数据解读KOL喊单效应:加密资产相关回报表现如何?

Odaily星球日报Publicado em 2024-05-16Última atualização em 2024-05-16

Resumo

论文中的集体证据表明,投资者应该谨慎遵循加密货币KOL的投资建议,因为大多数收益在推文发布后不久就消失了。

原文作者:深潮 TechFlow

对韭菜来说,关注各类 KOL 博主的喊单,是获取财富密码的重要来源。

那么 KOL 喊单,是永赚的常胜将军,还是一次次偶然的巧合?

对于这个问题,关注不同的博主有着截然不同的答案。一次 100 倍的的喊单正确,或者一次归零的错误推荐,都可能成为非常主观的幸存者偏差。

从整个行业来看,KOL 们带单最后的战绩如何?

2 月,来自哈佛大学商学院、印第安纳大学商学院和德克萨斯农工大学的几位研究者,共同发表了一篇名为《加密货币影响者》的论文。

文章对截至 2022 年 12 月的两年期间, 180 名最著名的加密货币社交媒体影响者(KOL)发布的约 36, 000 条推文中所提到的加密资产相关回报表现进行研究,涵盖超过 1, 600 种代币。

数据解读KOL喊单效应:加密资产相关回报表现如何?

关键结果

在使用机器学习对推文进行归类,通过多种统计性描述和检验对推文中所提到的代币和之后价格表现进行跟踪后,得到的关键结果如下:

1.加密货币影响者的推文最初与正回报。但这些推文之后出现了显著的长期负回报,这表明它们产生的长期投资价值微乎其微。

2.当具备小币、拥有大量推特粉丝和自称专家这几个要素时,这些推文所产生的上述影响最为明显。

3.论文用机器学习方法对推文进行分类,发现当推文具有更积极的情绪或与「购买」推荐相关时,上述结果模式更强。

数据例证

加密货币影响者的推文呈现积极的短期回报效应:

发推喊单某个币,平均一天(两天)回报率为 1.83% (1.57% )。

市值前 100 名之外的加密货币项目,喊单一天后的回报率为 3.86% 

收益最早开始大幅下降是在推文发布五天后。第二天到第五天的平均回报率为-1.02% ,这表明超过一半的初始涨幅在五个交易日内被消除。

数据解读KOL喊单效应:加密资产相关回报表现如何?

从更长远的角度来看,推文发布后 10 天和 30 天结束的平均累积回报分别为-2.24% 和-6.53%。我们进一步记录了这些负面的事后回报,对于低市值加密货币来说更加负面(其中信息和流动性问题是最严重的)。

粗略估计表明,个人投资 1,000 美元购买在推文日期非前 100 名加密代币并持有投资三十天将产生 79 美元 (7.9%) 的损失,年化损失为 62.8%。

所谓专家:当影响者自称为专家时,事件后的回报率会更加负面;而当这些专家拥有更多的追随者时,回报率会更差。

整体来看,研究结果表明加密货币影响者平均提供的长期投资建议是无利可图的。只有在推文发布后立即退出仓位,才能从中获利,但这种策略可能因为市场流动性不足而不总是可行。此外,这种立即卖出的行为与加密货币社区中「永不卖出」的文化相悖。

思考

论文中的集体证据表明,投资者应该谨慎遵循加密货币 KOL 的投资建议,因为大多数收益在推文发布后不久就消失了。

但文章作者也承认,证据还不是决定性的。加密货币 KOL 可能只是追逐趋势或推广将为他们赢得最大知名度和粉丝的代币,从而使他们在经济上受益。

此外,一种更无害的替代解释是,加密货币影响者确实相信加密资产最终将经历高水平的增长。有影响力的人也可能只是关注建议短期购买并假设投资者知道立即出售。

尽管如此,论文的结果仍然提供了丰富的信息,因为它们提供了明确的证据,表明如果一个人持有的代币超过了几个月甚至几年,那么投资建议就不太可能有用。

同时论文还建议,监管机构和商业媒体可能会促使对此类行为进行更多审查,以确定这些活动是否与更多相关的利益冲突有关。

附录:论文所提及的 TOP 25 推特账号(受论文研究时间影响,表格是 2 年前的排名)

数据解读KOL喊单效应:加密资产相关回报表现如何?

Leituras Relacionadas

Interview with Strategy CEO: Can STRC Recover After Selling Bitcoin?

