了解分析加密资产和传统金融市场之间的差异

近年来，加密货币市场已经迅速成熟，截至2025年5月，全球市值超过2.5万亿美元。

The cryptocurrency markets have matured rapidly in recent years, boasting a global market capitalization of over $2.5 trillion as of May 2025. Yet despite their scale, analyzing crypto assets remains fundamentally different from analyzing stocks, bonds, or commodities. These differences are not just academic—they have real consequences for investors, traders, and researchers trying to make sense of crypto markets. The lack of intrinsic valuation anchors, the dominance of sentiment, and the fragmentation of data are just a few of the factors that separate crypto from traditional finance.

近年来，加密货币市场已经迅速成熟，截至2025年5月，全球市值超过2.5万亿美元。但是，尽管规模范围，分析加密货币资产与分析股票，债券或商品的分析根本不同。这些差异不仅是学术，它们对试图理解加密市场的投资者，商人和研究人员产生了真正的影响。缺乏内在的估值锚，情感的主导地位以及数据的分散只是将加密货币与传统金融分开的一些因素。

1. No Real-World Benchmarks or Earnings

1。没有现实世界的基准或收益

Traditional stocks are evaluated based on business fundamentals: revenue, profit margins, cash flows, and valuation ratios like P/E (price-to-earnings) or EV/EBITDA. For example, Apple (AAPL) reported $383 billion in revenue in 2024, with a P/E ratio hovering around 28—concrete data that grounds its valuation.

根据业务基本原理评估传统股票：收入，利润率，现金流量和估值比率，例如P/E（市值）或EV/EBITDA。例如，苹果公司（AAPL）报告说，2024年的收入为3830亿美元，市盈率徘徊在28个左右，这是结合其估值的结合数据。

By contrast, most cryptocurrencies lack earnings, cash flows, or even consistent usage metrics. Bitcoin, for instance, has no balance sheet or income statement. Ethereum does generate fee revenue from network usage, amounting to over $1.7 billion in ETH burned in 2024 via EIP-1559, but that figure fluctuates heavily and is not directly comparable to company earnings. For newer or lower-cap coins, even basic adoption metrics like daily active users or transaction volume are often absent or unreliable.

相比之下，大多数加密货币都缺乏收益，现金流量甚至使用一致的用法指标。例如，比特币没有资产负债表或损益表。以太坊的确从网络使用中产生了费用收入，在2024年通过EIP-1559烧毁了超过17亿美元的ETH，但该数字大大波动，与公司的收入不直接相提并论。对于较新的或较低的硬币，即使是基本的采用指标，例如日常活跃用户或交易量通常都不存在或不可靠。

2. Sentiment Plays a Larger Role

2。情绪扮演更大的角色

In crypto, sentiment is often the primary driver of price movement. With no intrinsic earnings to anchor valuation, narratives and public perception become central. Social media platforms like Twitter, Telegram, Discord, and Reddit act as real-time sentiment indicators, often moving prices more significantly than on-chain data or fundamental updates.

在加密货币中，情绪通常是价格变动的主要驱动力。由于没有固定估值的内在收入，叙述和公众的看法就成为中心。 Twitter，Telegram，Discord和Reddit等社交媒体平台作为实时情感指标，通常比链上数据或基本更新更明显地转移价格。

A 2023 study by Santiment found that spikes in Twitter activity were followed by short-term price increases in 67% of the top 100 crypto assets. Memecoins like DOGE and SHIB have rallied hundreds of percent on viral memes alone. DOGE surged 500% in April 2021 after Elon Musk tweeted a single word—”Doge.” Similar examples abound: in 2024, PEPE and WIF reached billion-dollar market caps with virtually no utility, purely on the back of community hype and influencer promotion. Community ranking tools like Bitlenz are able to surface the most active crypto projects simply by how often they are mentioned on social media.

Santiment的一项2023年的研究发现，在Twitter活动中的尖峰之后，在前100名加密货币资产中，短期价格上涨了67％。诸如Doge和Shib之类的模因仅在病毒模因上集结了数百％。埃隆·马斯克（Elon Musk）在推特上发了一个字 - “多吉”之后，2021年4月猛增了500％。类似的例子比比皆是：2024年，佩佩（Pepe）和Wif几乎没有效用，纯粹是在社区炒作和影响者促进的后面，达到了十亿美元的市值。像Bitlenz这样的社区排名工具可以通过社交媒体上提到的频率来浮出水面最活跃的加密项目。

This is in stark contrast to equity markets, where earnings calls and quarterly reports carry far more weight than social media buzz.

