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
The viability of exponentially growing non-fungible token(NFT)market is evaluated by identifying potential value-generating mechanisms that can be rationalized.After identifying the value-generating mechanisms underly...The viability of exponentially growing non-fungible token(NFT)market is evaluated by identifying potential value-generating mechanisms that can be rationalized.After identifying the value-generating mechanisms underlying the positive values of NFTs,this study establishes a pricing model for NFTs that follows a continuous-time financial framework.As NFTs are claimed to securitize“ownership rights short of use”,and as such they may potentially serve as a substitute for the need to rely replace the reliance on the legal protection provided by intellectual property rights(IPRs).Considering this issue,this study evaluates the likelihood that NFTs will replace existing mechanisms that protect producers’rightful claim to use their assets or the need to apply the legal code that governs IPRs.The financial condition for this potential shift is derived for a category of assets whose use or consumption does not reduce supply as the notion of scarcity does not apply.展开更多
In this work, Nuclear Reactor safety was modeled inform of quadratic functional. The nuclear tokens are structured and used as elements of the control matrix operator in our quadratic functional. The numerical results...In this work, Nuclear Reactor safety was modeled inform of quadratic functional. The nuclear tokens are structured and used as elements of the control matrix operator in our quadratic functional. The numerical results obtained through Conjugate Gradient Method (CGM) algorithm identify the optimal level of safety required for Nuclear Reactor construction at any particular situation.展开更多
To better understand the potential and limitations of the tokenization of real asset mar-kets,empirical studies need to examine this radically new organization of financial mar-kets.In our study,we examine the financi...To better understand the potential and limitations of the tokenization of real asset mar-kets,empirical studies need to examine this radically new organization of financial mar-kets.In our study,we examine the financial and economic consequences of tokenizing 58 residential rental properties in the US,particularly those in Detroit.Tokenization aims at fragmented ownership.We found that the residential properties examined have 254 owners on average.Investors with a greater than USD 5,000 investment in real estate tokens,diversify their real estate ownership across properties within and across the cities.Property ownership changes about once yearly,with more changes for proper-ties on decentralized exchanges.We report that real estate token prices move accord-ing to the house price index;hence,investing in real estate tokens provides economic exposure to residential house prices.展开更多
Data trading is a crucial means of unlocking the value of Internet of Things(IoT)data.However,IoT data differs from traditional material goods due to its intangible and replicable nature.This difference leads to ambig...Data trading is a crucial means of unlocking the value of Internet of Things(IoT)data.However,IoT data differs from traditional material goods due to its intangible and replicable nature.This difference leads to ambiguous data rights,confusing pricing,and challenges in matching.Additionally,centralized IoT data trading platforms pose risks such as privacy leakage.To address these issues,we propose a profit-driven distributed trading mechanism for IoT data.First,a blockchain-based trading architecture for IoT data,leveraging the transparent and tamper-proof features of blockchain technology,is proposed to establish trust between data owners and data requesters.Second,an IoT data registration method that encompasses both rights confirmation and pricing is designed.The data right confirmation method uses non-fungible token to record ownership and authenticate IoT data.For pricing,we develop an IoT data value assessment index system and introduce a pricing model based on a combination of the sparrow search algorithm and the back propagation neural network.Finally,an IoT data matching method is designed based on the Stackelberg game.This establishes a Stackelberg game model involving multiple data owners and requesters,employing a hierarchical optimization method to determine the optimal purchase strategy.The security of the mechanism is analyzed and the performance of both the pricing method and matching method is evaluated.Experiments demonstrate that both methods outperform traditional approaches in terms of error rates and profit maximization.展开更多
Drone photography is an essential building block of intelligent transportation,enabling wide-ranging monitoring,precise positioning,and rapid transmission.However,the high computational cost of transformer-based metho...Drone photography is an essential building block of intelligent transportation,enabling wide-ranging monitoring,precise positioning,and rapid transmission.However,the high computational cost of transformer-based methods in object detection tasks hinders real-time result transmission in drone target detection applications.Therefore,we propose mask adaptive transformer (MAT) tailored for such scenarios.Specifically,we introduce a structure that supports collaborative token sparsification in support windows,enhancing fault tolerance and reducing computational overhead.This structure comprises two modules:a binary mask strategy and adaptive window self-attention (A-WSA).The binary mask strategy focuses on significant objects in various complex scenes.The A-WSA mechanism is employed to self-attend for balance perfomance and computational cost to select objects and isolate all contextual leakage.Extensive experiments on the challenging CarPK and VisDrone datasets demonstrate the effectiveness and superiority of the proposed method.Specifically,it achieves a mean average precision (mAP@0.5) improvement of 1.25%over car detector based on you only look once version 5 (CD-YOLOv5) on the CarPK dataset and a 3.75%average precision(AP@0.5) improvement over cascaded zoom-in detector (CZ Det) on the VisDrone dataset.展开更多
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
In the pursuit of balanced trade with the U.S., China pours it on where it counts A week ahead of Chinese President Hu Jintao's first state visit to the United States, Beijing and Washington reached a series of ag...In the pursuit of balanced trade with the U.S., China pours it on where it counts A week ahead of Chinese President Hu Jintao's first state visit to the United States, Beijing and Washington reached a series of agreements intended to ease the bilateral trade imbalance, including resuming trade in U.S. beef, increasing Chinese market access to U.S. medical devices, telecom services and express delivery, and cracking down on intellectual property rights infringements.展开更多
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.
