Lukas Christopher Eikeri, Sebastian Andresen Amundsen
Utilizing the generalized spillover index developed by Diebold and Yilmaz (2009,\n2012), we investigate the volatility connectedness between an index consisting of\nnine selected cryptocurrencies, S&P 500, Gold, and Copper. Furthermore, we\nstudy the connectedness and volatility spillover within the nine cryptocurrencies\nin the perspective of the categorization of the cryptocurrency market developed by\nCorbet et al. (2020b). To our knowledge, this is the first study investigating the\nconnectedness between these categories. Lastly, we analyze the initial effect of the\nCOVID-19 pandemic by using an extended set of data to June 2020 on the\nconnectedness within the cryptocurrency market. We also test the connectedness\nbetween the cryptocurrency market, S&P 500, and Gold during the same period.\nWe find that the cryptocurrency market has a weak connectedness with other\nfinancial markets, indicating that most of the volatility comes from within the\ncryptocurrency market. When studying the volatility spillover within the\ncryptocurrency market, in the perspective of categorizations, our results show that\nmost of the volatility is within the respective categories. Adding to this, there are\nsome key differences in the relationship of the categories. Finally, the COVID-19\npandemic increased the volatility and the spillovers across all markets. However,\nthe effects do not affect the results for the cryptocurrencies substantially.
Ethical behavior is a key factor for accountants to win the trust of their stakeholders in the digital age. Many ethical dilemmas are now under consideration and profession is more than concerned about the enhanced risks of ethical compromises. This paper is aiming to discuss the relevance of the fundamental ethics principles for professional accountants in a technology-led digital age. These five principles are: integrity, objectivity, professional competence and due care, confidentiality and professional behavior. Artificial intelligence and big data analytics that are currently changing work environment of the accounting profession are analyzed in this context. Cybersecurity, platform based business models and distributed ledger technology are also considered as ethical challenges in the light of exponentially growing digitalization of economy.
The three cutting-edge technologies virtual reality, blockchain, and 5G have increasingly attracted public attention. While virtual reality became a popular concept in the 1990s, recent technological advances and decreased costs have created a resurgence in the technology. With significant funding and early adoption, blockchain and 5G have begun to make their mark on the world. Each technology alone may disrupt business and society, but, together, they provide multiple opportunities. In this paper, we summarize a 2018 Association for Information Systems Americas Conference on Information Systems (AMCIS) panel session with IS researchers and industry practitioners that tackled important topics related to these technologies. In particular, the panel made the case for IS research that focuses on topics that emerge when these technologies intersect. Each panelist presented their perspectives based on their experience and knowledge along with current issues and future directions. This topic has significant business implications as practitioners continue to note their advancements and develop strategies to adapt in a rapidly changing environment. The topic also has implications for future research as these technologies continue to become more prevalent.
The application of machine learning algorithms in predicting cryptocurrency prices has gained significant attention in recent years. Researchers have explored various approaches such as recurrent neural networks, deep learning neural networks, Bayesian regression, k-nearest neighbor, support vector machine, and other algorithms to forecast the prices of cryptocurrencies like Bitcoin, Ethereum, Dogecoin and Litecoin. This paper will draw on established literature on price prediction using machine learning, including studies on NFT sales predictability, NFT sale price fluctuations prediction, gold price prediction, and silver price forecasting. The research paper has focused on utilizing high-dimensional features, time-series analysis, as well as the comparison of different statistical models and machine learning algorithms. Additionally, the prediction models have incorporated factors such as market liquidity, exchange market dynamics. While the literature acknowledges the potential of machine learning in cryptocurrency price prediction, gold, silver and NFT’s there is a recognized gap in the application of these techniques across a broader range of cryptocurrencies. The proposed methodology will integrate various machine learning models and statistical methods to predict the prices of cryptocurrencies, gold, silver, and NFTs, taking into account factors such as market trends, trade networks and visual features. Furthermore, the studies emphasize the importance of feature engineering, sample dimension engineering, and the use of various machine learning techniques to enhance the accuracy and stability of cryptocurrency price predictions. As the cryptocurrency market continues to expand, there is a need for further research to develop robust machine learning models that can effectively forecast the prices of diverse cryptocurrencies, contributing to the advancement of this field.
Abstract This paper proposes an empirical model for analysing the dynamics of Bitcoin prices. To do this, we consider a vector error correction model over two overlapping periods: 2010–17 and 2010–19. Price discovery is achieved through the Gonzalo–Granger permanent‐transitory decomposition. The pricing factors are endogenous linear combinations of the S&P 500 index, gold price, a Google search variable associated to Bitcoin and a fear index proxied by the FED Financial Stress Index. Our empirical analysis shows that during the first period, a linear combination of four pricing factors describes the efficient Bitcoin price. The S&P 500 index and Google searches have a positive effect whereas gold prices and the fear index have a negative effect. In contrast, during the second period, the efficient price behaves idiosyncratically and can be only rationalised by individuals' search for information on the cryptocurrency. These findings provide empirical evidence on the presence of a correction in Bitcoin prices during the period 2018–19 uncorrelated to market fundamentals. We also show that standard empirical asset pricing models perform poorly for explaining Bitcoin prices.
