The article addresses the inefficiencies in the mechanisms for forecasting cash flows and managing liquidity in local budget boiler accounts, necessitating a revision of liquidity management practices. Financial decentralization has posed numerous challenges for local financial authorities, including the need to maintain sufficient cash balances in local budget accounts to ensure financing and payment of obligations with minimal costs. Effective management of cash reserves and forecasting the revenue base of local budgets are also critical. The authors emphasize the importance of applying modern forecasting methods, such as machine learning and neural networks, which enable faster and more accurate financial data analysis and forecasting. Special attention is given to data preprocessing and automation, algorithm selection, model training, and performance evaluation. The article also examines the liquidity management concept developed by the Ministry of Finance of Ukraine for 2020-2023 and its impact on improving public finance management practices. This article underscores the need to implement effective forecasting and liquidity management methods to ensure the stability and efficiency of the financial system at both local and state levels.
Maryna Sadovenko, Olga Kondratyuk, Nataliia Suprun, Maxim Tarverdiev
In today's digital age, technical engineering plays an important role in using artificial intelligence and cryptocurrency to optimize tax systems and improve financial efficiency in fintech businesses. Artificial intelligence helps automate business processes, especially in taxation, which reduces the cost of tax administration. Cryptocurrencies open up new opportunities for optimizing tax systems, providing greater transparency and efficiency in financial transactions.. The use of AI in tax administration can streamline processes, reduce human error, and improve compliance. AI algorithms can analyze large amounts of data, identify patterns, and detect potential tax evasion or fraud, leading to more accurate tax assessments and improved revenue collection. Additionally, AI-powered chatbots and virtual assistants can provide taxpayers with personalized support and guidance, enhancing the overall experience. Cryptocurrencies, on the other hand, offer a transparent and secure way to conduct financial transactions. By leveraging blockchain technology, cryptocurrencies enable immutable and auditable records of transactions, which can facilitate tax reporting and compliance. Furthermore, the decentralized nature of cryptocurrencies eliminates the need for intermediaries, reducing transaction costs and increasing efficiency. However, the implementation of these technologies in tax systems requires significant investments in infrastructure, software, and personnel training. Tax authorities ought to allocate substantial budgets to modernize their systems and integrate AI and blockchain solutions seamlessly. Additionally, concerns over data privacy and the potential for cyber threats pose challenges in ensuring the confidentiality and security of taxpayer information.
Open access
Impact of AI and Big Data on Business and Society
Digitalization and Economic Development in Agriculture
With the degradation of the environment due to increasing ecological destruction and pollution, sustainable development has become the paramount objective of social progress. As a result, the concept of green development has garnered considerable attention, which is an important starting point for China to achieve stable economic development and sustainable ecological development. To achieve high-quality economic progress while advancing environmentally friendly practices, it is imperative to formulate and uphold a sound green credit system. However, the phenomenon of greenwashing by enterprises still exists, which compromises the efficacy of green credit and hinders the long-term sustainable and well-organized progress of green finance. Building on the background of green credit, considering the existence of blockchain and government subsidies and adopting the method of tripartite evolutionary game, this paper examines the strategic decisions made by the government, financial institutions, and small and medium-sized enterprises in the context of greenwashing. An emphasis is placed on the impact of blockchain technology on the three parties involved in the green credit market. The findings demonstrate that blockchain technology can diminish the likelihood of greenwashing by businesses and enhance the impact of government subsidies. However, it cannot replace the regulatory authority of the government in sustainable development. Moreover, excessive subsidies can stimulate more greenwashing practices, but eliminating subsidies does not eradicate the root of greenwashing. To encourage sustainable economic development and minimize corporate defaults, the government ought to reinforce supervision and establish a robust social surveillance and publicity mechanism. This paper broadens the research perspective on the effectiveness of green credit and provides some empirical and theoretical references for further promoting the green transformation of SMEs and the sustainable development of the ecological environment.
