了解分析加密資產和傳統金融市場之間的差異

近年來，加密貨幣市場已經迅速成熟，截至2025年5月，全球市值超過2.5萬億美元。

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.

近年來，加密貨幣市場已經迅速成熟，截至2025年5月，全球市值超過2.5萬億美元。但是，儘管規模範圍，分析加密貨幣資產與分析股票，債券或商品的分析根本不同。這些差異不僅是學術，它們對試圖理解加密市場的投資者，商人和研究人員產生了真正的影響。缺乏內在的估值錨，情感的主導地位以及數據的分散只是將加密貨幣與傳統金融分開的一些因素。

1. No Real-World Benchmarks or Earnings

1。沒有現實世界的基准或收益

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.

根據業務基本原理評估傳統股票：收入，利潤率，現金流量和估值比率，例如P/E（市值）或EV/EBITDA。例如，蘋果公司（AAPL）報告說，2024年的收入為3830億美元，市盈率徘徊在28個左右，這是結合其估值的結合數據。

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，大多數加密貨幣都缺乏收益，現金流量甚至使用一致的用法指標。例如，比特幣沒有資產負債表或損益表。以太坊的確從網絡使用中產生了費用收入，在2024年通過EIP-1559燒毀了超過17億美元的ETH，但該數字大大波動，與公司的收入不直接相提並論。對於較新的或較低的硬幣，即使是基本的採用指標，例如日常活躍用戶或交易量通常都不存在或不可靠。

2. Sentiment Plays a Larger Role

2。情緒扮演更大的角色

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.

在加密貨幣中，情緒通常是價格變動的主要驅動力。由於沒有固定估值的內在收入，敘述和公眾的看法就成為中心。 Twitter，Telegram，Discord和Reddit等社交媒體平台作為實時情感指標，通常比鏈上數據或基本更新更明顯地轉移價格。

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的一項2023年的研究發現，在Twitter活動中的尖峰之後，在前100名加密貨幣資產中，短期價格上漲了67％。諸如Doge和Shib之類的模因僅在病毒模因上集結了數百％。埃隆·馬斯克（Elon Musk）在推特上發了一個字 - “多吉”之後，2021年4月猛增了500％。類似的例子比比皆是：2024年，佩佩（Pepe）和Wif幾乎沒有效用，純粹是在社區炒作和影響者促進的後面，達到了十億美元的市值。像Bitlenz這樣的社區排名工具可以通過社交媒體上提到的頻率來浮出水面最活躍的加密項目。

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

這與股票市場形成鮮明對比，股票市場的收入電話和季度報告的重量要比社交媒體的嗡嗡聲要大得多。

3. Data is Fragmented and Unstructured

3。數據是零散的和非結構化的

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.

庫存數據乾淨，調節和標準化。收入，申請和價格來自SEC等集中交易所和監管機構。相比之下，加密數據是野外西部。交易所之間的價格不同。數量通常會被誇大 - 根據位報告，2019年報告的加密貨幣交易量中有95％是假的或非經濟的。

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.

即使鏈接數據通常被吹捧為加密的強度，也需要復雜的解釋。令牌轉移可能表明用戶活動，或者可能是WASH貿易或機器人移動。錢包地址的增加可能表明採用或只是耕種。從噪聲中解析有意義的數據是一個持續的挑戰。

4. Volatility and Market Hours

4。波動和市場時間

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.

與傳統股票不同，加密貨幣交易24/7，這些股票僅限於營業時間和假期。這種持續的可用性導致價格更頻繁和更尖銳的價格波動。根據彌賽亞的說法，前十名加密貨幣的平均30天波動率超過80％，而Tesla或Nvidia等技術股票為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.

這也意味著新聞（無論是地緣政治，監管或社會）都會在任何時候影響加密貨幣價格。交易者必須監視全天候全天候的全球市場，通常依靠警報系統，機器人和社交媒體刮擦工具以保持知情。

5. Community and Governance Signals Matter

5。社區和治理信號很重要

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.

加密項目通常具有分散的治理模型。 DAO（分散自治組織）的投票或令牌排放變化的結果可以極大地改變令牌價值。例如，在將協議費用直接向代幣持有人的提議通過的提議通過後，UNISWAP的Uni Uni代幣在2023年上漲了35％。在傳統股票中，除非與合併或行動主義相關，否則股東的投票很少會推動短期價格變動。

Conclusion

結論

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

分析加密需要範式轉移。沒有收入或物理資產，情感，社區和代幣學，更重要。社會信號通常在價格動作之前，製作社交數量跟踪，電報刮擦和Twitter分析等工具。儘管傳統財務依靠資產負債表和可比性，但加密貨幣要求行為財務，數據科學和持續的警惕。進入此空間的投資者必須認識到，在股票中有效