Article(id=1149673297249485273, tenantId=1146029695717560320, journalId=1146123222451335185, issueId=1149670639897854094, articleNumber=1671-1807(2025)10-0325-08, orderNo=null, doi=, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1732204800000, receivedDateStr=2024-11-22, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1752033073961, onlineDateStr=2025-07-09, pubDate=1748102400000, pubDateStr=2025-05-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752033073961, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752033073961, creator=13701087609, updateTime=1757563464646, updator=13701087609, issue=Issue{id=1149670639897854094, tenantId=1146029695717560320, journalId=1146123222451335185, year='2025', volume='25', issue='10', pageStart='1', pageEnd='377', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752032440399, creator=13701087609, updateTime=1756780756355, updator=15831073675, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1169586520596947842, tenantId=1146029695717560320, journalId=1146123222451335185, issueId=1149670639897854094, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1169586520596947843, tenantId=1146029695717560320, journalId=1146123222451335185, issueId=1149670639897854094, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=325, endPage=332, ext={EN=ArticleExt(id=1151877661552373833, articleId=1149673297249485273, tenantId=1146029695717560320, journalId=1146123222451335185, language=EN, title=Analysis of the Current Research Status of Digital Assets, columnId=1151877659430055969, journalTitle=Science Technology and Industry, columnName=Governance & Performance, runingTitle=null, highlight=null, articleAbstract=

With the rapid development of the digital economy, digital assets, as a new type of asset category, are showing an exponential growth trend. A comprehensive and systematic classification and summary of the types of digital assets was firstly conducted, and the valuation systems and operation mechanisms of various digital assets were deeply analyzed. The risks and challenges currently faced by the digital asset field were also examined and the regulatory measures at the regulatory level were discussed. Through in-depth and detailed sorting and analysis, scientific basis and guidance are provided for the future development of the digital asset field.

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随着数字经济的飞速发展,数字资产作为一种新兴的资产类别,呈现指数级的增长态势。首先对数字资产的类型进行全面而系统的归纳与总结,并深入分析各类数字资产估值体系与运行机制,同时还审视当前数字资产领域所面临的风险挑战,探讨监管层面的应对举措。通过深入细致的梳理与分析,旨在为数字资产领域的未来发展提供科学依据与指导。

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李潭博(1998—),男,河南汝州人,硕士研究生,研究方向为数字经济,金融风险管理;

孟佳欣(1998—),女,黑龙江宁安人,硕士研究生,研究方向为资本市场、金融风险管理;

蒋文江(1962—),男,云南昆明人,博士,教授,研究方向为金融风险管理、概率论与数理统计。

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李潭博(1998—),男,河南汝州人,硕士研究生,研究方向为数字经济,金融风险管理;

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李潭博(1998—),男,河南汝州人,硕士研究生,研究方向为数字经济,金融风险管理;

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孟佳欣(1998—),女,黑龙江宁安人,硕士研究生,研究方向为资本市场、金融风险管理;

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孟佳欣(1998—),女,黑龙江宁安人,硕士研究生,研究方向为资本市场、金融风险管理;

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蒋文江(1962—),男,云南昆明人,博士,教授,研究方向为金融风险管理、概率论与数理统计。

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蒋文江(1962—),男,云南昆明人,博士,教授,研究方向为金融风险管理、概率论与数理统计。

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数字资产研究现状分析
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李潭博 , 孟佳欣 , 蒋文江
科技和产业 | 治理绩效 2025,25(10): 325-332
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科技和产业 | 治理绩效 2025, 25(10): 325-332
数字资产研究现状分析
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李潭博, 孟佳欣, 蒋文江
作者信息
  • 云南师范大学经济学院, 昆明 650000
  • 李潭博(1998—),男,河南汝州人,硕士研究生,研究方向为数字经济,金融风险管理;

    孟佳欣(1998—),女,黑龙江宁安人,硕士研究生,研究方向为资本市场、金融风险管理;