这与股票市场形成鲜明对比，股票市场的收入电话和季度报告的重量要比社交媒体的嗡嗡声要大得多。

3. Data is Fragmented and Unstructured

3。数据是零散的和非结构化的

Stock data is clean, regulated, and standardized. Earnings, filings, and prices come from centralized exchanges and regulatory bodies like the SEC. Crypto data is the Wild West by comparison. Prices differ across exchanges. Volume is often inflated—according to a Bitwise report, 95% of reported crypto trading volume in 2019 was fake or non-economic.

库存数据干净，调节和标准化。收入，申请和价格来自SEC等集中交易所和监管机构。相比之下，加密数据是野外西部。交易所之间的价格不同。数量通常会被夸大 - 根据位报告，2019年报告的加密货币交易量中有95％是假的或非经济的。

Even on-chain data, often touted as a strength of crypto, requires complex interpretation. A token transfer might indicate user activity—or it might be a wash trade or bot movement. An increase in wallet addresses might signal adoption, or just airdrop farming. Parsing meaningful data from noise is a constant challenge.

即使链接数据通常被吹捧为加密的强度，也需要复杂的解释。令牌转移可能表明用户活动，或者可能是WASH贸易或机器人移动。钱包地址的增加可能表明采用或只是耕种。从噪声中解析有意义的数据是一个持续的挑战。

4. Volatility and Market Hours

4。波动和市场时间

Cryptocurrencies trade 24/7, unlike traditional equities, which are limited to business hours and holidays. This constant availability leads to more frequent and sharper price swings. According to Messari, the average 30-day volatility of the top 10 cryptocurrencies is over 80%, compared to 20–30% for tech stocks like Tesla or Nvidia.

与传统股票不同，加密货币交易24/7，这些股票仅限于营业时间和假期。这种持续的可用性导致价格更频繁和更尖锐的价格波动。根据弥赛亚的说法，前十名加密货币的平均30天波动率超过80％，而Tesla或Nvidia等技术股票为20–30％。

This also means that news—be it geopolitical, regulatory, or social—can impact crypto prices at any hour. Traders must monitor global markets round-the-clock, often relying on alert systems, bots, and social media scraping tools to stay informed.

这也意味着新闻（无论是地缘政治，监管或社会）都会在任何时候影响加密货币价格。交易者必须监视全天候全天候的全球市场，通常依靠警报系统，机器人和社交媒体刮擦工具以保持知情。

5. Community and Governance Signals Matter

5。社区和治理信号很重要

Crypto projects often have decentralized governance models. The outcomes of DAO (Decentralized Autonomous Organization) votes or token emissions changes can dramatically alter token value. For instance, Uniswap’s UNI token rose 35% in 2023 after a proposal to direct protocol fees to token holders passed. In traditional equities, shareholder votes rarely drive short-term price movement unless tied to mergers or activism.

加密项目通常具有分散的治理模型。 DAO（分散自治组织）的投票或令牌排放变化的结果可以极大地改变令牌价值。例如，在将协议费用直接向代币持有人的提议通过的提议通过后，UNISWAP的Uni Uni代币在2023年上涨了35％。在传统股票中，除非与合并或行动主义相关，否则股东的投票很少会推动短期价格变动。

Conclusion

结论

Analyzing crypto requires a paradigm shift. Without earnings or physical assets, sentiment, community, and tokenomics matter far more. Social signals often precede price action, making tools like social volume tracking, Telegram scraping, and Twitter analysis essential. While traditional finance leans on balance sheets and comparables, crypto demands a hybrid of behavioral finance, data science, and constant vigilance. Investors entering this space must recognize that what works in equities

分析加密需要范式转移。没有收入或物理资产，情感，社区和代币学，更重要。社会信号通常在价格动作之前，制作社交数量跟踪，电报刮擦和Twitter分析等工具。尽管传统财务依靠资产负债表和可比性，但加密货币要求行为财务，数据科学和持续的警惕。进入此空间的投资者必须认识到，在股票中有效