With its decentralized structure and unchangeable record-keeping system, blockchain technology has gained widespread acceptance in a number of industries, including supply chain management, healthcare, and finance. However, there are issues with scalability, security, and efficiency with its conventional implementation. One way to automate transactions and processes on the blockchain is through smart contracts, which are self-executing agreements with the terms of the contract directly written into lines of code. When combined with smart contracts, artificial intelligence (AI) can unleash a new range of capabilities, such as predictive analytics, adaptive contract execution, and autonomous decision-making. The potential, design, implementation, and effects on blockchain networks of AI-driven smart contracts are the main topics of this paper. It explores the advantages, difficulties, and uses of this integration in addition to the direction that AI-enhanced smart contract systems will take in the future.
In the dynamic world of financial markets, the prediction of stock performance and bitcoin trading is undergoing a significant transformation due to the integration of advanced technologies and novel methodologies.The incorporation of Transformer models alongside Time Embeddings significantly improves the precision of stock market predictions by effectively capturing intricate temporal relationships and mitigating the presence of overly simplistic assumptions.The integration of real-time social media data with sentiment analysis based on BERT provides significant value in understanding investor sentiment.Additionally, the application of language model pre-training, as exemplified by BERT, brings about a transformative impact on text classification for predicting stock prices.Within the domain of cryptocurrency, sophisticated algorithms such as Transformers, Long Short-Term Memory (LSTM), Deep Convolutional LSTM (DC-LSTM), and Neural Networks (NN) have demonstrated enhanced capabilities in predicting price movements.These algorithms are further bolstered by the implementation of a comprehensive trading strategy.Automated systems for bitcoin trading introduce elements of personalization and adaptability to the trading process, thereby facilitating broader access to a diverse group of traders.The progress highlights the significant importance of the integration of technology and methodologies in the field of financial analysis.This integration enables investors and traders to possess the necessary resources for making well-informed choices within the ever-changing landscape of financial markets.
Jan 1, 2023·Proceedings of the International Conference on Financial Innovation, FinTech and Information Technology, FFIT 2022, October 28-30, 2022, Shenzhen, China
The market for cryptocurrency has thrived for more than 10 years and has experienced a drastic change. The success of cryptocurrencies was concerned and analyzed worldwide. This research discusses the way to build machine learning and statistical models to predict the future price of the cryptocurre
As an investor, volatility plays an important role in decision making. It is defined as the rate at which a security’s price increases or decreases, i.e., shows pricing behavior during a definite span of time. A high volatility will lead to high risk. Thus, it becomes critical to determine the volatility and the risk-return trade-off among investments. This paper tries to document the volatility and risk-return trade-off of four prominent crypto-currencies (Bitcoin, Ethereum, Binance and Ripple), based on market-capitalization. For analysis, closing prices of cryptocurrencies has been accumulated through secondary method for 365 days, starting from 1st March 2022 and ending on 28th February 2023. Standard Deviation and Kurtosis, used together for volatility and risk assessment, documented that Bitcoin has the highest volatility and risk associated with expected returns. Regression, for assessing the impact of volatility in BTC price on others, derived that ETH has a strong, but not very strong, bivariate relationship with BTC, among all the pairs. Durbin Watson (DW) test concluded that there was no auto-correlation in the prices of crypto-currencies, i.e., previous day’s price does not play significant role in today’s price. For risk-return trade-off, Coefficient of Variation (CoV) has been applied. It determined that Ethereum has the highest ratio indicating its non-suitability to a conservative investor because of having the lowest returns as compared to risks involved; while Binance has the lowest Coefficient of Variation (CoV) depicting lower risk and maximum return among all.
Management of traditional construction contracts that is frequently preferred in the architecture, engineering, and construction (AEC) industries are affected by many factors due to the complexity and large number of contract documents.With the introduction of Web 3.0 technology, blockchain is considered as a suitable solution for solving many problems arising from traditional contracts and can be considered as an alternative method to traditional contracts in the AEC industry.Using cryptocurrencies, switching to blockchain-based contracts, and using smart contracts will be advantageous for AEC industry in many ways.However, in addition to these advantages, the existence of risk factors cannot be denied.With this background, this study aims to identify risk factors affecting blockchain-based smart contract use in AEC industry through a comprehensive literature review and to prioritize the identified risk factors using Analytic Hierarchy Process, respectively.The prominent risks were found to include implementation risks, followed by legal risks and contractual risks.The contributions of the study to the academic literature are the identification of the risks that may occur during the integration of blockchain-based contracts into the AEC industry and the diagnosis of any problems that may occur during the integration process.Professionals in the field of construction management can also benefit greatly from the findings of this study by analyzing those risks throughout their projects.