Nidal Zaqeeba, Hamza Alqudah, Badi Salem Rawashdeh, Abdalwali Lutfi · 6 authors
The objective of the present study is to measure the impact of blockchain technology on financial reports. The study utilizes a time series analysis covering eleven commercial banks listed on the Amman Stock Exchange from 2009 to 2019. Two key measures, namely other operating expenses and customer deposits are employed in the Return on Assets (ROA). The findings indicate that blockchain technology can be quantified by 0.038 of other operating expenses. However, there are no discernible indications of measuring blockchain technology through customer deposits. The study suggests that blockchain technology is a double-edged sword; when not utilized as required, it leads to increased expenses, and conversely, its effective exploitation can have cost-reducing effects. In other words, operational inefficiencies or heterogeneity are associated with elevated costs associated with implementing blockchain technology. Doi: 10.28991/HIJ-2024-05-02-014 Full Text: PDF
‘Sustainable Finance’ refers to the process of taking environmental, social, and ‘Blockchain Technology (BCT) is a decentralized and distributed ledger system that enables secure and transparent recording of transactions across a network of computers. It has immense potential to revolutionize sustainable finance reporting. By leveraging BCT’s inherent transparency, immutability, and decentralized nature, organizations can enhance trust and accountability in reporting practices related to sustainability initiatives. The ever growing importance of ‘Sustainable Finance’ and the need for transparent reporting in this field need not be exaggerated. Of late, BCT has emerged as a disruptive force in improving transparency and accountability. Traditional Reporting practices face several challenges in today's dynamic business environment. Addressing these challenges requires organizations to embrace innovation and adopt modern reporting practices that prioritize timeliness, transparency, relevance, and stakeholder engagement. This may involve leveraging advanced analytics, automation technologies, integrated reporting frameworks, and interactive data visualization tools to enhance the quality, accessibility, and usability of reporting processes and outputs. Sustainable Finance Reporting (SFR) plays a crucial role in promoting transparency, accountability, and responsible investment practices within the financial sector. It is essential for promoting responsible investment, managing risks, enhancing transparency, and driving long-term value creation in the financial sector. By integrating sustainability into their reporting practices, financial institutions can contribute to a more sustainable and resilient global economy. Adopting BT offers numerous benefits and opportunities across various industries. BCT Framework provides a robust and innovative platform for building decentralized applications, facilitating secure and transparent transactions, and transforming various industries and sectors. This comprehensive Concept Paper provides an overview of BTS’s Framework, challenges involved in traditional reporting systems and SFR, the potential and promise of BCT, its benefits and opportunities, and practical applications.
The advent of smart cities has paved the way for transformative advancements in healthcare, particularly in the domain of disease diagnosis. In the wake of the COVID-19 pandemic, accurate and timely identification of Pandemic diseases has become paramount. This paper explores the challenges and opportunities in synergizing Artificial Intelligence (AI), Internet of Things (IoT), and Blockchain technologies for diagnosis of Pandemic diseases in smart cities. This study provides an overview of each technology and its relevance to sustainable healthcare in smart cities, emphasizing its potential for analyzing medical data and making informed decisions. We also explore how IoT devices can contribute to disease surveillance, enabling real-time data collection and remote healthcare. Additionally, we discuss the potential of Blockchain in ensuring secure and transparent healthcare systems. Following, the paper study the synergistic potential of integrating AI, IoT, and blockchain, emphasizing how their combined strengths can enhance the accuracy, efficiency, and security of COVID-19 diagnosis systems in smart cities Moreover, the paper highlights the challenges in integrating these technologies and the opportunities for research and implementation, underlining the significance of synergizing AI, IoT, and Blockchain in disease diagnosis in smart cities. The findings demonstrate that the convergence of AI, IoT, and blockchain can enhance the speed and accuracy of diagnosing Pandemic diseases, leading to more effective containment and management strategies.
