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加密货币市场数据的质量对于学术研究和财务应用至关重要，但是，该行业面临许多挑战

The quality of cryptocurrency market data is critical for academic research and financial applications. Yet, the industry faces a number of challenges, including pervasive mislabeling, measurement errors and discrepancies in reported market metrics.

加密货币市场数据的质量对于学术研究和财务应用至关重要。然而，该行业面临许多挑战，包括广泛的标签，测量错误和报告的市场指标的差异。

A new academic research by Gustavo Schwenkler of the Santa Clara University, alongside Aakash Shah and Darren Yang of Indicia Labs, highlights these persistent issues, emphasizing the difficulty of relying on a single provider for all crypto market data needs.

圣塔克拉拉大学的古斯塔沃·施旺克勒（Gustavo Schwenkler）以及Indicia Labs的Aakash Shah和Darren Yang进行了一项新的学术研究，强调了这些持久问题，强调了难以依靠单个提供商来满足所有加密市场数据需求的困难。

The researchers reviewed 20 of the most common crypto market data providers, examining their crypto data from January 2022 to October 2024. An in-depth analysis of a subset of eight providers – CoinCap, CoinGecko, CoinMarketCap, CoinPaprika, CryptoCompare, Live Coin Watch, Nomics, and Santiment – from November 2018 to October 2024 revealed concerning trends.

The analysis revealed a substantial level of inconsistency in how cryptocurrencies are identified. As much as 21% of all coins in a provider’s dataset could undergo ID changes within a 24-month period without any disclosure, rendering direct comparisons across time difficult.

该分析表明，如何识别加密货币有很大的不一致性。提供商数据集中所有硬币中多达21％的硬币可以在24个月内进行ID变化，而无需任何披露，从而在困难的情况下进行了直接比较。

Moreover, some providers kept the same ID for a coin even after a fork or a swap that rendered a new coin, effectively misrepresenting the asset’s identity. Additionally, certain providers used the same ID for distinct cryptocurrencies, a problem encountered in 16% of the sample from CoinGecko.

此外，即使在叉或交换后，一些提供商仍保留了硬币的同一ID，从而有效地歪曲了资产的身份。此外，某些提供商将相同的ID用于不同的加密货币，这是Coingecko的16％样本中遇到的问题。

This analysis also unveiled significant inconsistencies in the reported data across providers. For instance, the daily close price for a cryptocurrency can vary to a great extent from one provider to another. In extreme cases, the price discrepancies at the close of a particular day could be quite large.

该分析还揭示了跨提供商报告的数据的明显不一致。例如，加密货币的每日近距离价格可能会在很大程度上从一个提供商到另一个提供商。在极端情况下，特定日期结束时的价格差异可能很大。

These inconsistencies arise because providers collect and aggregate data from various public platforms. Because providers have discretion over which prices they select at any given time and how they aggregate them, inconsistencies are to be expected.

这些矛盾之处之所以出现，是因为提供商从各种公共平台收集和汇总数据。由于提供者在任何给定时间选择哪些价格以及他们如何汇总的价格都有酌处权，因此预期的是不一致。

Beyond price discrepancies, trading volume metrics also exhibit strong variations across providers. This is especially pervasive for reported volumes, where in almost 70% of the daily instances in the six-year sample, the daily aggregate volume for a coin reported by a provider deviated by more than 5% from the median volume reported across providers.

除了价格差异之外，交易量指标还表现出各个提供商的差异。这对于报道的量尤其普遍，在六年样本中，几乎70％的每日实例中，每日总量的每日总量是由提供商偏离5％以上的提供商中间量的代理商报告的每日总量。

This issue is particularly prominent for large coins that are listed on many exchanges and is exacerbated by the practice of wash trading, where exchanges artificially inflate their reported trading volumes to appear more liquid.

对于在许多交易所上列出的大型硬币而言，此问题尤为突出，并且因Wash Trading的做法而加剧了，在这种做法中，交易所的交换人为地膨胀了其报告的交易量，以表现出更多的流动性。

In traditional capital markets, data is standardized across large vendors or by regulatory bodies. However, the crypto industry lacks such standardization, with providers differing in data definitions, delivery technologies, and reporting methodologies.

