挖出潜力代币:如何用 AI 模型构建市盈率监控系统?

深潮Published on 2025-07-04Last updated on 2025-07-04

教你如何对市盈率进行分析,并借助AI模型构建相应的监控系统。

作者:Hoeem

编译:Tim,PANews

加密领域最被忽视的指标是什么?市盈率(P/E)。它能快速帮你判断:某个币种是被高估还是低估,是暴涨在即还是暗藏风险,是投机潜力股还是泡沫聚集地,更让你看透市场情绪。

这篇文章将教你如何对市盈率进行分析,但首先你需要像专业人士一样理解这个概念。

理解市盈率

1.快速识别高估与低估资产

市盈率 = 每股股价 ÷ 每股收益

  • 这表明投资者愿意为每1美元收益支付的价格

  • 高市盈率 = 市场预期增长(但可能估值过高)

  • 低市盈率 = 可能是价值投资机会或警示信号

2.同类型比较协议方案

用盈利来对类似的公司或加密货币进行排名

  • 项目A市盈率10,项目B市盈率30

  • 相同行业板块,基本面相同?那么A公司估值可能偏低

3.​​用市盈率洞察市场情绪​​

市盈率不仅仅是数字计算,更反映了市场情绪。

  • 高市盈率 = 市场乐观、炒作情绪与增长预期

  • 低市盈率 = 恐惧、疑虑或市场错误定价

4.对收入进行场景分析

原始利润 ≠ 事实真相

  • 市盈率有助于将收入放在行业场景中评估。

  • 这表明市场对每一美元净利润的估值。

5.寻找潜力股或高增长标的

  • 价值投资者非常青睐具有强劲基本面的低市盈率股票。

  • 成长型投资者追逐高市盈率和加速上涨空间。

  • 关键就在于了解市场为什么这样定价

额外建议

市盈率好比速度表,它能告诉你市场消化预期的快慢。但就像速度需要结合场景来解读,估值也要看具体背景才更全面。

如何快速计算加密货币的市盈率

1.访问DeFiLlama

挖出潜力代币:如何用AI模型构建市盈率监控系统?

好的,我现在在 DeFiLlama 上,然后呢?

2.然后去查看“收入”与“费用”页面

挖出潜力代币:如何用AI模型构建市盈率监控系统?

好,我找到这个地方了,下一步呢?

3.选择你要对比的筛选类别

挖出潜力代币:如何用AI模型构建市盈率监控系统?

明白了,我也可以把它们都对比一下,这样比较公平。

4.点击“30天收入”

挖出潜力代币:如何用AI模型构建市盈率监控系统?

是的,找到了。

5.将数据页面截图

挖出潜力代币:如何用AI模型构建市盈率监控系统?

这操作真简单

6.进入能联网的大语言模型网站

挖出潜力代币:如何用AI模型构建市盈率监控系统?

7.输入该提示 + 截图(复制并粘贴在下方)

提示词

你是一名专业的加密货币基本面分析师。

数据收集流程

  • 收入 – 从提供的DeFiLlama截图中提取协议30天收入(美元)。使用OCR技术;忽略任何收入为空或收入≤0的条目。

  • 市值与全稀释估值——从CoinGecko或CoinMarketCap获取实时数据(尽量使用当日数据)。通过代币符号匹配,若协议缺少任一数据则跳过。

  • 分类聚焦——仅考虑用户指定的DeFiLlama类别(例如:去中心化交易所DEX、借贷协议Lending、流动性质押代币LST、永续合约Perps等)。

  • 过滤和筛选

  • 筛选方案时市盈率<0或>1000不予采用

  • 计算市盈率 = 市值 ÷ (30天营收 × 12)。

  • 返回市盈率最低的20个项目(即最被"低估"的)。

  • 对于每一个项目,同时计算“收入与完全稀释估值比率” = (30天收入 ÷ FDV)× 100%。

  • 输出:生成一个整洁的Markdown表格,按市盈率升序排列,并额外添加首行显示最终列表的平均市盈率和平均营收与完全稀释估值占比。

  • 将数字缩写为K/M/B格式以提高可读性。

列设置:

1.协议名

2.代币符号

3.P/E

4.30天收入(美元)

5.流通市值(美元)

6.全稀释市值(美元)

7.所属链

8.简单介绍

9.营收与全稀释估值比率(%)

质量检查,确保:

1.营收与全稀释估值同时呈现。

2.根据DeFiLlama的分类标签正确。

3.当前数据为最新(来自CoinGecko或CoinMarketCap的抓取数据更新不足48小时)。

4.表格易于浏览,无缺失值。

目标:帮助加密货币投资者通过核心指标(市盈率和收入/完全稀释估值比率),在选定赛道中快速发现潜在价格偏离的代币。

例子:

挖出潜力代币:如何用AI模型构建市盈率监控系统?

比较流通市值与完全稀释估值,同时关注近期是否有代币解锁也很重要。

那么,好了,你现在已经明白如何运用市盈率,并且知道如何找出市盈率了。

Trending Cryptos

Related Reads

Hacker Leaks GTA6 and Launches a Token: Leaked Videos Become Ad Space for $CYBERLEEK, Must Buy Tokens to Vote for Next Clip