Innovation has profoundly transformed the finance industry, improving efficiency, transparency, and accessibility through technologies like electronic banking, blockchain, and Artificial Intelligence (AI). This research explores the future of finance, emphasizing the pivotal role of AI and other emerging technologies in redefining financial practices, creating new opportunities, and addressing challenges. The study synthesizes findings from academic journals, industry reports, and case studies, employing a mixed-methods approach that includes quantitative analysis of adoption rates and qualitative interviews with industry experts. Key advancements, such as the rise of algorithmic trading and the introduction of Decentralized Finance (DeFi) platforms, highlight the deep intertwining of finance and technology. The anticipated outcomes include identifying key innovations, the potential for AI to enhance efficiency and personalize services, and the strategies needed to address emerging challenges like regulatory hurdles and ethical concerns. The findings are designed to provide valuable insights for policymakers, industry leaders, and academics to facilitate informed decision-making and foster innovation while ensuring ethical and regulatory compliance
This paper presents an innovative application of blockchain technology utilizing smart contracts to offer crop recommendations tailored to the agricultural community.Leveraging Ethereum's solidity language, we developed a decentralized system enabling farmers to access real-time data on crop selections made by their peers.The system aggregates information on crop preferences and land allocations, facilitating informed decision-making for individual farmers.Our implementation ensures data integrity and transparency, crucial for fostering trust among users.Through empirical evaluation, we demonstrate the efficacy of our approach in providing accurate and timely crop recommendations, thereby enhancing agricultural productivity and sustainability.Our findings highlight the potential of blockchain technology to revolutionize traditional agricultural practices by fostering collaboration and data-driven decision-making.We conclude by discussing future avenues for research and adoption, emphasizing the scalability and accessibility of our proposed solution in addressing broader agricultural challenges.
This study aims to investigate the influence of blockchain and artificial intelligence on the audit quality of firms from Turkey. Primary data from 300 respondents are collected through random sampling to attain the study's objectives. PLS-SEM is used to investigate the relationship between exogenous and endogenous variables. Our findings show that blockchain technologies and artificial intelligence (AI) utilization in their financial system positively impact audit quality by assisting in the audit process and the detection of fraud, which also improves financial reporting. Blockchain and Artificial Intelligence in the financial system create confidence for investors, stakeholders, and legislators. Moreover, this study advocated significant implications for investors, government, firms, and policymakers. Investors can make investment decisions based on the accuracy of the financial accounts; the government and policymakers can improve the governance mechanism by using the study's findings.
Syed Ali Asif, Emma Cao, Hang Chen, Chien-Chung Shen · 5 authors
The Metaverse, an immersive virtual world, has emerged as a shared space where people engage in various activities ranging from social interactions to commerce. Cryptocurrencies [3] and Non-Fungible Tokens (NFTs) [6] play pivotal roles within this virtual realm, reshaping interactions and transactions. Cryptocurrencies, utilizing cryptographic techniques for security, enable decentralized and secure transactions, and NFTs represent ownership or proof of authenticity of unique digital assets through the blockchain technology. While NFTs and cryptocurrencies offer innovative opportunities for ownership, trading, and monetization within the metaverse, their use also introduces potential risks and negative consequences, such as financial scams and fraud, highlighting the need for users to exercise caution and diligence in their virtual transactions.
Unlabelled: The convergence of artificial intelligence (AI), blockchain technology, and health care represents one of the most transformative yet technically challenging frontiers in computational medicine. As health care systems adopt data-driven paradigms for precision medicine and clinical decision support, the need for secure, privacy-preserving, and collaborative learning frameworks has become critical. This tutorial introduces a comprehensive, clinically oriented, and compliance-aware framework integrating federated learning (FL) and blockchain for secure and privacy-preserving health care analytics. FL enables collaborative training across distributed institutions without raw data sharing, in alignment with privacy regulations such as the Health Insurance Portability and Accountability Act (HIPAA) and the General Data Protection Regulation (GDPR). However, FL remains vulnerable to model poisoning and gradient leakage. To address these risks, we introduce blockchain-based FL (BCFL), which leverages blockchain's immutable ledger and decentralized consensus to enhance trust, verifiability, and auditability. The tutorial's main contributions include (1) a taxonomy of diverse medical data types and their FL requirements; (2) three integration architectures (fully coupled, semicoupled, and loosely coupled) analyzed for security, scalability, and regulatory compliance; (3) a security analysis of health care-specific vulnerabilities and mitigation strategies using advanced cryptography, such as zero-knowledge proofs, homomorphic encryption, and differential privacy; and (4) a regulatory compliance framework addressing HIPAA, GDPR, and United States Food and Drug Administration guidelines for AI-enabled medical devices. We demonstrate BCFL's relevance across major health care applications, including disease prediction, medical imaging, patient monitoring, and drug discovery, and highlight emerging research directions such as quantum-resilient cryptography, scalable interoperability, and automated compliance. This tutorial serves as a foundational resource for advancing secure, compliant, and collaborative AI in health care; fostering privacy-preserving analytics; and improving patient outcomes.