在传统的资本市场中，数据在大型供应商或监管机构中进行标准化。但是，加密行业缺乏这样的标准化，提供者的数据定义，交付技术和报告方法不同。

As digital assets gain traction among institutional investors, the demand for robust and reliable market data infrastructure has intensified as investors seek high-quality data for informed trading strategies and regulatory compliance.

随着数字资产在机构投资者之间的吸引力，随着投资者寻求高质量的数据以获得知情的交易策略和监管合规性，对稳健和可靠的市场数据基础设施的需求加剧了。

This has fueled the growth of crypto data providers like CCData, CoinDesk, Compadre, CryptoCompare, Digital Asset Analytics, Factor Factor, FTX, Kaiko, Lungo, and TRM offering cleansed and normalized data from multiple independent sources, despite the absence of agreed data quality standards or auditing. These sources include blockchains themselves, but also centralized exchanges, decentralized finance (DeFi), and derivatives markets.

这加剧了加密数据提供商的增长，例如CCDATA，COINDESK，COMPADRE，CRYPTOCARE，数字资产分析，因子因子，FTX，Kaiko，Lungo和TRM，尽管缺乏商定的数据质量标准或审计，但仍能从多个独立源提供清洁和归一化数据。这些来源包括区块链本身，还包括集中式交流，分散的财务（DEFI）和衍生品市场。

Beyond consolidating and normalizing data, some vendors also deliver derived metrics, signals, and indicators, empowering clients with actionable information. For instance, DeFi analytics providers like DefiLlama and DeFiPulse provide insights into liquidity pool sizes, interest rates, and other crucial metrics within the decentralized finance ecosystem.

除了合并和标准化数据之外，一些供应商还提供了派生的指标，信号和指标，还可以通过可行的信息授权客户。例如，诸如Defillama和Defipulse之类的Defi分析提供商提供了对分散融资生态系统中流动性池大小，利率和其他关键指标的见解。

Crypto data is a rapidly emerging sub-industry that’s playing a significant role in the broader digital asset ecosystem. Explored in a new report by Financial Technology (FT) Partners, a fintech-focused investment bank, this ecosystem encompasses five main verticals:

加密数据是一个快速新兴的子行业，在更广泛的数字资产生态系统中发挥了重要作用。该生态系统在金融技术（FT）合作伙伴的新报告（FT）合作伙伴的一份新报告中探讨，该生态系统涵盖了五个主要垂直领域：

This sector has seen a strong interest from investors, with major funding rounds such as Chainalysis’s $170 million Series F, Lukka’s $110 million Series E, and Kaiko’s $53 million Series B.

该行业对投资者产生了浓厚的兴趣，包括Chainalysis的1.7亿美元系列F，Lukka的1.1亿美元系列E和Kaiko的5300万美元系列B。

In terms of mergers and acquisitions (M&A) activity, prominent players like Chainalysis, Lukka and Amberdata have been acquiring smaller startups to integrate new technologies and expand their product offerings.

在合并和收购（并购）活动方面，诸如Chainalysis，Lukka和Amberdata之类的杰出参与者一直在收购较小的初创企业，以整合新技术并扩展其产品。

Chainalysis acquired Excygent, a specialist in cybercrime investigation; Transpose, a blockchain data and infrastructure company; and Alterya, an AI-powered fraud detection solution provider. Meanwhile, Lukka acquired Blox Finance, a crypto accounting and financial data management software business; Venato, a Web3 blockchain analytics startup; and Coinfirm, a top-tier European based blockchain analytics software company.

链分析获得了网络犯罪研究专家Excygent；转置，区块链数据和基础架构公司；和Antya，AI-Power的欺诈检测解决方案提供商。同时，卢卡（Lukka）收购了Blox Finance，Crypto会计和财务数据管理软件业务； Venato，Web3区块链分析初创公司；以及CoInfirm，这是一家欧洲顶级区块链分析软件公司。

On the other hand, Kaiko acquired Kesitys, a data analytics company; and Vinter, a leading European crypto index provider.

另一方面，Kaiko收购了数据分析公司Kesitys；和欧洲领先的加密指数提供商Vinter。