文摘The viability of exponentially growing non-fungible token(NFT)market is evaluated by identifying potential value-generating mechanisms that can be rationalized.After identifying the value-generating mechanisms underlying the positive values of NFTs,this study establishes a pricing model for NFTs that follows a continuous-time financial framework.As NFTs are claimed to securitize“ownership rights short of use”,and as such they may potentially serve as a substitute for the need to rely replace the reliance on the legal protection provided by intellectual property rights(IPRs).Considering this issue,this study evaluates the likelihood that NFTs will replace existing mechanisms that protect producers’rightful claim to use their assets or the need to apply the legal code that governs IPRs.The financial condition for this potential shift is derived for a category of assets whose use or consumption does not reduce supply as the notion of scarcity does not apply.
文摘In this work, Nuclear Reactor safety was modeled inform of quadratic functional. The nuclear tokens are structured and used as elements of the control matrix operator in our quadratic functional. The numerical results obtained through Conjugate Gradient Method (CGM) algorithm identify the optimal level of safety required for Nuclear Reactor construction at any particular situation.
文摘To better understand the potential and limitations of the tokenization of real asset mar-kets,empirical studies need to examine this radically new organization of financial mar-kets.In our study,we examine the financial and economic consequences of tokenizing 58 residential rental properties in the US,particularly those in Detroit.Tokenization aims at fragmented ownership.We found that the residential properties examined have 254 owners on average.Investors with a greater than USD 5,000 investment in real estate tokens,diversify their real estate ownership across properties within and across the cities.Property ownership changes about once yearly,with more changes for proper-ties on decentralized exchanges.We report that real estate token prices move accord-ing to the house price index;hence,investing in real estate tokens provides economic exposure to residential house prices.
基金supported by the National Key Research and Development Program of China(No.2022YFF0610003)the BUPT Excellent Ph.D.Students Foundation(No.CX2022218)the Fund of Central University Basic Research Projects(No.2023ZCTH11).
文摘Data trading is a crucial means of unlocking the value of Internet of Things(IoT)data.However,IoT data differs from traditional material goods due to its intangible and replicable nature.This difference leads to ambiguous data rights,confusing pricing,and challenges in matching.Additionally,centralized IoT data trading platforms pose risks such as privacy leakage.To address these issues,we propose a profit-driven distributed trading mechanism for IoT data.First,a blockchain-based trading architecture for IoT data,leveraging the transparent and tamper-proof features of blockchain technology,is proposed to establish trust between data owners and data requesters.Second,an IoT data registration method that encompasses both rights confirmation and pricing is designed.The data right confirmation method uses non-fungible token to record ownership and authenticate IoT data.For pricing,we develop an IoT data value assessment index system and introduce a pricing model based on a combination of the sparrow search algorithm and the back propagation neural network.Finally,an IoT data matching method is designed based on the Stackelberg game.This establishes a Stackelberg game model involving multiple data owners and requesters,employing a hierarchical optimization method to determine the optimal purchase strategy.The security of the mechanism is analyzed and the performance of both the pricing method and matching method is evaluated.Experiments demonstrate that both methods outperform traditional approaches in terms of error rates and profit maximization.
文摘Drone photography is an essential building block of intelligent transportation,enabling wide-ranging monitoring,precise positioning,and rapid transmission.However,the high computational cost of transformer-based methods in object detection tasks hinders real-time result transmission in drone target detection applications.Therefore,we propose mask adaptive transformer (MAT) tailored for such scenarios.Specifically,we introduce a structure that supports collaborative token sparsification in support windows,enhancing fault tolerance and reducing computational overhead.This structure comprises two modules:a binary mask strategy and adaptive window self-attention (A-WSA).The binary mask strategy focuses on significant objects in various complex scenes.The A-WSA mechanism is employed to self-attend for balance perfomance and computational cost to select objects and isolate all contextual leakage.Extensive experiments on the challenging CarPK and VisDrone datasets demonstrate the effectiveness and superiority of the proposed method.Specifically,it achieves a mean average precision (mAP@0.5) improvement of 1.25%over car detector based on you only look once version 5 (CD-YOLOv5) on the CarPK dataset and a 3.75%average precision(AP@0.5) improvement over cascaded zoom-in detector (CZ Det) on the VisDrone dataset.
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In the pursuit of balanced trade with the U.S., China pours it on where it counts A week ahead of Chinese President Hu Jintao's first state visit to the United States, Beijing and Washington reached a series of agreements intended to ease the bilateral trade imbalance, including resuming trade in U.S. beef, increasing Chinese market access to U.S. medical devices, telecom services and express delivery, and cracking down on intellectual property rights infringements.