Purpose: This article clarifies the factors influencing individual investors' Bitcoin investments in the Vietnamese stock market. Design/methodology/approach: We employed the Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM), a comprehensive survey with 300 responses, and quantitative analysis using SmartPLS from December 2022 to March 2023. Findings: The findings reveal that the perceived usefulness of the Bitcoin market, subjective norms, self-efficacy, and herd behavior positively impact the Bitcoin investment decisions of individual investors in Vietnam. Research, Practical & Social Implications: This study provides regulators and relevant agencies with more practical evidence regarding the Bitcoin market, facilitating the formulation of appropriate management policies in an emerging economy. Originality/value: There is a shortage of research on the Bitcoin cryptocurrency investment market from the perspective of individual investors in emerging countries like Vietnam. Therefore, this study tries to shed light on individual investors with a comprehensive and objective overview to consider before making investment decisions. Additionally, the results can offer managers and relevant agencies empirical evidence to promulgate future regulations on the Bitcoin market.
Abstract This research focuses on investigating the impact of cryptocurrency accounting reports on company value (measured by financial performance) before and during the COVID 19 epidemic. Analyzing publicly listed companies’ data in firms’ 10-K filings, we find that there is no significant relation with the company’s profits while a company holds cryptocurrency positions. Although the issue of cryptocurrency accounting is an emerging topic, prior literature is mostly focused on cryptocurrency investment and is a rare investigation coping with the accounting treatment of crypto-assets. This paper seeks to contribute to the knowledge of fresh issues surrounding the accounting practices and standards tied to cryptocurrency for the company’s holding of crypto-assets. Taken together, the observed findings obtained from the test of the second hypothesis show that there is no significant relationship with the company’s stock returns while a company holds cryptocurrency positions. This result can be interpreted to determine whether the general investors take a more positive or negative attitude towards companies involved in cryptocurrency holding. Crucially, research findings unveil that cryptocurrency holdings have a significant impact on a company's liabilities. Our empirical evidence could be beneficial to public authorities and firms in decision- making situations related to cryptocurrency holdings of companies. JEL classification numbers: G10, G18, M14, M41. Keywords: Cryptocurrency accounting reports, Crypto-asset holdings, Firm value.
People are starting to see the cryptocurrency market as a viable source of income and investment, similar to the stock market, as the concept of cryptocurrencies continues to gain popularity. Predicting Bitcoin returns is related to financial machine learning, which uses time series to forecast price variance. This study starts with the daily close price of Bitcoin for its initial dataset. The price is transformed into percentages and binary classes, which categorize into “Up” and “Down”, after which a time series is applied to produce two datasets: a categorical dataset for classification and a numerical dataset for regression. For classification that represents a Binary classification in asset-price forecasting, k-fold cross-validation is applied to ensure that the best classifiers are selected for testing and analysis. Most of the regression analysis was based on visualization, which displayed the predicted prices by each regressor in front of the original values and helped analyse the models’ results more accurately. The outcomes of this study were achieved by anticipating bitcoin returns using classification and regression machine learning models, despite the approaches’ low accuracy and significant precision rate to the “Up” class. At this stage, with a significant limitation regarding the dataset and a lack of other indicators, a model capable of predicting future variations is considered a beneficial addition for many trading tools or even for crypto market analysts.