Riaz Ahmad Ziar, Syed Irfan Ullah, Rafiulllah Omar
The introduction of smart devices and the IOT network has led to the creation of large amounts of data that require protection from intrusion. Most users desire to have personal data kept confidential while seeking for platforms that would prohibit their vendors from distributing it to third parties without their consent. However, the users that are conscious of data privacy often share information with third parties, contradicting their intentions in keeping their information confidential. The difference between user intentions and actions regarding data privacy is called privacy paradox while privacy fatigue refers to the weariness of people on implementing security and privacy solutions. In this proposed system we design and develop smart contracts to provide interaction for the IoT device and company which require personal data. A company or Application requests personal information from the device to share the device sends, that information to the smart contract, smart contract uses dynamic rules to check PII in the users' personal information. Base on the PII(,) system would alert users on the limit and risk of sharing personal information through a public network. We used solidity programing language for the modeled of the smart contract. The performance of the contract is evaluated on the Repsten test network.
With blockchain technology, information is recorded in a permanent distributed ledger that is maintained by multiple computers in a peer-to-peer network. There is no central authority that can alter records or change network consensus rules. Such technology could be utilized for voting, title transfers, issuance of company shares, document notarization, but currently, the most popular use-case are virtual currencies. An interesting feature that some virtual currencies have is a multisignature (multisig) protocol that requires the electronic signatures from more than one private key to initiate a transfer of funds. Raw data of a multisig transaction may be recognized as an arbitral award under the New York Convention, where the law of England is the lex arbitri and parties have opted-out of a reasoned award.
Dilek Akdoğan Akbaş, Gamze Yıldız Şeren, Osman Geyik
Last revolution of industry history is known as “Industry 4.0” or also known as 4th Industrial Revolution that<br> forms the basis of increasing technology network has emerged as digital technology-based digital revolution. Digitalisation<br> in 4th Industrial Revolution reflected to currency and cryptocurrencies has become a part of today’s<br> world. Blockchain technology as the basis of virtual currency is one of the leading technologies under 4th Industrial<br> Revolution and gradually increases impact range. Bitcoin as a cryptocurrency that introduced blockchain technology<br> to the world can be characterised as the most important financial technology (fintech) innovation of digital<br> age. Income from bitcoin as cryptocurrency are at significant level and risks of using bitcoin in money laundering<br> and financing illegal activities have led countries to apply regulations for cryptocurrencies. This study aims to<br> analyse regulations for cryptocurrencies that gradually increases market cap under 4th Industrial Revolution process.
La blockchain propose un système d'enregistrement décentralisé, immuable et transparent. Elle offre un réseau de nœuds sans entité de gouvernance centralisée, ce qui la rend "indéchiffrable" et donc plus sûr que le système d'enregistrement centralisé sur papier ou centralisé telles que les banques. L’approche traditionnelle basée sur l’enregistrement ne fonctionne pas bien avec les relations numériques où les données changent constamment. Contrairement aux canaux traditionnels, régis par des entités centralisées, blockchain offre à ses utilisateurs un certain niveau d'anonymat en leur permettant d'interagir sans divulguer leur identité personnelle et en leur permettant de gagner la confiance sans passer par une entité tierce. En raison des caractéristiques susmentionnées de la blockchain, de plus en plus d'utilisateurs dans le monde sont enclins à effectuer une transaction numérique via blockchain plutôt que par des canaux rudimentaires. Par conséquent, nous devons de toute urgence mieux comprendre comment ces opérations sont gérées par la blockchain et combien de temps cela prend à un nœud du réseau pour confirmer une transaction et l’ajouter au réseau de la blockchain. Dans cette thèse, nous visons à introduire une nouvelle approche qui permettrait d'estimer le temps il faudrait à un nœud de la blockchain Ethereum pour accepter et confirmer une transaction sur un bloc tout en utilisant l'apprentissage automatique. Nous explorons deux des approches les plus fondamentales de l’apprentissage automatique, soit la classification et la régression, afin de déterminer lequel des deux offrirait l’outil le plus efficace pour effectuer la prévision du temps de confirmation dans la blockchain Ethereum. Nous explorons le classificateur Naïve Bayes, le classificateur Random Forest et le classificateur Multilayer Perceptron pour l’approche de la classification. Comme la plupart des transactions sur Ethereum sont confirmées dans le délai de confirmation moyen (15 secondes) de deux confirmations de bloc, nous discutons également des moyens pour résoudre le problème asymétrique du jeu de données rencontré avec l’approche de la classification. Nous visons également à comparer la précision prédictive de deux modèles de régression d’apprentissage automatique, soit le Random Forest Regressor et le Multilayer Perceptron, par rapport à des modèles de régression statistique, précédemment proposés, avec un critère d’évaluation défini, afin de déterminer si l’apprentissage automatique offre un modèle prédictif plus précis que les modèles statistiques conventionnels.