    蒋文江(1962—),男,云南昆明人,博士,教授,研究方向为金融风险管理、概率论与数理统计。

Analysis of the Current Research Status of Digital Assets
Tanbo LI, Jiaxin MENG, Wenjiang JIANG
Affiliations
  • School of Economics, Yunnan Normal University, Kunming 650000, China
出版时间: 2025-05-25 doi:
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随着数字经济的飞速发展,数字资产作为一种新兴的资产类别,呈现指数级的增长态势。首先对数字资产的类型进行全面而系统的归纳与总结,并深入分析各类数字资产估值体系与运行机制,同时还审视当前数字资产领域所面临的风险挑战,探讨监管层面的应对举措。通过深入细致的梳理与分析,旨在为数字资产领域的未来发展提供科学依据与指导。

数字资产  /  数据资产  /  加密货币

With the rapid development of the digital economy, digital assets, as a new type of asset category, are showing an exponential growth trend. A comprehensive and systematic classification and summary of the types of digital assets was firstly conducted, and the valuation systems and operation mechanisms of various digital assets were deeply analyzed. The risks and challenges currently faced by the digital asset field were also examined and the regulatory measures at the regulatory level were discussed. Through in-depth and detailed sorting and analysis, scientific basis and guidance are provided for the future development of the digital asset field.