Ahmad AL-Hawamleh, Marwan Altarawneh, Heba Mousa Mousa Hikal, Alya Elfedawy
This research focuses on the metaverse's evolving trend and the potential application of blockchain technology in the accounting of virtual assets in this digital domain.The metaverse introduces a new economy in which users may earn real-world revenue through virtual activities, necessitating the need for efficient and dependable virtual asset accounting.Blockchain technology, with its decentralized and immutable record, appears to be a viable answer to these problems.This paper discusses the present status of blockchain technology for accounting for virtual assets in the metaverse as well as its potential role for businesses and the economy.It also determines the technology's issues and limits and makes recommendations for further development.The approach of this study is based on a comprehensive review of the existing literature on the interactions between blockchain technology, virtual asset accounting, and the metaverse.The findings indicate that blockchain technology has the potential to transform virtual asset accounting in the metaverse by improving security, transparency, and consistency.However, scalability and legal/regulatory issues must be overcome before it can completely achieve its promise.Accounting experts, developers, and stakeholders interested in the convergence of blockchain technology and the metaverse economy will find this paper useful.
Emilyani, Marviola Hardini, Natasya Aprila Yusuf, Achani Rahmania Az Zahra
This research aims to explore the convergence between smart networks, artificial intelligence (AI), and blockchain technology as a foundation for future innovation. The background includes the rapid development of information and communications technology, which is driving increasing integration between AI and blockchain in infrastructure networks. The methods used include a comprehensive literature survey and in-depth analysis of the latest trends in the development of this technology. The issues examined include interoperability, security, and privacy challenges faced in integrating AI and blockchain. The research results show that this convergence promises to improve efficiency, transparency and transparency in a variety of applications, from supply chain management to financial services. However, significant challenges such as scalability and regulation must also be overcome to realize the full potential of this convergence. In conclusion, the merger of AI and blockchain expands the scope of technological innovation by leveraging the strengths of each, but more efforts are needed to address further issues so that this convergence can be implemented widely and sustainably in various industrial fields.
Mohammad Vahidpour, Amir Daneshvar, Mohsen Amini Khouzani, Mahdi HOMAYOUNFAR
Financial markets are characterised by their dynamic, non-linear, and fluctuating nature. Analysing financial time series in these contexts is a complex and challenging task. Candlestick patterns are recognised as among the most widely used financial tools and offer invaluable insights into market sentiment and psychology. However, manual analysis of these patterns presents significant challenges. Therefore, leveraging machine learning methods becomes a necessity for overcoming these challenges. In this study, a four-step framework was introduced in which the data preparation process is executed on the price data of the 20 cryptocurrencies. Forty-eight candlestick patterns were extracted alongside returns. Employing the long shortterm memory (LSTM) neural network, structured with multiple layers, each specialising in a specific cryptocurrency, enables individualised prediction of market returns. Evaluation of model accuracy and sensitivity is conducted via the confusion matrix, and two distinct trading strategies assess the capital portfolio. The research findings underscore the profitability of the proposed model across all scenarios. Candlestick patterns serve as powerful tools for understanding market sentiments and identifying shifts in market trends. However, their standalone efficacy is limited. Integrating them with other technical analysis tools facilitates more informed decision-making and fosters a deeper understanding of market dynamics.
Blockchain is a decentralized network in which data blocks are linked.Through a decentralized peer-to-peer network, users can create shared databases, resulting in a trustworthy and aggregated database known as a blockchain that enhances reliability and security.The distributed nature of the blockchain enables data to be stored on multiple nodes, eliminating the need for a central server or platform.This disintermediation significantly reduces the transaction and administrative costs.The blockchain is particularly valuable in applications where reliability and stability are critical because it establishes an open database that ensures data integrity, making it virtually impossible to tamper with or falsify data.This study explores the diverse applications of the blockchain technology in virtual assets, such as cryptocurrency, decentralized finance, central bank digital currency, nonfungible tokens, and metaverses.In addition, it analyzes the potential prospects and developments driven by these innovative technologies.
