In the metaverse,digital assets are essential to define identity,shape the virtual environment,and facilitate economic transactions.This study introduces a novel feature to the metaverse by capturing a fundamental asp...In the metaverse,digital assets are essential to define identity,shape the virtual environment,and facilitate economic transactions.This study introduces a novel feature to the metaverse by capturing a fundamental aspect of individuals–their conversations–and transforming them into digital assets.It utilizes natural language processing and machine learning methods to extract key sentences from user conversations and match them with emojis that reflect their sentiments.The selected sentence,which encapsulates the essence of the user’s statements,is then transformed into digital art through a generative visual model.This digital artwork is transformed into a non-fungible token,becoming a valuable digital asset within the blockchain ecosystem that is ideal for integration into metaverse applications.Our aim is to manage personality traits as digital assets to foster individual uniqueness,enrich user experiences,and facilitate more personalized services and interactions with both like-minded users and non-player characters,thereby enhancing the overall user journey.展开更多
The metaheuristics algorithm is increasingly important in solving many kinds of real-life optimization problems but the implementation involves programming difficulties. As a result, many researchers have relied on so...The metaheuristics algorithm is increasingly important in solving many kinds of real-life optimization problems but the implementation involves programming difficulties. As a result, many researchers have relied on software framework to accelerate the development life cycle. However, the available software frameworks were mostly designed for rapid development rather than flexible programming. Therefore, in order to extend software functions, this approach involves modifying software libraries which requires the programmers to have in-depth understanding about the internal working structure of software and the programming language. Besides, it has restricted programmers for implementing flexible user-defined low-level hybridization. This paper presents the concepts and formal definition of metaheuristics and its low-level hybridization. In addition, the weaknesses of current programming approaches supported by available software frameworks for metaheuristics are discussed. Responding to the deficiencies, this paper introduces a rapid and flexible software framework with scripting language environment. This approach is more flexible for programmers to create a variety of user-defined low-level hybridization rather than bounded with built-in metaheuristics strategy in software libraries.展开更多
The convergence of blockchain and immersive technologies has resulted in the popularity of Metaverse platforms and their cryptocurrencies,known as Metaverse tokens.There has been little research into tokenomics in the...The convergence of blockchain and immersive technologies has resulted in the popularity of Metaverse platforms and their cryptocurrencies,known as Metaverse tokens.There has been little research into tokenomics in these emerging tokens.Building upon the information dissemination theory,this research examines the role of trading volume in the returns of these tokens.An empirical study was conducted using the trading volumes and returns of 197 Metaverse tokens over 12 months to derive the latent grouping structure with spectral clustering and to determine the relationships between daily returns of different token clusters through augmented vector autoregression.The results show that trading volume is a strong predictor of lead-lag patterns,which supports the speed of adjustment hypothesis.This is the first large-scale study that documented the lead-lag effect among Metaverse tokens.Unlike previous studies that focus on market capitalization,our findings suggest that trade volume contains vital information concerning cross-correlation patterns.展开更多
This study investigates the static and dynamic return and volatility spillovers between non-fungible tokens(NFTs)and conventional currencies using the time-varying parameter vector autoregressions approach.We reveal t...This study investigates the static and dynamic return and volatility spillovers between non-fungible tokens(NFTs)and conventional currencies using the time-varying parameter vector autoregressions approach.We reveal that the total connectedness between these markets is weak,implying that investors may increase the diversification benefits of their multicurrency portfolios by adding NFTs.We also find that NFTs are net transmitters of both return and volatility spillovers;however,in the case of return spillovers,the influence of NFTs on conventional currencies is more pronounced than that of volatility shock transmissions.The dynamic exercise reveals that the returns and volatility spillovers vary over time,largely increasing during the onset of the Covid-19 crisis,which deeply affected the relationship between NFTs and the conventional currencies markets.Our findings are useful for currency traders and NFT investors seeking to build effective cross-currency and cross-asset hedge strategies during systemic crises.展开更多
We analyze the connectedness between major cryptocurrencies and nonfungible tokens(NFTs)for different quantiles employing a time-varying parameter vector autoregression approach.We find that lower and upper quantile s...We analyze the connectedness between major cryptocurrencies and nonfungible tokens(NFTs)for different quantiles employing a time-varying parameter vector autoregression approach.We find that lower and upper quantile spillovers are higher than those at the median,meaning that connectedness augments at extremes.For normal,bearish,and bullish markets,Bitcoin Cash,Bitcoin,Ethereum,and Litecoin consistently remain net transmitters,while NFTs receive innovations.However,spillover topology at both extremes becomes simpler—from cryptocurrencies to NFTs.We find no markets useful for mitigating BTC risks,whereas BTC is capable of reducing the risk of other digital assets,which is a valuable insight for market players and investors.展开更多
文摘In the metaverse,digital assets are essential to define identity,shape the virtual environment,and facilitate economic transactions.This study introduces a novel feature to the metaverse by capturing a fundamental aspect of individuals–their conversations–and transforming them into digital assets.It utilizes natural language processing and machine learning methods to extract key sentences from user conversations and match them with emojis that reflect their sentiments.The selected sentence,which encapsulates the essence of the user’s statements,is then transformed into digital art through a generative visual model.This digital artwork is transformed into a non-fungible token,becoming a valuable digital asset within the blockchain ecosystem that is ideal for integration into metaverse applications.Our aim is to manage personality traits as digital assets to foster individual uniqueness,enrich user experiences,and facilitate more personalized services and interactions with both like-minded users and non-player characters,thereby enhancing the overall user journey.