digital assets  /  data assets  /  cryptocurrencies
李潭博, 孟佳欣, 蒋文江. 数字资产研究现状分析. 科技和产业, 2025 , 25 (10) : 325 -332 .
Tanbo LI, Jiaxin MENG, Wenjiang JIANG. Analysis of the Current Research Status of Digital Assets[J]. Science Technology and Industry, 2025 , 25 (10) : 325 -332 .
随着第四次工业革命的推进,数字技术的进步不断重塑人们对资产类型的认知。以数据形式存在的数字资源,因其能够带来经济回报,逐渐被视为资产。资产的概念由最初的有形资产(如不动产、交通工具和贵金属等)拓展到无形资产(包括知识产权、专利和商誉等)。如今,这一概念进一步扩展到数字资产,涵盖商业数据、数字藏品和加密货币等新兴领域。这一演变不仅反映资产定义的扩展,还揭示数字经济时代下资产形态的多样性和复杂性。由于数字资产类型多样、结构复杂,其价值评估及所面临的风险也显著不同于传统资产类型。因此,如何精准把握数字资产的价值并有效防范多样化的风险,对该行业的发展具有重要意义。
数字资产作为一种新兴的资产类型,目前国内相关研究尚处于起步阶段,数字资产的界定与分类还比较模糊,尤其是针对不同类型数字资产的价值评估、风险预防及监管方面的研究较为零散。这亟待进行系统的梳理和科学的分析。本文将数字资产的内涵与分类、数字资产的估值与应用以及数字资产的风险预防与监管三个角度进行梳理研究,旨在为数字资产的管理与配置、交易与风险预防及监管提供理论基础。
在讨论数字资产之前,将引入三组相关概念,即数字资产、数据资产和数字货币。旨在通过这些概念的分析与组织,对数字资产的内涵、价值实现与风险进行系统评估。
数字资产源于第三次工业革命信息化技术的发展,其存在形式和经济特性不同于传统资产。在存在形式上,Meyer[1]于1996年第一次提出数字资产这一概念,随后Van Niekerk[2]将其定义为二进制形式存在的任何的文本或者媒体项目。Best[3]进一步将数字资产定义为存储在智能设备中的资源,Toygar等[4]则将这一范围进一步扩大为以数字形式存储在计算设备或者互联网云端的数据。上述研究表明,数字资产是以二进制或者数字形式存在。作为能够带来经济回报的资产类型,Goldfinger[5]首次提出数字文本、图片等以数字形式存在资产已经成为经济来源的一部分,Gladen等[6]提出数字资产具有多次重复传播和价值增值的特征,可以为其拥有者带来一系列价值流入。在此基础上Austerberry[7]将数字资产定义为个人或机构拥有的以数字形式存在,能在日常生活和生产活动中产生经济价值的资产。
早在1974年Peterso[8]就提出“数据资产”的概念,他认为将原始数据资料作为生产资料进行加工处理以后形成的即为数据资产,Lee和Yang[9]通过构建模型证明数据通过与传统资产结合具有价值的流动性和创造性。中国信息通信研究院云计算与大数据所将数据资产定义为“由组织(政府机构、企事业单位等)合法拥有或控制的数据,以电子或其他方式记录,如文本、图像、语音、视频、网页、数据库、传感信号等结构化或非结构化数据,可进行计量或交易,能直接或间接带来经济效益和社会效益”[10]。耿汉威[11]从会计角度认为,只有企业能够控制的数据才能被确认为资产,而公开渠道可获取的公共数据不属于这一范畴。从上述研究可以看出,数据本身并不直接产生价值,对数据进行整理、加工、清洗、分析后数据才能为企业所用。此外,数据资产流转要以产权归属明晰为前提,只有明确了数据的归属权和所有权才能合理分配数据从而产生收益。
关于“数字货币”的定义,学术界尚未达成一致,但围绕发行方式、支付方式和价值形成等角度展开了广泛讨论。Chaum[12]在其著作《不可追踪支付系统的盲签名》(Blind Signatures for Untraceable Payment Systems)中首次提出数字货币的概念,在国际清算银行2015年发布的《数字货币》报告中,数字货币被定义为一种电子形式的货币,其价值存储在芯片卡或个人电脑硬盘中,包括央行准备金、商业银行存款等,属于广义的电子货币。蔡昌等[13]认为数字资产有广义和狭义之分,广义数字资产包括信息系统产生的数据,狭义则主要指数字货币。本文通过整理数字货币的相关文献,以发行机构的不同将数字货币分为法定数字货币和加密货币,加密货币又可细分为同质化代币和非同质化代币,同质化代币又可细分为稳定币和加密货币等。