The real estate industry is crucial sector of the world economy Buying and selling properties usually takes a long time, is complicated, and can be expensive.There's also a risk of mistakes and fraud, which might cause big financial losses and legal problems.This research paper delves into the innovative use of blockchain technology to address the pervasive issue of fraud within the real estate industry.By introducing a comprehensive system where user authentication is conducted through Aadhaar numbers, properties are represented as Non-Fungible Tokens (NFTs), and transactions involve the crucial oversight of designated inspectors, this paper aims to provide a robust framework for fraud prevention.Additionally, it explores how blockchain's inherent properties prevent instances of double selling, thus bolstering the integrity of real estate transactions.The research demonstrates the effective utilization of blockchain technology and Ethereum's smart contracts.The immutability nature of the blockchain ledger and transactions can provide a safe environment for the real estate sector.The project also identified some challenges and opportunities for blockchain adoption in the real estate industry.One of the challenges is the lack of awareness and understanding of blockchain technology.Another challenge is the regulatory environment, which is currently unclear.However, there are many opportunities for blockchain adoption in the real estate industry, such as streamlining the real estate transaction process, reducing fraud, and improving transparency.
Can Zhao, Yibing Wang, Dejun Wang, Guangyan Sun · 5 authors
The analysis on conformance between legal contracts and smart contracts is necessary and precondition for constructing the secure blockchain. Currently, the analysis method is the language-dependent single qualitative analysis. There does not exist quantitative metrics and quantitative analysis methods. Hence, the quantitative metric and language-independent quantitative analysis method are proposed to analyze the conformance between legal contract and smart contract. First, the definitions and metrics of partial conformance and complete conformance are proposed, and then rewrite logic and language-independent symbol execution are used to construct a language-independent quantitative method; then, the executable formal semantic for legal contract description language Business Process Model and Notation2.0 (BPMN2.0) is presented. Finally, the conformance of the five main methods for mapping BPMN2.0 legal contracts to Solidity smart contracts is analyzed. The results show that three methods have partial conformance, one method has complete conformance, and method has neither complete conformance nor partial conformance.
Virtual currencies, including cryptocurrencies and non-fungible tokens (NFT’s), are increasingly used as rewards in virtual environments. Traditional reward systems have been effective in improving employee satisfaction and retention but with the shift to hybrid or remote work post-COVID-19, organisations need adapted reward systems. However, the problem of this research is that it’s unclear how virtual currencies can be effectively utilised as a reward system, in the Metaverse, and their impact on employee motivation and engagement. This study explores this by reviewing literature, analysing reward mechanisms, and proposing a conceptual model to evaluate the feasibility of such a reward system. The study considers factors like social comparison and loss aversion as well as rewards known to boost motivation and engagement. The flexibility of virtual currencies for conversion or exchange into rewards offers numerous possibilities, with specific reward choices left to organisations’ discretion. This study offers promise to organisations seeking to retain and motivate their employees, ultimately contributing to increased productivity. In turn, employees can benefit from improved job satisfaction and reduced work-related pressures. The study’s conclusion assesses the usefulness of this research and outlines potential areas for future research.
Next Earth is a pioneering metaverse project that has rapidly evolved since its inception. Initially conceived as a virtual world platform, Next Earth has expanded its vision to become a multifaceted ecosystem that blends blockchain technology, virtual reality, and decentralized finance. The project aims to create a digital universe where users can buy, sell, and develop virtual real estate, participate in immersive experiences, and engage in a vibrant community. Next Earth's evolution has been marked by strategic partnerships, innovative features, and a commitment to user empowerment. As the project continues to grow, it is poised to redefine the concept of the metaverse and pave the way for a new era of digital interaction. Moreover, it has been observed that different domain parking players are considering NextEarth domains for future revenue generation.