A hacker group called "CyberLeek" has leaked gameplay footage of the highly anticipated video game *GTA 6*, which is slated for release in 2026. Simultaneously, the group launched a meme token, $CYBERLEEK, on Solana. The leaks, which include maps and gameplay clips, are heavily watermarked with advertisements urging viewers to buy the token. Investigations of blockchain data reveal that the token was created and funded from a single wallet approximately eight hours before the first leak was released, suggesting a coordinated plan. The group has implemented a voting system where token holders can "vote" for the next type of content to be leaked by sending $CYBERLEEK tokens to a designated wallet—a process that permanently transfers the tokens to the hackers. This creates a self-sustaining cycle where interest in the leaks drives token purchases. Financially, the operation involved minimal upfront costs (less than $3,500 in out-of-pocket expenses) but generated significant revenue. On its first day, the token saw $15 million in trading volume, netting the creators an estimated $30,000 from transaction fees alone. While the group later burned a large portion of its developer-held tokens (worth over $1 million) to build trust, the fee-generating mechanism remains intact. The game's publisher, Take-Two Interactive, has initiated legal proceedings to identify the hackers. Despite this, the case demonstrates a new model where leaked intellectual property is used as leverage to promote and profit from a cryptocurrency, with meme token markets serving as an additional revenue stream.

marsbit12m ago

Hacker Leaks GTA6 and Launches a Token: Leaked Videos Become Ad Space for $CYBERLEEK, Must Buy Tokens to Vote for Next Clip

marsbit12m ago

Jensen Huang's Daughter: From Chef to an $8 Million Annual Salary

Madison Huang, daughter of NVIDIA founder Jensen Huang, recently made a rare public appearance in Beijing during the 2026 World Robot Conference. As the Senior Director of Product and Technology Marketing for NVIDIA's Physical AI Platform, with an annual salary of approximately $1.2 million, her visit focused on evaluating leading Chinese robotics companies like UBTech, Unitree, and others. This highlights NVIDIA's strategic interest in the burgeoning Chinese robotics ecosystem, a key battleground for the development of Physical AI—technology that enables machines to understand and interact with the physical world. Huang's career path is unconventional. Initially pursuing her passion, she studied culinary arts, worked as a chef, and later held a marketing role at LVMH. She joined NVIDIA as an intern in 2020 after completing an MBA, quickly rising through the ranks. Her brother, Spencer Huang, followed a similar path, closing a cocktail bar he co-founded to also join NVIDIA, where he now works on robotics software. Jensen Huang has publicly addressed nepotism concerns, humorously noting that some "second-generation" employees outperform their parents. The conference itself underscored China's vibrant robotics sector, marked by Unitree's recent blockbuster IPO and a pipeline of companies preparing to go public. While hardware development and manufacturing are advancing rapidly, industry leaders like Wang Xingxing of Unitree point to the next critical challenge: developing the "brain" or AI that allows robots to perform diverse, unseen tasks based on simple instructions. With massive manufacturing scale and diverse real-world testing scenarios, China is positioned as a central player in the global race to define the future of robotics.

marsbit2h ago

Jensen Huang's Daughter: From Chef to an $8 Million Annual Salary

marsbit2h ago

He Gave Wang Xingxing the First 2 Million, Now Serves as Chairman for the Next 'Unitree'

On August 19, 2024, Unitree Robotics, China's "first humanoid robotics stock," went public. Its founder, Wang Xingxing, started a decade ago with his self-developed XDog. In 2016, at a critical funding juncture, he received his first angel investment of 2 million RMB from Yin Fangming. This bet has since yielded a return of over 140 times. Yin Fangming is more than just a key investor. He was a co-founder of the AI robotics company ROOBO, whose own venture ultimately struggled. This firsthand experience with the hardware challenges in robotics gave him unique insight when backing Unitree, a company renowned for its hardware R&D and cost control. While his own company faltered, Yin continued investing shrewdly. He partially cashed out some Unitree shares early, reinvesting the proceeds into sectors like energy (e.g., solid-state battery firm TaiLan) and commercial aerospace (e.g., small launch vehicle developer XianDeng Aerospace). However, his most significant move after Unitree is his deep involvement with Galaxy General, a leading embodied AI unicorn. In July 2024, Yin stepped from behind the scenes to officially become its Chairman, indicating a role far beyond a typical investor. This comes as Galaxy General is viewed as preparing for future capital moves. Yin's career has consistently been ahead of the curve—from mobile internet to AI and robotics. Known for his foresight and low profile, he declined an interview for this story, offering only a statement encouraging support for visionary entrepreneurs like Wang Xingxing.

marsbit3h ago

He Gave Wang Xingxing the First 2 Million, Now Serves as Chairman for the Next 'Unitree'

marsbit3h ago

Coldcard Theft Reflection: Source Code Visibility Does Not Equal Security

The article examines the open-source vs. closed-source debate in crypto, prompted by a theft of over $100M in Bitcoin from Coldcard hardware wallets. It clarifies key terminology: true "Free and Open Source Software" (FOSS) grants four essential freedoms (use, study, share, modify), while "source available" code, like Coldcard's firmware, may have usage restrictions. The piece argues that visible source code alone does not guarantee security; actual safety depends on the economic incentives for thorough, ongoing review by skilled individuals. Using Bitcoin Core as a model, the article describes a successful, transparent open-source development culture built on public review and consensus. It contrasts this with the Coldcard case, where a critical bug in a lightly-reviewed, source-available library went undetected for years, highlighting a "tragedy of the commons" scenario where assumed but absent scrutiny creates vulnerability. The economics of licensing are crucial: restrictive licenses can limit the pool of motivated commercial reviewers. Finally, the article explores AI's impact. It cites the Bitcoin Red Team's use of AI to rapidly audit codebases and find vulnerabilities at scale, demonstrating a powerful new tool for security. However, AI also floods projects with low-quality code, straining maintainers. The piece concludes that in high-stakes crypto, only well-audited projects—whether open or closed-source—can withstand evolving threats, with AI both challenging and aiding security practices.

marsbit3h ago

Coldcard Theft Reflection: Source Code Visibility Does Not Equal Security

marsbit3h ago

Trading

Spot

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of AI (AI) are presented below.

活动图片