The graduation certificate forgery has become a major problem in now a days and the lack of effective anti-forge mechanism, In order to solve the problem of counterfeiting certificates, the digital certificate system based on blockchain technology would be introduced. The system generate the electronic file of a paper certificate accompanying other related data into the database and calculates its hash value. It then store the hash value into the block in the chain system. The system will create a related QR-code and inquiry string code to affix to the paper certificate, this will verify the authenticity of the paper certificate through mobile phone scanning or website inquiries. By integrating the features of blockchain, the system improves the efficiency operations at each stage.
This paper examines how smart contracts can enhance accounts payable in supply chain finance by automating the three-way match.The conventional system relies on the manual verification of purchase orders, goods receipts, and invoices; hence, it usually causes delays and errors and is expensive.This paper has created a set of conceptual frameworks where blockchain technology is used to automate such processes.The outcomes are great improvements.The processing time is also cut down to approximately 1.5 or 2 days using smart contracts, compared with the manual systems of about 8-14 days.The per 1000 transactions cost is reduced to approximately 650 from 2000 by a wide margin of almost 40-70%.The error rate also reduces drastically from 9.5% to 1.3%, which is primarily through automated validation and elimination of manual data entry.Real-time data capture enhances transparency and accelerates reporting on finances.Certain issues are still there, including the reliability of the data, scaling of the system, and absence of clear legal and accounting standards.The analysis demonstrates that smart contracts can benefit the efficiency, accuracy, and control in the accounts payable process significantly.
The evolution of financial technology adds to the complexity of the global financial system and the underlying assets that store its value.This complexity manifests as an adverse market risk profile in assets where fintech can be considered an endogenous variable.A theoretical framework that may contribute toward an improved understanding of this relationship is established.In contrast to the adverse risk profile in these markets, however, the literature still suggests a value proposition in these fintech-endogenous markets.The suggested value proposition is investigated by means of an empirical literature review, and partial recreation of some key findings from previous literature.Subsequently, additional empirical findings are contributed through a comparative set of tests in a controlled environment, with some significant results, specifically in the case where an appropriate trading strategy is back-tested along with some neural network forecasting procedures.The implications for researchers and practitioners are emphasised by a re-contextualisation of how the findings could affect future research in forecasting-and trading methodologies as well as the status quo of portfolio management strategies that risk managers have at their disposal.They key contribution is that risk managers should be able to benefit from the erratic behaviour of fintech-endogenous markets in the form of non-negligible short-term abnormal profit, whilst not having to trade off the diversification properties consistent with the established literature.The junction of forecasting-and trading methodologies used here may result in a "best of both worlds" investment strategy where abnormal profits are possible in the short run, in a simultaneously well-hedged trading environment, which relies on (instead of mitigating) the erratic price-formation phenomena prevalent in fintech-endogenous markets.
Smart contracts are the most important feature in block chain applications, and they are also the main reason why blockchains are called disruptive technology. Traditional intelligent contracts with receipts are generated by SHA-256A UXTO (unexpended transaction output), and increasing the number of receipts slows down the speed. This paper introduces the operation of receipts in smart contracts and proposes to generate contract receipts with the VIF virtual iteration function. VIF takes advantage of the excellent features of the Hash function and the unreadable nature of the self-compiled system, so that different contract parameters generate unique and non-repudiation receipts through the virtual iterative function, providing a secure and reliable credential for smart contracts. Finally, the speeds at which the VIF receipt and traditional UXTO receipt are generated are compared.
