer nonlinear-type controllers to stabilize the fractional financial map.The numerical results of this study are obtained using MATLAB.
文摘The increasing data pool in finance sectors forces machine learning(ML)to step into new complications.Banking data has significant financial implications and is confidential.Combining users data from several organizations for various banking services may result in various intrusions and privacy leakages.As a result,this study employs federated learning(FL)using a flower paradigm to preserve each organization’s privacy while collaborating to build a robust shared global model.However,diverse data distributions in the collaborative training process might result in inadequate model learning and a lack of privacy.To address this issue,the present paper proposes the imple-mentation of Federated Averaging(FedAvg)and Federated Proximal(FedProx)methods in the flower framework,which take advantage of the data locality while training and guaranteeing global convergence.Resultantly improves the privacy of the local models.This analysis used the credit card and Canadian Institute for Cybersecurity Intrusion Detection Evaluation(CICIDS)datasets.Precision,recall,and accuracy as performance indicators to show the efficacy of the proposed strategy using FedAvg and FedProx.The experimental findings suggest that the proposed approach helps to safely use banking data from diverse sources to enhance customer banking services by obtaining accuracy of 99.55%and 83.72%for FedAvg and 99.57%,and 84.63%for FedProx.
基金This project was funded by Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah underGrant No.(IFPIP-1127-611-1443)the authors,therefore,acknowledge with thanks DSR technical and financial support.
文摘In the rapidly evolving landscape of today’s digital economy,Financial Technology(Fintech)emerges as a trans-formative force,propelled by the dynamic synergy between Artificial Intelligence(AI)and Algorithmic Trading.Our in-depth investigation delves into the intricacies of merging Multi-Agent Reinforcement Learning(MARL)and Explainable AI(XAI)within Fintech,aiming to refine Algorithmic Trading strategies.Through meticulous examination,we uncover the nuanced interactions of AI-driven agents as they collaborate and compete within the financial realm,employing sophisticated deep learning techniques to enhance the clarity and adaptability of trading decisions.These AI-infused Fintech platforms harness collective intelligence to unearth trends,mitigate risks,and provide tailored financial guidance,fostering benefits for individuals and enterprises navigating the digital landscape.Our research holds the potential to revolutionize finance,opening doors to fresh avenues for investment and asset management in the digital age.Additionally,our statistical evaluation yields encouraging results,with metrics such as Accuracy=0.85,Precision=0.88,and F1 Score=0.86,reaffirming the efficacy of our approach within Fintech and emphasizing its reliability and innovative prowess.
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This study is funded by National Social Science Fund Major Project:“Research on Stimulating Innovation Vitality of Scientific and Technological Talent in the Context of Building a Talent Powerhouse”(21ZDA014)Research Start-Up Fund for Talent Recruitment of Sichuan Academy of Social Sciences:“Research on the Deep Integration of Sichuan’s Digital Economy and Real Economy to Support the Construction of a Modern Industrial System”(23RYJ03).
文摘As a novel economic form,the digital economy is reshaping the financial regulatory landscape and significantly impacting regulatory costs.This paper incorporates the digital economy and financial regulatory costs into the classic Solow growth model,uncovering an inverted U-shaped relationship between them.A subsequent mechanism analysis explains the rationale behind this relationship.To empirically examine this relationship in China,the paper utilizes inter-provincial panel data from 2013 to 2021 and employs methodologies such as the two-way fixed effects and moderating effects models.These analyses have important implications for the sound and sustainable development of China’s financial industry.The findings indicate:(a)As China’s digital economy develops,its impact on financial regulatory costs follows an inverted U-shaped pattern,initially increasing and then declining.This conclusion remains valid after robustness tests.(b)The influence of the digital economy on regulatory costs depends on favorable external conditions.Specifically,the impact is more pronounced in regions and periods with better digital infrastructure and more abundant human capital.(c)Additionally,redundant resources moderate this impact,which can weaken the inverted U-shaped relationship.Our findings not only provide a theoretical foundation for understanding the impact of the digital economy on financial regulatory costs but also offer valuable policy insights for optimizing financial regulation in China.
基金support was obtained from the Fundamental Research Funds for the Central Universities[Grant No.JBK2307090].
文摘With intensifying global climate change,humanity is confronted with unparalleled environmental challenges and risks.This study employs the staggered difference-in-difference model to examine the relationship between climate policy and green innovation in the corporate financialization context.Using Chinese-listed company data from 2008 to 2020,our analysis reveals a favorable correlation between China’s carbon emission trading policy(CCTP)and advancements in green innovation.Furthermore,we find that the level of corporate financialization moderates this correlation,diminishing the driving effect of CCTP on green innovation.Additionally,results of heterogeneity analysis show that this moderating consequence is more evident in non-state owned and low-digitization enterprises compared with state-owned and high-digitization ones.Our findings contribute to the existing literature by clarifying the interaction between CCTP,green innovation,and corporate financialization.Our research provides valuable insights for policymakers and stakeholders seeking to strengthen climate policies and encourages green innovation in different types of businesses.
文摘In 2022,the United States stepped up its sanctions on Russia.Most notably,it restricted the flow of the Russian Central Bank's foreign exchange(forex)assets,using financial administrative power as a source of strategic leverage.This move should have reduced the appeal of US dollar assets but in reality has not accelerated as expected the decline of the greenback as a store of value.The US dollar's share of global forex reserves increased instead of decreased during 2022 and 2023.Despite the rise of economic costs caused by tightened US financial sanctions,countries that recognize the geopolitical role of the United States have further accepted the dollar's international status;their continued willingness to live with the dollar's“security premium”has given a fillip to the US dollar in the short term,boosting its appeal as a reserve currency.Meanwhile,de-dollarization of forex reserves has yet to reach a sufficient scale,thus falling short of significantly challenging the dollar's reign.From a longer-term perspective,as economic and security conditions shift,countries that accept the dollar's international role or seek de-dollarization may change their choices.As a result,four possible scenarios may arise:(i)the preeminence of the US dollar remains unthreatened;(ii)the international monetary system splits into blocs;(iii)the international monetary system fragments;and(iv)the dollar loses its throne.The author believes that the last scenario is the most likely outcome.