Dai[14]最早提出数字货币这一概念,他描述了一个匿名、分布式和数字货币的系统,后来这一思想为比特币的出现奠定基础。比特币作为最典型的同质化加密货币于2008年由Nakamoto[15]通过著名的《比特币:点对点电子现金系统》(Bitcoin: A Peer-to-Peer Electronic Cash System)创建比特币而普及开来。在该篇论文中,Nakamoto介绍了加密货币是基于区块链技术进行加密并产出货币的,这些货币所具有的价值是相等的并且可以互换。同质化货币除了比特币这类加密货币外还有稳定币,稳定币最早由Larimer[16]在BitShares 平台上提出,后来Tether[17]于2014年发布白皮书发行泰达币并说明其与美元的挂钩机制,目前泰达币已经成为应用最广泛的稳定币。稳定币与加密货币的区别在于稳定币通常由私营部门发行,并且与法定货币价值挂钩或者由资产支持而加密货币没有任何资产支持,稳定币的目的是在加密货币的波动市场中提供价格稳定性。除此之外,同质化代币还包括以太坊智能合约的实用性代币、募集资金的证券型代币(ICO)和随着DeFi 生态系统的成熟的合成型代币。
非同质化的代币(non-fungible tokens,NFT)是一种基于区块链技术的资产,它代表了对某些独特物品或内容的所有权(如数字艺术藏品、收藏品或虚拟地产等),由于每一个资产的内容或者存在形式都是不同的,因此NFT是不可互换且唯一的。在2014年纽约七艺博览会上Kevin McCoy 和 Anil Dash展出一个名为“Quantum” 的作品,标志着第一个 NFT 的诞生。McCoy 创建这个作品,并通过 Namecoin 区块链来证明该作品的所有权。这种将艺术品通过区块链数字化,并赋予其不可互换的特性的行为后来成为非同质化代币概念的基础。后来Entriken等[18]编写了ERC-721标准,该标准是非同质化代币的技术基础之一。该技术不仅定义了以太坊如何管理和创建不可互换的代币,而且推动NFT作为数字资产概念的落地。
中央银行数字货币(central bank digital currency,CBDC)的概念最早可以追溯到20世纪末期,但是没有明确的单一提出者。法定数字货币大规模讨论出现在比特币和区块链技术之后,其实施最早开始于2014年厄瓜多尔推出的法定数字货币项目(sistema de dinero electrónico),该项目由于各种因素于2018年被终止。厄瓜多尔推出的法定数字货币属于零售型数字货币,即面向普通消费者和小型企业的日常消费和交易,其目的是作为法定货币的补充。真正让零售型法定货币面向国际的是中国的数字人民币(digital currency electronic payment,DCEP)[19]。中国不仅大力发展数字人民币,并且于2021年提出多边央行数字货币桥,大力推进数字人民币国家化。另一种法定数字货币是批发型法定货币,即用于金融机构之间大规模交易和结算的法定货币,主要面向银行、大型金融机构。加拿大于2016年推出贾斯铂项目(Project Jasper)[20],这是最早探索批发型法定货币的项目,此外新加坡金融管理局(MAS)也推出了乌宾项目(Project Ubin)[21]以推进研究批发行数字货币,旨在提高跨境支付和金融机构之间的结算效率[21]
综上所述,数据资产和数字资产的内涵大致趋同,因此将数据资产等同于广义的数字资产。在考察广义的数字资产是要强调以下两点:一是客体是以有意义的数据聚合在一起,能够给企业带来经济效益的数据资源。二是这些资源能够被可靠计量并且完成价值评估。狭义的数字资产的内涵比较丰富,由发行人的不同可以分为法定数字货币和加密货币,加密货币又因是否可以互换分为同质化代币和非同质化代币。数字货币的相互关系如图1所示。
数字资产价值实现一般有三种形式:一是以数字形式存在本身具有内在价值的数字金融资产,可以作为货币进行电子交易、储存和支付(如比特币、CBDC和稳定币等)。二是经过整合、处理和分析后的数据可以产生价值,这类数字资产一般通过对外交易实现价值,交易者通常以数据咨询和分析为主的服务型企业为主。三是数据本身是杂乱无章的,但是结合企业本身的业务可以间接创造价值、赋能实体业务,帮助企业增加销售收入、提高竞争力。
由于数字资产更新速度快、价值波动大且具有可复用性,传统的定价模型在其估值中的适用性显著下降,亟须开发新的定价模型以应对这一挑战。本文根据数字资产的不同类型,对相关定价模型及运行机制进行简要介绍。