This thesis in Industrial Engineering and Management examines which the critical success factors are for implementing blockchain technology in the context of trade finance. Blockchain is an up-and-coming technology that has yet not been implemented in many organizations. By examining which the success factors are for implementing the technology, a foundation can be provided for future implementation efforts with the hope of achieving a successful result. Furthermore, to assess if an implementation of blockchain has been successful or not, the value of it has been assessed. Through a qualitative study with interviewees from both companies acting in the trade finance industry and experts on the subject of blockchain, information could be gathered in order to confirm the theoretical framework as well asprovide for new findings. The conclusion was that the most important success factors for implementing blockchain, found in the theoretical framework were: "Managing and involving stakeholders (for instance customers and suppliers)", "Clear management support/commitment/involvement of the implementation",and "Understanding of the organization in which the implementation is to take place (its strengths, needs,etc.)". The least important factors proved to be "An in depth understanding of the technology that is to be implemented; what it is and how it works", "Keeping the change communicable and transparent within the organization", and "Extensive project definition and planning". Unexpected findings were that almost all interviewees mentioned that there has to be a real need for the technology in order for it to be successfully implemented. Also, as the very nature of blockchain requires cooperation; it is important to realize that blockchain will require a higher degree of working over organizational boundaries. Another aspect that proved to be important to take into consideration is that the trade finance industry holds legacyand therefore is prone to be resistance to change, especially to a technology of such a highly disruptive character. Lastly, it is of importance to mention that the context also has to be taken into consideration;every organization is different and require different approaches when it comes to implementing blockchain technology. When it comes to how blockchain technology generates value from an organizational perspective, the most common answers were that it enhances collaboration and trust. Many identify value in the problem-solving and more decentralized mindset that blockchain brings. An unexpected finding was that the mere use of the word blockchain will create value, as this enables collaboration and investment. Other reasons given were security, transparency, automation, traceability,and decentralization. Further analysis examined the reasons behind the importance and connection of these answers.
Currently, a large range of opinions exists regarding the appropriate classification and regulation of cryptocurrency. From the legal perspective, some suggest that cryptocurrency investments are too speculative. As a result of this, it is suggested that cryptocurrency should be more heavily regulated. This would be done to prevent speculators from losing vast wealth. Other legal analysts suggest that an increasing cryptocurrency regulation would have a detrimental effect on the state of cryptocurrency, and its use would cause long-term problems. From the accounting perspective, opinions vary. Some suggest an accounting classification that would make cryptocurrency cash equivalents; others suggest an accounting classification that would render cryptocurrency an intangible asset with an indefinite useful life. The “big 4” accounting firms that include Deloitte, PricewaterhouseCoopers, Ernst and Young, and KPMG recommend that cryptocurrency should be classified as an intangible asset with an indefinite useful life. However, other companies currently using cryptocurrency through the general operations of the business have decided to classify it differently. The legal perspectives and the accounting perspectives will be analyzed to determine appropriate regulations for cryptocurrency and an appropriate classification for cryptocurrency. The results will show that cryptocurrency should be classified as an intangible asset with an indefinite useful life for accounting purposes and as property for tax purposes.
Ubiquitous sensing enabled by Wireless Sensor Network (WSN) technologies cuts across many areas of modern day living.This offers the ability to measure, infer and understand environmental indicators, from delicate ecologies and natural resources to urban environments.The proliferation of these devices in a communicating-actuating network creates the Internet of Things (IoT), wherein, sensors and actuators blend seamlessly with the environment around us, and the information is shared across platforms in order to develop a common operating picture (COP).Fuelled by the recent adaptation of a variety of enabling device technologies such as RFID tags and readers, near field communication (NFC) devices and embedded sensor and actuator nodes, the IoT has stepped out of its infancy and is the next revolutionary technology in transforming the Internet into a fully integrated Future Internet.As we move from www (static pages web) to web2 (social networking web) to web3 (ubiquitous computing web), the need for data-on-demand using sophisticated intuitive queries increases significantly.This paper gives very interesting understanding with IoT discussed with making as simple as possible not with the intention to reach concept only up to readers but to become understandable and friendly at students level with some text and basic models.
As one of the most cutting-edge technologies in Fintech, the application of blockchain has been prevailing across a series of industries. By adopting literature research, this paper analyzes the origin, characteristics and working principle of blockchain. According to the features and requirements of traditional auditing, this paper finds the superiority of blockchain technology, for example, distributed ledger, consensus mechanism and timestamp could facilitate auditing in three ways: (1)improve timeliness of auditing and reduce auditing cost; (2)ensure data integrity and realize automatic auditing; and (3)realize pre-warning and real-time supervision to reduce auditing risk. However, although blockchain has brought unprecedented opportunities to the development and reform of audit industry, the blockchain technology still faces a number of challenges, such as data security, talent and technology support, industry and recognition promotion, and practical application and execution. Concerning these limitations, this paper looks forward to further research field which could contribute to the upcoming improvement of blockchain auditing.
Jan 1, 2018·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Smart City infrastructures require contracts between public and private organizations collaborating in what is frequently referred to as fog computing platforms. We investigate contract provision variations from different stakeholder perspectives. Our methodology relies on complex adaptive systems theory, and we simulate different contract provision scenarios to identify patterns that emerge. The specific contract provisions we investigate in this paper are related to analytical model and data ownership paradigm variations. We find that some variations offer advantages to stakeholders that include those who participate in the smart city fog platform and those who may have ownership of smart city fog platform infrastructure.