基金partially funded by Goverment of Spain,Ministry of Science,Innovation and Universities(grant:RTI2018093366-B-I00)by Goverment of Spain,Ministry of Universities(grant:Subsidies to Public Universities for the Requalification of the Spanish University System,“Margarita Salas”Grants Modality for the Training of Young Doctors,RD 289/2021 of April 20)+1 种基金by the Xunta de Galicia,Consellería de Educacion e Ordenación Universitaria(grant:#ED431C 2018/41)by the Group of Numerical Methods in Engineering of the Universidade de A Coruna。
文摘We present a new methodology to statistically determine the net present value(NPV)and internal rate of return(IRR)as financial estimators of shale gas investments.Our method allows us to forecast,in a fully probabilistic setting,financial performance risk and to understand the importance of the different factors that impact investment.The methodology developed in this study combines,through Monte Carlo simulation,the computational modeling of gas production from shale gas wells with a stochastic simulation of gas price as a geometric Brownian motion(GMB).To illustrate the methodology's validity,we apply it to an analysis of investments in shale gas wells.Our results show that gas price volatility is a key variable in the performance of an investment of this type,in such a way that at high volatilities,the potential return on an investment in shale gas increases significantly,but so do the risks of economic loss.This finding is consistent with the history of shale gas operations in which huge investment successes coexist with unexpected investment failures.
文摘There is a broad connection between finance and human rights,with finance having both positive and negative impacts on human rights.Everyone has a need for access to financial services.Documents in both the international human rights and international finance fields address the relationship between financial services and human rights.Among financial services,microcredit and inclusive finance have the closest connection to human rights and potentially the greatest impact on human rights.Access to financial services promotes economic,social,and cultural rights as well as the rights of specific groups.The conditions for access to financial services to promote human rights require the state to assume obligations to recognize,respect,protect,and fulfill the need for individuals to access financial services,and to ensure the availability,accessibility,acceptability,and adaptability of basic financial services.Access to financial services has played a significant role in China’s comprehensive victory in the battle of poverty alleviation,providing valuable experience for the international community in poverty eradication,achieving sustainable development goals,and protecting and promoting human rights.
文摘The study focuses on assessing the financial management practices and accounting mechanisms in agricultural cooperatives in Tulsipur Sub-Metropolitan,Dang District,Nepal with a focus on understanding their implications for financial performance and organizational effectiveness.The sample size of total cooperatives(n=46)was divided into Savings and Credit Cooperatives(n=18)and Multipurpose Cooperatives(n=28),respectively,with a total number of respondents(n=138)categorized into managing directors,employees,and general members.Using a mixed-methods approach that combines quantitative analysis of financial data with qualitative insights gathered through interviews and surveys,the study emphasizes the importance of modern financial practices,improved reporting mechanisms,and relevant staff training for long-term sustainability.Recommendations include the integration of criteria and evaluation tools to assess cooperative performance,with Hamro Pahunch Multipurpose Cooperative identified as a high performer.Emphasizing the need for robust financial management strategies to navigate the complexity of the agricultural sector,manage risks,and achieve sustainable development,the study notes frequent preparation of financial management reports on a monthly and annual basis,and predominantly annual accounting management.Most cooperatives are using computerized models to present financial positions,but face challenges such as lack of marketing infrastructure,cooperative skills,and technical support.Ultimately,the study advocates for educating policy makers,cooperative leaders,practitioners and stakeholders on the role of effective financial management and accounting in enhancing the resilience,expansion and socio-economic impact of agricultural cooperatives,thereby fostering their long-term prosperity and viability as drivers of rural development and empowerment.
基金the research result of“Financial Accounting”(Project No.HKSZ2024-10)supported by the Ideological and Political Demonstration Project of Hainan Vocational University of Science and Technology.
文摘From the perspective of the digital economy,enterprise financial management is facing unprecedented challenges and opportunities.Traditional financial management models are no longer suited to current development needs.Fine-tuning financial management is essential to support the modernization of enterprises,guard against operational risks,and promote coordination across the entire value chain for greater economic efficiency.With the help of digital technology,data-driven,highly interconnected,and intelligent decision-making processes are becoming more prominent,profoundly transforming the operational and financial management models of enterprises.This enables financial management to keep pace with modern developments.In light of this,the paper explores the connotations and mechanisms of the digital economy and enterprise financial management,clarifies relevant conceptual characteristics,and identifies problems in financial management under the digital economy.It also offers strategies for optimization and problem-solving,with the aim of providing valuable insights for educators and practitioners.
文摘In the context of the rapid development of big data technology,the financial management model of Internet financial enterprises is undergoing a profound transformation.This paper analyzes the key aspects of applying big data technology in Internet finance,including its basic concepts,characteristics,and current state of development in the field.It examines the current situation and primary challenges faced by financial management in Internet financial enterprises,such as risk management,cost control,and data integration.To address these challenges,optimization strategies based on big data are proposed,focusing on areas such as risk control and cost optimization.By constructing a financial data analysis model,this study provides an in-depth analysis of relevant data,demonstrating the role of big data technology in improving financial management.Finally,through a case study,the effectiveness of big data applications in financial management is verified,and future development directions are discussed.