Résumé : La technologie blockchain promet un véritable développement pour le marché financier et en apportant de nouveaux apports sur le marché. Elle a été adoptée dans plusieurs industries et principalement les services financiers. Elle peut créer des registres décentralisés et distribués spécialement dédiés aux services financiers et peut améliorer l’intermédiation financière en procédant à une rapidité de règlement, une baisse des coûts de transactions ainsi qu’un fonctionnement au continu du marché. L’objectif principal de ce papier est alors d’analyser s’il existe empiriquement une relation de long terme et un impact positif entre l’intégration de la blockchain sur la performance du marché boursier, en prenant le cas de la BVMC. La méthode utilisée est une analyse de cointégration via une modélisation du degré d’intégration de la blockchain au Maroc et la performance du marché boursier, représentée par l’évolution de l’indice MASI, tout en intégrant d’autres variables pour étayer davantage le modèle. La BVMC est en pleine transformation et le nouveau modèle de développement de 2021 lui place un rôle important dans le financement de l’économie. Un des leviers d’accélération le plus importants pour la réalisation de ses objectifs reste la digitalisation. Et la blockchain offre plein d’avantages en termes de transformation digitale pour le marché boursier marocain. Plusieurs projets de création de marché financier opérant sur une blockchain sont en cours dans les pays développés, et plusieurs études théoriques démontrent les avantages de l’intégration de la blockchain sur le marché financier. La BVMC sera tentée de suivre les tendances internationales et la recherche de performance conduira la BVMC à intégrer la technologie blockchain. Les résultats de l’étude démontrent alors clairement que la technologie blockchain va apporter de nouvelles règles au mode de fonctionnement et d’organisation des transactions, et qu’elle aura un impact positif sur la performance du marché boursier marocain. Mots clés : Blockchain, registre décentralisé, performance, coûts de transaction, Classification JEL : G15, G17, O16, O31, O55 Type de l’article : Recherche appliquée Abstract: Blockchain technology promises real development for the financial market and bringing new contribution to the market. It has been addressed in several industries and mainly financial services. It can create decentralized and distributed registers specially dedicated to financial services and can improve financial intermediation by ensuring rapid settlement, lower transaction costs and continuous operation of the market. The main objective of this paper is then to analyze whether there exists empirically a long-term relationship and a positive impact between the integration of blockchain on the performance of the stock market, taking the case of BVMC. The method used is a cointegration analysis via modeling the degree of blockchain integration in Morocco and the performance of the stock market, represented by the evolution of the MASI index, while integrating other variables to further support the model. The BVMC is in the midst of a transformation and the new development model (2021) gives it an important role in financing the economy. One of the most important acceleration levers for achieving its objectives remains digitalization. And blockchain offers plenty of advantages in terms of digital transformation for the Moroccan stock market. Several projects to create financial markets operating on a blockchain are underway in developed countries, and several theoretical studies demonstrate the advantages of blockchain integration in the financial market. The BVMC will be tempted to follow international trends and the search for performance will lead the BVMC to integrate blockchain technology. The results of the study clearly demonstrate that blockchain technology will bring new rules to the way transactions operate and are organized, and that it will have a positive impact on the performance of the Moroccan stock market. Keywords: Blockchain, decentralized ledger, performance, transaction costs, JEL Classification: G15, G17, O16, O31, O55 Paper type: Empirical research
Considering that cryptocurrencies are now present in practically every financial transaction because they are widely accepted as an alternate means of making payments and exchanging currencies, academics and economists have more opportunities to study cryptocurrency prices. Over the years, investors, traders and investment banks have found it difficult to predict the closing daily price of Ethereum due to its rapid price fluctuation. The daily closing price of cryptocurrency is essential to consider when trading or investing in Ethereum. This report focuses on carrying out a comparative study of the predictive capabilities of deep machine learning algorithms with a stacking ensemble modelling framework using daily historical observations of the price of Ethereum obtained from Coindesk, tweets extracted from Twitter ranging from the 1st of August 2022 to the 8th of August 2022 and other five covariates (closing price lag1, closing price lag2, noltrend, daytype and month) engineered from the closing price of Ethereum. Seven models are used to compute the forecasts for the daily closing price of Ethereum; these are the recurrent neural network, ensemble stacked recurrent neural network, gradient boosting machine, generalized linear model, distributed random forest, deep neural networks and stacked ensemble for gradient boosting machine, generalized linear model, distributed random forest and deep neural networks. The main evaluation metric used is the mean absolute error. According to MAE, RNN forecasts outperform the other model’s forecasts in this study, producing an MAE of 0.0309.