Consensys 高管:别傻乎乎盯着 CT 了,能明说的大概不是 Alpha

深潮Published on 2024-07-23Last updated on 2024-07-23

Crypto Twitter(CT)是一头猛兽。

撰文:Matt Gilmour,ConsenSys 企业发展部经理

编译:Yangz,Techub News

Crypto Twitter(CT)是一头猛兽。在与其相处多年后,我逐渐了解了它的作息,但更重要的是,我意识到了它是如何「逼迫」着我与它一同行动的。

了解事物的本质,而不是人们希望它成为什么,是关键所在。就 CT 而言,理解了它的本质,也就理解了游戏的核心,只有这样,我们才算真正入局。

何为 CT

Crypto Twitter 与罗夏墨迹测验(一种利用墨迹对人格进行的测验)类似,你想看到什么,它就会变成什么。对于 degens 来说,它就像一个赌场,满是 meme 和各种形式的 shitposting;而对新手来说,CT 上充斥着各种阿尔法,也有很多自愿分享投资理念,看似善意的「大佬」;至于经验稍微丰富一些的投资者,情况会有微妙变化,他们认为 CT 上多是市场投资老手及声誉良好的风险投资家看似透彻且系统的投资论述。

然而,请别误会,以上所有印象都只是罗夏测验带来的误导。当人们摘下 CT 的罗夏「面具」,其本来面貌不过是混乱不堪的「污水池」。CT 上有(有时)存粹的市场评论,也有(多数情况下)令人作呕的投资背书。最终形成的一连串无用且有害的噪音,使得投资信号几乎不可能从这发出。

为什么 CT 无用

世上并无全知

有什么证据能表明 CT 上的人什么都知道?的确,有的投资者可能在前几轮周期中取得了成功。但牛市嘛,总有那么几个成功的。就像《随机致富的傻瓜》(Fooled by Randomness)中的高收益交易员 John,这些投资者靠着运气成功,但同时也面临着财务破产的危机。

那么,那些获得大额风投的项目创始人呢?人们总觉得他们肯定知道些什么。但是,不妨思考一下,为什么融资会在 CT 上受到高度重视?他们又是如何融到资的?在很多情况下,投资机构会根据其过往的成功经历,期望他们再次成功并从中获利。就像刚才说的,在多数情况下,他们的成功除了幸运之外,再无其他。

需要强调的是,我并不是主张所有的投资成功都依靠运气,我只是想说所有的投资成功都是运气和技术的结合,而要区分这二者几乎是不可能的(关于这一点,Nassim Taleb 已经在《FBR》中进行了阐述,我就不再赘述了)。

CT 上并无阿尔法

撇开「运气」与「技术」不谈,我们有可能在推特上找到阿尔法吗?根据定义,阿尔法是相对于基准的超额收益。要实现这一点,投资者就必须先于他人了解未来可能发生的情况。因此,从定义上讲,在 CT 上发现的东西就不可能是阿尔法。当所谓的阿尔法出现在你的 CT 上时,这一信息极有可能已经传遍了大街小巷,你在承担巨大风险的同时,或许只能获得极少的回报。记住,所有被大声公开的阿尔法都会变成贝塔。

与「旅鼠」为伍

即使 CT 上有些许价值可寻,但投资者的情绪波动会非常剧烈。在这种情况下,要想时刻保持自己的投资理念也是异常困难的。也许前一天每个人都是亢奋的,但第二天就可能全颓了。或许你打心底里知道这一点,但终究逃不过「旅鼠式情绪」的影响。最终,你也会变成 CT 上的一只「旅鼠」。

怎么办?

无需他人告知,渴望成功投资,且深刻明白自己正身处毫无阿尔法可言的「污水池」中的投资者,会主动离开 CT。这就好比不需要告诉别人不要突然闯到马路中间一样。然而,尽管这一理念特别容易理解,但其隐含的意思可能没有人们想象的那么简单。

从理性角度来看,要了解混迹 CT 的后果并不难。更难(也是必要的)的是,个人真正想要什么,真正的愿望是什么。

如果跟随 CT 的必然结果是低质的收益回报,那么渴望投资成功的人为什么还要混迹在 CT 上呢?答案是,他们实际追求的就不是什么投资回报,他们真正的目的并不在此。

有人会问,「在有高投资回报可能的情况下,人们怎么会希望获得较低的回报?」

因为在获得低质回报的背后,他们真正追寻的是别的东西。有人追寻正确性,娱乐性,也有人渴望社区,渴望成为共识的一部分,还有人寻求自我抚慰,为自己的愤怒找到出口,又或享受自怜。虽然混迹 CT 的人们的愿望各不相同,但事实是,优厚的回报可能并不全是他们最大的愿望。

此外,CT 如此受欢迎的另一个原因是,人们对自己「一定能在 CT 上找到阿尔法」的坚信,他们相信「虽然现在还没有找到阿尔法,但将来一定能找到」。人类就是这样浪费自己的一生的,不管是与 CT 有关,还是在其他方面。