由于数据资产具有动态性、业务依附性、迭代积累和价值不确定性[22]。因此,在进行资产定价之前首先要确定数据资产的所有权。目前学界对于数据资产所有权的讨论还未形成一致的共识,比较具有代表性的有“新人格权说”“知识产权说”“商业秘密说”“数据所有权说”。其中“数据所有权”的受关注度最高,这是因为数据所有权更适合大数据发展。数据所有权是指对信息的使用权和所有权以及责任。由于数据资产能够产生一系列的收益,因此数据资产的估值可以类比无形资产,无形资产的评估方法已经比较成熟,主要有市场法、成本法、收益法等。下面分别从三个方法简要介绍以下相关学者的研究。
李永红和张淑雯[23]认为,基于信息生命周期理论,数据资产的价值只能在交换过程中体现,因此应用市场法作为评估依据。从数据数量、质量、数据分析能力等角度,确定数据资产价值评估的影响因素。运用层次分析法计算各影响因子的权重值。采用灰色关联度法对各影响因素进行量化,计算关联系数,进而计算关联度。在此基础上,选取可比数字资产,构建价值评估模型。刘琦等[24]通过量化两者之间的差异,对数据资产的价值进行量化评估,并且综合确定技术修正系数,从数据资产的获取成本、技术、价值密度、数据容量差异等方面对其价值进行调整。
张志刚等[25]分析数据资产的构成和主要影响因素,运用层次分析法(AHP)构建成本和应用指标评价体系,并运用YAAHP层次分析软件计算评价指标的权重,最后得出资产价值评估模型:数据资产价值=数据资产车成本得分+数据资产应用评估得分。
在数据资产价值评估中,收益法主要有超额收益法、增量收益法和收益分成法等,其中核心是超额收益法。超额收益法首先用残差法将由于数据资产产生的超额收益从整体收益中剔除出来,然后对超额收益进行折现。陈芳和余廉[26]基于数据资产的特点,采用多期超额收益法建立数据资产价值评估模型,计算数据资产的折现率,据此评估数据资产的价值。刘惠萍等[27]改进多期超额收益模型来评价企业的数据资产,他们利用Pear曲线和GM(1,1)灰色预测模型对多期超额收益法进行改进,并选取相关行业进行验证。除了类比传统无形资产估值,也有学者尝试从经济学、管理学和计算机科学等领域的非传统模型中找到评估数据资产的突破口。李秉祥和任昑晓[28]以B-S模型为基础,从平台用户数量和点击量、数据资产使用权应用产生的价值、数据资产所有权转移产生的超额收益及风险政策和道德因素对数据量变甚至是质变的影响4个方面构建数字资产价值评估模型。左文进和刘丽君[29]将资产定价和博弈论有机结合,涉及数据资产估值方法,构建数据资产估值方法优化体系。
数字货币可以分为加密货币和法定数字货币,法定数字货币作为法定货币的补充,价值一般较为稳定,学界关于法定数字货币的研究都集中在法定数字货币的机制上,关于价值的研究较少。吴桐等[30]对法定数字货币优势、风险及运行做了详细阐述,并在中国人民银行货币现行基础上提出一套分级利率体系,并指出该体系未来的发展方向。姚前[31]使用DSGE模型测算了数字货币对经济有正面影响,并且指出央行数字货币的利率作为货币政策的补充,可以起到宏观调控的作用。宋爽和刘东民[32]站在全球视角,提出未来央行数字货币在国际竞争中将会重视技术发展,要积极发挥私营机构积极性、稳步推进普惠性和利率化并且积极通过国际合作建立竞争优势。
由于比特币的出现间接导致了加密货币市场的兴起,因此学界关于比特币的价值及其影响因素的研究较多。根据Peng等[33]的做法,影响加密货币定价的因素主要有6类,分别是为基本面因素、技术因素、经济因素、市场波动性、投资者属性和社交媒体。研究加密货币定价模型的方法有很多,如向量自回归模型、广义自回归条件异方差模型和三因素模型等,但是使用最广泛的是向量自回归模型,Ibrahim[34]认为该模型与传统自回归模型和贝叶斯模型相比,在模拟比特币交易价格方面取得了更好的性能。Garcia等[35]首先使用大数据量化比特币的社会经济信号,然后使用向量自回归模型解释加密货币价格的驱动因素。加密货币总其他方向的研究也在稳步推进,如Ante[36]指出学界关于稳定币的研究大多集中的三个方向,研究最多的是不同资产类别支持的稳定币的稳定性或波动性,其次研究稳定币在加密货币生态中的作用以及研究稳定币与其他加密货币的联系。关于非同质化代币的研究主要集中在法律、社会效率以及其他方面,关于定价方面的研究较少。Dowling[37]测算土地作为非同质代币的定价效率,他们使用一系列统计测试,包括自动方差比(AVR)测试、自动波特曼(AP)测试和多明戈斯和洛博托(DL)一致性测试,以评估土地定价的市场效率,研究发现NFT的定价普遍低效。
数据资产估值学术界目前已提出多种模型,如市场法、成本法和超额收益法,但对具体数字资产形式的研究仍存在差异,特别是在法定数字货币、加密货币和非同质化代币(NFT)的定价问题上仍需要更多探索。研究显示,数据资产的所有权及法定数字货币的机制、加密货币的多种影响因素等方面,均是定价模型发展的关键领域。