Interview with Strategy CEO Phong Le on the recent sale of 32 Bitcoin and its impact. He clarifies the move was a small, strategic action to demonstrate liquidity to debt holders, test internal processes, and prove operational discipline—not a response to fears of a "death spiral" from DeFi protocols leveraging STRC (Strategy's preferred stock product), which he notes holds less than 10% of STRC. Le emphasizes Strategy’s long-term focus as the largest corporate Bitcoin holder, using the adage that markets are a "voting machine" short-term but a "weighing machine" long-term. Decision-making is data-driven, involving the board, complex modeling, and multiple stakeholder considerations, moving beyond a founder-centric model. He outlines various capital options but stresses the strategic importance of "doing nothing" as a valid choice, citing resilience built during the 2022 bear market. Le expresses unwavering belief in Bitcoin's foundational value for global sovereignty and its future role in an AI-driven economy with trillions of autonomous agents. Addressing STRC's current price below its $100 face value, Le explains recent pressure was due to using dollar reserves for bond buybacks. He expects STRC to return to par as reserves are replenished and its semi-monthly dividend payments begin, noting the product is heavily over-collateralized. Finally, Le confirms the company sold Bitcoin the week prior to May 31st, as disclosed in an 8-K filing, leaving prediction market interpretations to others. The overarching philosophy remains "Spread Bitcoin with love," embracing all methods of gaining Bitcoin exposure.

marsbitHá 8m

Interview with Strategy CEO: Can STRC Recover After Selling Bitcoin?

marsbitHá 8m

IOSG Founder: Ethereum Doesn't Need Another Leap of Technical Faith, It Needs a Musk-style Compromise

Jocy, founder of IOSG Ventures, argues that Ethereum does not need renewed technological faith but a "Musk-like compromise." The recent formation of ETHLabs—funded by major ETH holders like BitMine and Lubin—highlights a market-driven move to fill a gap left by the Ethereum Foundation (EF), signaling a loss of confidence in its decentralized, hands-off approach. The core critique contrasts Vitalik Buterin's (V) idealistic, technology-first vision with Elon Musk's pragmatic, business-driven execution. The author asserts Ethereum's current shortage is not another technical roadmap but a clear, real-world application narrative and a leader willing to engage directly with commercial realities—like Musk. Internal issues are emphasized, citing EF's management problems and talent drain. While the new decentralized model with independent nodes like ETHLabs addresses the single foundation's limitations, it risks fragmentation without cohesive direction. True cohesion, the author suggests, must come from a shared, compelling narrative around ETH's value, not just from aligned financial interests. Independence claims for new entities are seen as aspirational, needing years of transparency to build trust. The ultimate threat is not competitors like Solana, but the broader shift of attention and talent toward AI. Ethereum has a limited window—12 to 18 months—to recapture focus by delivering tangible, real-world applications. The conclusion urges V to shift from abstract ideals to grounded, pragmatic leadership. The time for this crucial pivot is running out.

marsbitHá 1h

IOSG Founder: Ethereum Doesn't Need Another Leap of Technical Faith, It Needs a Musk-style Compromise

marsbitHá 1h

Google Starts Selling TPUs, Big Tech Aims to Produce "Low-Cost Tokens" with AI Chips

Google has begun selling its proprietary TPU chips and AI computing hardware directly to third-party data centers and clients, marking a strategic shift. Previously only accessible via cloud rentals, TPUs are specialized processors designed for the matrix and tensor operations central to AI models. By combining thousands into supercomputing clusters managed by CPUs, Google achieves high-efficiency AI processing. This move enables Google’s Gemini AI to offer competitive token pricing, challenging rivals like OpenAI. It also signals a broader industry trend where AI compute is becoming a commoditized resource like electricity. While NVIDIA remains dominant with its CUDA ecosystem and high-performance GPUs, the focus is shifting from raw power to cost efficiency and system integration. Google’s approach mirrors NVIDIA’s by selling an entire ecosystem—hardware, software, and data center expertise—rather than just chips. This threatens NVIDIA’s grip on the mid-range inference market, where lower-cost, efficient solutions are increasingly demanded. Similarly, cloud providers like Huawei Cloud and Alibaba Cloud in China are developing their own AI chip ecosystems (e.g., Ascend, Zhenwu), packaging chips, clusters, and tools into full-stack solutions. They aim to reduce token costs and capture market share through integrated systems. In summary, the AI infrastructure race is evolving from a competition for the strongest chips to a contest for the most efficient and cost-effective systems. Google’s TPU sales highlight this transition, emphasizing that future success lies in delivering affordable, scalable AI compute as a foundational service.

marsbitHá 1h

Google Starts Selling TPUs, Big Tech Aims to Produce "Low-Cost Tokens" with AI Chips

marsbitHá 1h

Trading

Spot
Futuros
活动图片