文摘The metaheuristics algorithm is increasingly important in solving many kinds of real-life optimization problems but the implementation involves programming difficulties. As a result, many researchers have relied on software framework to accelerate the development life cycle. However, the available software frameworks were mostly designed for rapid development rather than flexible programming. Therefore, in order to extend software functions, this approach involves modifying software libraries which requires the programmers to have in-depth understanding about the internal working structure of software and the programming language. Besides, it has restricted programmers for implementing flexible user-defined low-level hybridization. This paper presents the concepts and formal definition of metaheuristics and its low-level hybridization. In addition, the weaknesses of current programming approaches supported by available software frameworks for metaheuristics are discussed. Responding to the deficiencies, this paper introduces a rapid and flexible software framework with scripting language environment. This approach is more flexible for programmers to create a variety of user-defined low-level hybridization rather than bounded with built-in metaheuristics strategy in software libraries.
文摘The convergence of blockchain and immersive technologies has resulted in the popularity of Metaverse platforms and their cryptocurrencies,known as Metaverse tokens.There has been little research into tokenomics in these emerging tokens.Building upon the information dissemination theory,this research examines the role of trading volume in the returns of these tokens.An empirical study was conducted using the trading volumes and returns of 197 Metaverse tokens over 12 months to derive the latent grouping structure with spectral clustering and to determine the relationships between daily returns of different token clusters through augmented vector autoregression.The results show that trading volume is a strong predictor of lead-lag patterns,which supports the speed of adjustment hypothesis.This is the first large-scale study that documented the lead-lag effect among Metaverse tokens.Unlike previous studies that focus on market capitalization,our findings suggest that trade volume contains vital information concerning cross-correlation patterns.
基金supported by FCT,I.P,the Portuguese national funding agency for science,research and technology under the Project UIDB/04521/2020.
文摘This study investigates the static and dynamic return and volatility spillovers between non-fungible tokens(NFTs)and conventional currencies using the time-varying parameter vector autoregressions approach.We reveal that the total connectedness between these markets is weak,implying that investors may increase the diversification benefits of their multicurrency portfolios by adding NFTs.We also find that NFTs are net transmitters of both return and volatility spillovers;however,in the case of return spillovers,the influence of NFTs on conventional currencies is more pronounced than that of volatility shock transmissions.The dynamic exercise reveals that the returns and volatility spillovers vary over time,largely increasing during the onset of the Covid-19 crisis,which deeply affected the relationship between NFTs and the conventional currencies markets.Our findings are useful for currency traders and NFT investors seeking to build effective cross-currency and cross-asset hedge strategies during systemic crises.
基金supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea(NRF-2022S1A5A2A01038422)partly funded by the University of Economics Ho Chi Minh City,Vietnam.
文摘We analyze the connectedness between major cryptocurrencies and nonfungible tokens(NFTs)for different quantiles employing a time-varying parameter vector autoregression approach.We find that lower and upper quantile spillovers are higher than those at the median,meaning that connectedness augments at extremes.For normal,bearish,and bullish markets,Bitcoin Cash,Bitcoin,Ethereum,and Litecoin consistently remain net transmitters,while NFTs receive innovations.However,spillover topology at both extremes becomes simpler—from cryptocurrencies to NFTs.We find no markets useful for mitigating BTC risks,whereas BTC is capable of reducing the risk of other digital assets,which is a valuable insight for market players and investors.