Aloysius Ansell Saerang, Meita Kristalina Laman, Setiani Putri Hendratno
Metaverse comes from a novel released in 1992 entitled “Snow Crash”. Metaverse represents concepts beyond entertainment and commerce to create virtual communities as users use avatars to represent themselves within the Metaverse and interact with other users through avatars. In the Metaverse world, Non- Fungible Tokens, or NFTs for short, are also integrated by registering the ownership of digital assets using blockchain technology. However, with technological progress, there are challenges related to security, regulations, difficulties in using the technology, and others. This challenge causes the NFT market to remain unstable, So it raises crucial questions surrounding the behaviour of an accountant, especially in the Gen Z demographic, on how to face these challenges. For this research regarding Metaverse and NFT, the researchers used the qualitative exploratory method, with interviews being one of the most commonly used for data collection. Concluding this research, the accounting profession still has time to adapt to the changes brought on by the Metaverse and NFTs since the technologies are still a small niche, and the majority of the public does not have access to and knowledge about them. Also, many risks and challenges arise due to inadequate government regulations regarding NFT and Metaverse.
Abstract This study examines blockchain technologies and their pivotal role in the evolving Metaverse, shedding light on topics such as how to invest in cryptocurrency, the mechanics behind crypto mining, and strategies to effectively buy and trade cryptocurrencies. While it contextualises the common queries of "why is crypto crashing?" and "why is crypto down?", the research transcends beyond the frequent market fluctuations to unravel how cryptocurrencies fundamentally work and the step-by-step process on how to create a cryptocurrency. Contrasting existing literature, this comprehensive investigation encompasses both the economic and cybersecurity risks inherent in the blockchain and fintech spheres. Through an interdisciplinary approach, the research transitions from the fundamental principles of fintech investment strategies to the overarching implications of blockchain within the Metaverse. Alongside exploring machine learning potentials in financial sectors and risk assessment methodologies, the study critically assesses whether developed or developing nations are poised to reap greater benefits from these technologies. Moreover, it probes into both enduring and dubious crypto projects, drawing a distinct line between genuine blockchain applications and Ponzi-like schemes. The conclusion resolutely affirms the staying power of blockchain technologies, underlined by a profound exploration of their intrinsic value and a reflective commentary by the author on the potential risks confronting individual investors.
Jan 1, 2023·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Darren Aiello, Tetyana Balyuk, Marco Di Maggio, Mark J. Johnson · 6 authors
This paper uses transaction-level data across millions of accounts to identify cryptocurrency investors and evaluate how fluctuations in individual crypto wealth affect household consumption, equity investment, and local real estate markets.We estimate an MPC out of unrealized crypto gains that is more than double the MPC out of unrealized equity gains but smaller than the MPC from exogenous cash flow shocks.This MPC is mostly driven by increases in cash/check spending and mortgages.Moreover, households sell crypto to increase both discretionary as well as housing spending.As a result, crypto wealth causes house price appreciation-counties with higher crypto wealth see higher growth in home values following high crypto returns.Our results indicate that cryptocurrencies have substantial spillover effects on the real economy through consumption and investment into other asset classes.
무기한 선물(Perpetual Swaps)은 가상 자산 시장에서만 유일하게 관찰할 수 있는 파생상품으로 2020년 이후 현재 약 20여 곳 이상의 가상 자산 거래소에서 서비스를 제공하고 있으며 2020년 전체 거래 시장의 20.4%, 2021년 50.4%를 차지할 정도로 양적 성장을 이루었다. 본 연구는 거래소 간 비트코인 무기한 선물과 현물(Spot) 간의 가격 차이를 이용해 차익 거래 기회에 대한 실증 분석 결과를 제시한다. 연구 결과, 비트코인 현물과 무기한 선물 가격의 음과 양이 역전 될 때를 거래 진입 및 청산 신호로 인식하는 매매를 통하여 차익 거래 수익을 창출할 수 있음을 확인하였다. 또한 분 단위 거래에서 거래수수료는 차익 거래 수익에 민감하게 작용하였지만, 일 단위 거래에서는 거래 수수료에 민감하지 않은 양의 수익을 보여주었다. 그리고 분 단위 거래에서는 월 평균 9%, 일 단위 거래에서는 월 평균 38%의 높은 수익률을 나타내었다.
Abstract: We live in a digital age, and Pandemic has accelerated the development of new health care products and introduced new business models and health opportunities. In addition to tele-medicine, supply chain, payment, secure data exchange, and remote monitoring applications, there and they are the latest innovations in blockchain and non-fungible tokens (NFTs) that enable the exchange of value on fragmented networks. Futurists and technology experts are also exploring how Metaverse can play a role in various fields. This Commentary aims to explore how Metaverse can be used in the future to transform, improve, and possibly transform health care. The following areas covered are teamwork, education, clinical care, wellness, and monetization.
Selçuk Kendirli, Ergenoğlu, Sevim, Şenol, Fatma Yıldız
Virtual currency movements, which have intensified recently, are in relation to many macroeconomic variables. The decentralized nature of the cryptocurrency market does not eliminate the variables that affect the market. Macro and microeconomic events and variables affect the cryptocurrency market. The cryptocurrency market can also interact with and affect other markets and variables. Indices, which are the indicator indices of the markets, are important in terms of examining the relationship between the markets. The index, which is the indicator of the cryptocurrency market and includes 30 cryptocurrencies, is called the Cryptocurrencies Index (CCi30). The aim of the study is to examine the relationship between the CCi30 index, BIST 100, and Nasdaq Indices. In the study conducted using Granger Causality Analysis, data between the years 2015-2022 were used. According to the analysis result; It was concluded that CCi30 and Nasdaq indices affect each other in a bidirectional way.