追求低回报不是错,追求高回报也不一定对。自我评判就像一条死胡同,应该和不应该都不会再有回应。简单来说,一个人开始深入探究自己的欲望时,并不是因为他们应该这样做,而是因为他们已经认识到,他们目前追寻的必然导致失败。而且,无论他们打开多少盒子,追随 CT 付出多少努力,其结果都只能是失败。由于目标不同,彼之砒霜也可以是汝之蜜糖。所谓的「砒霜」将推动投资者踏上新的旅程。在这趟旅程中,他们将认识到世界级投资回报的真正所在,而 CT 上绝对找不到答案。

Related Reads

History's Only Asset with a 100% Win Rate After 4 Years of Holding

**Title: The Only Asset with a 100% Win Rate Over Any 4-Year Holding Period** This article analyzes which major, freely-tradable assets have historically never produced a nominal loss over any rolling 4-year holding window. It concludes that only two distinct categories achieve this: ultra-low-risk contractual assets and Bitcoin. Among traditional risk assets, none maintain a perfect 4-year record. The S&P 500 had negative 4-year periods (e.g., 1929-1932: -64.8%). The Nasdaq 100 fell roughly 60% from 2000-2003. Gold saw a ~47.7% loss from 1981-1984. US real estate declined about 23.3% from 2007-2010. Even long-term US Treasury bonds (e.g., 2021-2024: -19.8%) and corporate bonds can produce 4-year losses due to interest rate and market price risks. In contrast, the first category achieving 100% nominal success includes assets like rolling 3-month US Treasury Bills, 4-year certificates of deposit (CDs), and US Treasuries held to maturity within 4 years. Their "guarantee" stems from contractual obligations and credit backing (e.g., FDIC insurance, US sovereign promise), not price appreciation. The sole exception in the high-risk category is Bitcoin. Analysis of daily data from 2010-2026 across 4,419 rolling 4-year windows shows a 100% positive return rate. The worst 4-year period (April 2021 to April 2025) still yielded a +32.6% total return (~7.3% CAGR). This record is unique because Bitcoin has no issuer, promises no cash flows, and has endured severe drawdowns (70-90%), yet its market price has always recovered within a 4-year span. The key distinction is the source of the "100%": contractual assets offer known, low nominal returns, while Bitcoin's record stems purely from historical price appreciation despite extreme volatility. The article suggests that for Bitcoin, the ability to hold for 4+ years is more critical than active trading strategies.

marsbit6m ago

History's Only Asset with a 100% Win Rate After 4 Years of Holding

marsbit6m ago

How One Article Moved 45 Billion: The Collapse of a 25-Year-Old 'AI Stock Guru'

This article details the dramatic rise and near-collapse of a hedge fund built by Leopold Aschenbrenner, a 24-year-old former OpenAI researcher. The fund, named Situational Awareness, amassed $45 billion in assets within two years. Its explosive growth stemmed from Aschenbrenner's influential 165-page manifesto predicting AGI's arrival by 2027 and his high-profile Silicon Valley connections. The fund employed an extremely aggressive strategy: high concentration and 400% leverage to bet long on AI infrastructure stocks while shorting legacy software firms. In July, this structure backfired when both sides of the trade reversed simultaneously—AI stocks plunged while shorted stocks rallied—triggering massive losses that nearly wiped out all equity. Major player Jane Street reportedly lost billions. The fund's leveraged public portfolio was ultimately sold at a discount to Citadel. The SEC is now investigating banks like Goldman Sachs for their role in facilitating the fund's high-leverage trades. The article compares this to past blow-ups like Archegos, highlighting systemic failures in risk management where the pursuit of short-term profits overrode due diligence. It questions whether such risky leverage concentrated in the AI sector, currently at record highs, poses a broader systemic threat. Ironically, Aschenbrenner, who studied AI safety at OpenAI, designed a fund structure prone to uncontrolled failure. Days after the crisis, he reportedly raised another $400 million for new investments.

marsbit20m ago

How One Article Moved 45 Billion: The Collapse of a 25-Year-Old 'AI Stock Guru'

marsbit20m ago

AI Accelerates Everything: Mathematics's Line of Defense Has Fallen, Physics is Already in AI's Crosshairs

This summer, the mathematics community was shaken as OpenAI's Astra model reportedly solved 10 long-standing open problems, and Claude Fable 5 found a potential counterexample to the Jacobian conjecture. This was followed by a major shift in physics: renowned physicist Gavin E. Crooks presented an open problem in stochastic thermodynamics to Claude, which the AI solved completely in days—a task that might take a skilled graduate student months. The problem concerned constraints on entropy production statistics under the Detailed Fluctuation Theorem (DFT), a core concept in non-equilibrium physics. Claude provided a unifying geometric answer: all possible DFT-compatible distributions correspond to a convex "moment body." Its key insight was that for a fixed "gap," the distribution is uniquely determined, making any general DFT distribution a mixture of these basic two-outcome distributions. This structure implies that for given lower-order moments, the nth moment only has a sharp lower bound, with no upper bound. Claude demonstrated that numerous previously published bounds on entropy production are merely low-dimensional projections or "shadows" of this single, unified convex body. The AI-authored paper offers a complete hierarchical characterization of the moment constraints. This case signifies a potential paradigm shift: AI is progressing from solving known problems to aiding in the exploration of fundamental, unsolved scientific questions, heralding an AI-accelerated era for physics.

marsbit20m ago

AI Accelerates Everything: Mathematics's Line of Defense Has Fallen, Physics is Already in AI's Crosshairs

marsbit20m ago

Trading

Spot
活动图片