近年来,随着数字技术的迅速发展,数字资产的种类和规模都呈现出快速增长的趋势。作为一种新兴资产类别,数字资产已经深度融入全球金融体系,成为其不可或缺的一部分。尽管数字资产的创新特性使其在风险特征上与传统资产相似,但仍存在显著差异。此外,由于不同国家对数字资产的态度和政策目标各异,其相关法律条款和监管措施也呈现多样化的特点。正因如此,在面对法律问题和纠纷时,制定一套能够兼容不同国家法律体系的国际数字资产法律框架显得尤为重要。Predrag[38]指出,在不同国家的经济主体因经济纠纷需要诉诸法律时,应根据纠纷涉及的数字资产的实际控制人所在国来确定适用的法律。不同类型的数字资产在法律冲突中应该依据技术中立原则同等对待,无论该资产以何种形式存在或持有都应一视同仁。Lehmann[39]通过对比不同国家在解决法律冲突时的做法,进一步提出处理数字资产法律冲突的“理想”规则。他认为,数字资产物权的法律性质、内容和有效性应依据数字资产所属地的法律进行认定。当无法明确选择适用法律时,应以数字资产的登记注册运营商、发行人或委托管理人所在地的有效法律为依据。在发生交易冲突时,若涉及有形链接资产的收购,收购方应优先于代币收购方,除非收购方明确知晓或应当知晓该有形资产已经被代币化。如果交易涉及多个关联方或权责难以划分时,应以与该项目关系最为紧密的方所在地的法律为准,若该法律与当地法律相冲突,则该条款不适用。冯静[40]从税收角度指出现行的三层分类的税收框架无法解决数字资产的纳税问题,她指出技术创新难以从根本上解决这一难题,必须改变法律框架或中央集中管理才能从根本上解决纳税问题。
数字资产的风险不仅体现在法律框架的残缺,还体现在法律监管的缺失,数字资产的隐私权与监管问题是当前亟待解决的关键难题。由于数字资产通常以数字或电子形式存在,并且部分数据由管理平台存储在网络中,这种去中心化和匿名化的特性使得货币当局难以对其交易和活动进行有效监管。此外,许多数字资产的参与者购买数字资产的部分动机正是为了规避传统监管机制。因此,如何确定数字资产的数据是否能够被监管者有效监控,及其监管的范围和尺度,已经成为学术界迫切需要解决的重要课题。为了解决隐私安全问题,王宝银等[41]提出以随机公证人多签架构的跨链模型保护参与者的隐私安全。张虹和熊澄宇[42]从法律与伦理角度不仅要保护用户的隐私安全,还要适度进行监管以保护社会安全。Collberg[43]指出数字资产的隐私权问题主要涉及个人信息保护、交易隐私及去中心化网络中的数据安全。其中隐私与透明性的矛盾、去中心化中的网络保护问题及法律挑战最为重要,他提出可以使用如门罗币等隐私币交易、链下交易、签署隐私征求协议和法律与技术相结合等方法解决上述问题。由于不同类型的数字资产的风险特征和设计初衷有所差别,因此需要采取的政策措施在细节上也稍有不同,下面分别简述一下各种类型的数字资产目前采取的政策和相关研究。
关于数据资产的研究起步较早,相关讨论也相对丰富。黄海瑛[44]在整理中国数据产权政策后指出中国数据产权处于“分散模式”,提出需要解决监管、交易、确权等九大问题。王虎和宋良荣[45]认为,当前国内数据资产监管首先需要解决的是数据资产产权问题,明确产权是数据资产价值计量的基础。其次,现有估值方法的可行性和稳定性不足,企业对数据资产的披露相关性也有待提高。马慧洁和夏杰长[46]提出要根据数据处理过程中来源、处理及使用者的权益明晰所有权。杜振华和荼洪旺[47]以制度经济学为基础从公共数据、企业数据和个人数据三个层面分析并提出确权的基础。刘悦欣和夏杰长[48]根据目前实际估值遇到的问题,提出要确定估值标准、以市场应用为导向、加强信息保护和提升监管水平的政策建议。陈雪萍和钟翊鸣[49]提出可以在《民法典》的基础上厘清数字资产的定义并以此作为资产权力的客体,并制定《数字资产保护法》以解决数字资产的产权及估值问题。
关于法定数字货币的研究,虽然全球多数法定数字货币仍处于研发或实验阶段,学者们已经对其风险防范及法律框架展开了讨论。现有研究主要集中在CBDC对银行业、金融稳定、支付体系及货币政策的影响。Keister和Sanches[50]认为在新货币主义体系下如果CBDC与银行存款竞争激烈,银行脱媒是不可避免的。Andolfatto[51]认为计息CBDC将成为银行获取存款的威胁,并激励银行为吸收存款给出更加优惠的条款。Ozili[52]认为CBDC对不同体量的银行的影响不同,CBDC对大型银行贷款的负面影响是小型银行的三倍。Fernando等[53]通过三期银行挤兑模型的变体引入CBDC,最终他们认为创建广泛使用的CBDC可能会增加全系统的挤兑风险。Andolfatto[54]提出著名的CBDC三难困境,即运营CBDC的央行最多可以实现以下三个目标中的两个:金融稳定、效率和价格稳定。Auer[36]强调了不同司法管辖体系之间的互操作性的重要作用。Minesso等[55]通过一般均衡模型(dynamic stochastic general equilibrium, DSGE)研究CBDC对货币政策和福利的经济影响,他们认为CBDC的加入可能会对最佳货币政策产生重大影响,并加剧国际货币体系的不对称性。
