On fractional discrete financial system:Bifurcation,chaos,and control

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.

2P3FL:A Novel Approach for Privacy Preserving in Financial Sectors Using Flower Federated Learning

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.

Unleashing the Power of Multi-Agent Reinforcement Learning for Algorithmic Trading in the Digital Financial Frontier and Enterprise Information Systems

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.

The Impact of the Digital Economy on Financial Regulatory Costs: An Empirical Analysis Based on the Solow Growth Model

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.

Deep Learning for Financial Time Series Prediction:A State-of-the-Art Review of Standalone and HybridModels

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.

Moderating effect of corporate financialization on the impact of climate policy on corporate green innovation:Evidence from China

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.

Impact of US Financial Sanctions on the Dollar's International Status

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.

Assessing Financial Management Practices and Accounting Mechanisms in Agricultural Cooperatives:A Case Study From Nepal

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.

Access to Financial Services——An Analysis from the Human Rights Perspective

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.

Research on Enterprise Finance Integration Model Based on Financial Sharing

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.

Research on the Optimization of Enterprise Financial Management under the Financial Sharing Model

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.

The Impact of“Fintech+Financial Regulation”Matching Level on Financial Risk:Evidence from China

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.

Empirical Analysis of the ESG and Financial Performance:Evidence from Chinese Technology Enterprises

To date,the concept of sustainable development has gained global attention from companies and investors.One important reason for this is the increasing interest of investors in incorporating environmental,social,and governance(ESG)elements into their investments.The purpose of this dissertation is to analyze the correlation between ESG factor performance and corporate financial performance in Chinese technology enterprises.Additionally,the study focuses on Internet and medical technology companies to ensure relevance.The findings of the study provide guidance on ESG investment and sustainability for both companies and individual investors.

Regulatory Issues and Countermeasures in International Financial Markets

With the deepening of globalization,the development speed of capital markets is constantly accelerating,presenting a trend of globalization.At the same time,the emergence of multiple forms of trading platforms and diversified financial products further highlights the competitive relationship between security exchanges and other trading platforms.While promoting the transformation of security exchange forms in various countries,it also prompts governments to re-examine the financial regulatory system of securities markets.In this situation,it is very important to research the international financial market and financial regulatory system.This article explores the regulatory issues and countermeasures in the international financial market,intending to promote the stability and healthy development of the international financial market.

Exploration of Financial Management Curriculum Reform in Vocational College

As the core course of finance and accounting major,the study of financial management knowledge plays a positive role in promoting students’understanding of the whole financial work and enriching financial knowledge.This paper analyzes the necessity of financial management curriculum reform,from the design ideas,teaching content,teaching mode,and teaching methods of several aspects of vocational college financial management curriculum reform work carried on the preliminary thinking,hoping to improve the teaching quality of this course will be helpful.

The Problems and Solutions of Enterprise Financial Management in the Perspective of Digital Economy

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.

Research on the Path of Transition from Financial Accounting to Management Accounting Under the Background of Big Data

Driven by the wave of big data,the traditional financial accounting model faces an urgent need for transformation,as it struggles to adapt to the complex requirements of modern enterprise management.This paper aims to explore the feasible path for transitioning enterprise financial accounting to management accounting in the context of big data.It first analyzes the limitations of financial accounting in the era of big data,then highlights the necessity of transitioning to management accounting.Following this,the paper outlines the various challenges that may arise during this transition and,based on the analysis,proposes a series of corresponding transition strategies.These strategies aim to provide theoretical support and practical guidance for enterprises seeking a smooth transition from financial accounting to management accounting.

Does Financial Globalization Discipline Macroeconomic Policies

Using the unbalanced panel data of 160 countries from 1970 to 2007,we employ inflation and the budget deficit as proxies for monetary policy and fiscal policy,respectively,and study whether financial globalization has discipline effects on these macroeconomic policies.The empirical results in our study suggest a significant discipline effect of financial globalization on monetary policy during the entire sample period,which is robust both to de jure and to de facto measures of financial openness.Our sub-sample investigations demonstrate that financial globalization reduces inflation only in higher-middle-income and high-income countries,and when financial globalization is scaled by the proportion of a country’s foreign assets and liabilities to its GDP,the discipline is evident only after 1988.Nevertheless,we do not demonstrate any evidence of financial globalization’s discipline effect on fiscal policy.The empirical results indicate that financial globalization even increases the budget deficit in certain countries and periods.

Digital Transformation and Corporate Financial Risk:Evidence from Listed Companies in

As a core issue in enterprise operation management,corporate financial risk is directly related to the survival and development of enterprises,and digital transformation has brought new challenges to the control of corporate financial risk.Based on the data of The Shanghai Stock Exchange(SSE)and Shenzhen Stock Exchange(SZSE)from 2009 to 2022,this paper analyzes the impact of digital transformation on corporate financial risk and the impact mechanism.The empirical study finds that digital transformation significantly increases the financial risk of enterprises,and shows differences among different regions,different risk factors,and enterprise natures,and substantially increases the corporate financial risk in the East and West,non-state-owned enterprises,high-risk and low-risk enterprises.The mechanism analysis found that digital transformation would affect the financial risk of enterprises by increasing their R&D investment and reducing their debt level.The conclusion improves insights and guidance for analyzing and managing financial risks in enterprises under digital transformation.

Exploring the Application of Refined Management in University Financial Management

The refined management of university finances primarily involves optimizing management methods and continuously improving financial management levels.This process helps enhance fund utilization efficiency,optimize resource allocation,ensure the rational use of educational funds,and provide solid financial support for the development of teaching,research,and other university undertakings.This paper explores the application of refined management in university financial management.