基于上述问题,王青和钱昕舟[56]建议构建区域性新型跨境支付体系,提出中国央行参与的“数字货币桥”项目是一个良好的示范,各国应根据实际需求选择合适的交互模式和开放程度,确保新型支付体系与传统体系相辅相成,并提前制定跨境支付体系的支付规则,强化政策研究。杨荣海和李亚波[57]则站在全球角度提出中国要依托“中国制造”推广数字人民币,发挥数字人民币在国际贸易中的优势,让数字人民币成为全球央行数字货币体系之锚。邓宇[58]提出CBDC全球化要依靠各国协调配合,各国不仅要在安全稳定的基础上加入CBDC的多边合作,也要共同推进CBDC的国际金融网络基础设施建设。
自2009年比特币问世以来,加密货币已经成为一种革命性的资产类别,在某种程度上成为传统法定货币的替代品。经过多年发展,加密货币市场经历指数级增长,已经成为全球金融系统生态的重要组成部分,在给金融领域带来创新的同时,加密货币也带来了风险,包括逃税、操纵市场、放大市场波动和用于洗钱或资助恐怖主义等非法活动。考虑到以上因素,加密货币的相关监管变得尤为重要,但是由于其去中心化的设计,各国对待加密货币监管态度也有所不同,中国国际司与2021年9月宣布中国全面禁止虚拟货币交易(2018)、2014年6月加州州长签署AB129法案为虚拟货币合法化铺平道路、德国将比特币视为资产征税。Bal[59]提出如果比特币等视为资产,那么交易比特币获得的收益应该纳税。总的来说全球对待加密货币的监管立场可以大致分为:全面禁止(如中国等)、部分禁止、限制性管制、支持性监管等。在现有监管体系下Xiong和Luo[60]提出加密货币体系目前面临诸多挑战,如:区块链的可扩展性与加密货币金融包容性、区块链假名与用户隐私、区块链去中心化与法律问责、区块链跨境性质与管辖权问题。为解决上述挑战,庞野和县祥[61]提出从几个方面进行治理:①严格审核加密货币交易平台的资质与合规流程,各部门联合建立严格的准入标准和监管机制,并且设置涨跌幅限制抑制投资行为。②各政府运用技术手段提升监管水平,并且加强投资者宣传教育,引导投资者理性交易,增强投资者的风险意识。提升加密货币全球监管不是一个或几个国家参与就可以实现的,应该建立一个国际化的数字货币治理与监管机构,并借鉴联合国的制度安排,让加密货币为国际金融的发展提供新的动力。
综上所述,数字资产是指所有以数字形式存在并能够为个人或企业带来经济效益的资产。从广义上看,数字资产主要指企业通过数据整合和分析形成的可利用数据资源,这些资源能够与实体资产或业务有机结合,从而创造更大的经济价值。狭义的数字资产主要指基于区块链技术的加密货币和央行数字货币,其区别在于发行主体和发行目的不同。加密货币通常由去中心化的技术平台发行,而央行数字货币由政府或中央银行主导。作为一种新兴的资产类型,数字资产种类繁多,类型间差异显著,结构复杂,且参与方多样。其价值波动远超传统资产,并因去中心化特性及监管机制的缺失,带来诸多风险。尽管如此,学术界在数字资产的定义和估值模型方面仍未形成统一的结论。本文基于相关学者的研究,尝试从广义和狭义两方面对数字资产的定义和估值模型进行梳理和总结,期望为这一领域的理论完善和实践应用提供参考与启示。在理解数字资产的性质与估值问题的同时,还需认识到其作为新兴资产类别,发展时间短,相关风险防控意识薄弱,抗风险能力不足,以及监管体系的缺位等问题。未来的研究与实践应着重推动数字资产的合理安全发展,确保其能够在有效的监管框架下为金融系统服务,为经济发展提供支持。
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  • 接收时间:2024-11-22
  • 首发时间:2025-07-09
  • 出版时间:2025-05-25
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    云南师范大学经济学院, 昆明 650000
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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