저자: TomLee · 외국인
요약 보기
Tom Lee는 비트코인이 12개월 내 25만 달러에 도달할 수 있다고 주장하며, 이더리움은 BTC/ETH 비율 회귀 시 약 1.2만 달러, 2021년 고점 비율 시 2.2만 달러, 글로벌 결제 정산층이 되면 6.2만 달러까지 가능하다고 본다. 근거로 전쟁 중 이더리움 3개월 연속 상승, 2016년 5천 달러 투자의 막대한 수익률, 스테이블코인 거래량이 비자 결제량을 상회한 점, 토큰화 자산 시장 확대(Grayscale 3백조 달러 추정)를 든다. AI 에이전트의 프로그래머블 머니 수요와 JP Morgan·Jane Street·Tether의 직원 대비 수익성을 들어 향후 10년 내 대형 금융사 절반이 디지털 자산 기업이 될 것이라 주장한다. 영상 중간에 하드웨어 지갑(BitBox02) 광고가 포함되어 있다.
다듬은 글
Tom Lee is calling Bitcoin at $250,000 within the next 12 months. And if that plays out, he says Ethereum follows it to somewhere between $12,000 and $62,000, depending on how much of the global financial system moves onto blockchain rails in the years ahead. Now, those aren't casual numbers. Lee is building a case that the crypto winter is already behind us.
That Ethereum has been outperforming as a wartime store of value while most people were focused elsewhere. And that the next leg of this cycle is going to be driven by something much bigger than speculation. He's talking about trillions of dollars in real world assets, bonds, real estate, and equities moving on chain and an entirely new category of economic actor, autonomous AI agents, that will need programmable money to function at all.
The argument connects Bitcoin's trajectory to Ethereum's positioning in a way that is specific enough to be worth sitting with properly. So, today we're going to walk through exactly what Lee laid out, the historical data he's leaning on, the macro forces he believes are already in motion, and what it all points to for where both Bitcoin and Ethereum are headed from here.
Let's get into it. So, let's start with why three months consecutively. three . Lee made a bold claim about crypto winters. He says that in the entire history of crypto, there has never been a case where Ethereum closed up three consecutive months during a crypto winter. Every previous crypto winter ended without Ethereum managing three consecutive months of positive closes.
The fact that it has now done exactly that during a period when the US is actively engaged in a geopolitical conflict with Iran and most retail participants are still sitting on the sidelines is what makes him confident enough to call it. The conflict context matters more than people are giving it credit for.
Conventional thinking would say that wartime uncertainty is bad for risk assets, but Ethereum has been rising through that uncertainty, which tells you something about what kind of asset it is becoming in the eyes of the people who are actually allocating serious money right now. It's behaving less like a speculative token and more like something people reach for when they want to store value outside of a system that feels unstable.
That shift in behavior, if it holds, changes the entire conversation about where Ethereum fits in a portfolio. But, here's what a lot of people miss about that conversation. It doesn't matter how well Ethereum or Bitcoin perform if you're not the one holding them when it counts. Every time we've seen a crisis shake this market, the people who got hurt worst weren't the ones who picked the wrong asset.
They were the ones who left the right asset on the wrong platform. That's why I use the BitBox02. It's audit just launch Lee's right that we're entering the next major leg of this cycle, the simplest thing you can do to protect your position is make sure it's actually yours. BitBox makes that easy. First link in the description for 5% off.
Now, Lee doesn't stop at calling the bottom. His next argument is about what the upside actually looks like, and he builds it on a specific piece of math that connects Bitcoin's trajectory directly to Ethereum's price. rd o, if you had a $ had add ; A $5,000 allocation into Ethereum at the end of 2016, which would have been just 5% of a $100,000 portfolio, grew to over a million dollars.
The total portfolio with that single allocation ended up at roughly 1.7 million compared to $230,000 for someone who held nothing but traditional assets over the same period. That's not a marginal difference. That's a completely different financial outcome produced by a single decision about allocation size.
Now, he made a hedging comparison against gold. To protect yourself against a 50% collapse in the S&P 500 using gold, you would have needed to park more than a third of your entire portfolio into it. To achieve the same protection using Ethereum, the figure was around 4%. There's actually a gap there.
Gold moves slowly, and its upside is capped by its own nature as a physical commodity. Ethereum, because of how dramatically it can move to the upside, provides asymmetric protection in a way that gold simply cannot replicate at small allocation sizes. Now, Ethereum does track Bitcoin. So, I think you should look at the price ratio, and the current price ratio is below not only the 8-year average, but the 2021 high at 0.087.
And we you've seen this chart from us before. , a gigantic AI. So, let's talk about the future of money. Now, Elon Musk said something pretty profound recently. He says that this future system won't use dollars as currency, just mass and energy. What he's really referring to is that compute and energy are the two scarce assets.
In fact, Larry Fink a BlackRock believes that compute will actually become a new asset class and that we'll be buying futures of compute. Reid Hoffman, the billionaire founder of LinkedIn, said that crypto will become critical in an AI world. Ethereum and Bitcoin have a price ratio, meaning how much one Ethereum costs relative to one Bitcoin.
And that ratio has averaged a certain level over the last eight years. Right now, that ratio is sitting below both the eight-year average and the peak it hit in 2021. Lee's framework is simple. If Bitcoin reaches $250,000, which he considers fair value at this stage of the institutional adoption cycle, and the Ethereum to Bitcoin ratio just returns to its eight-year average, Ethereum lands at around $12,000.
If the ratio climbs back to where it was at the 2021 peak, you get to $22,000 Ethereum. And if Ethereum becomes the actual settlement layer for global commerce and AI transactions, the number he puts on that scenario is $62,000. What makes this framework useful is that it separates the Bitcoin thesis from the Ethereum thesis while keeping them connected.
You do not have to believe in the $62,000 scenario to find the base case interesting. Even the most conservative reading of his model, the simple mean reversion of the price ratio, produces a number that represents substantial upside from where Ethereum is trading today. The historical consolidation data he references , Ethereum moved more than 200 times from its base.
After 2020, it moved roughly 50 times. The current consolidation has been running for 5 years, which by historical standards is the longest Ethereum has ever spent building a base before a major move. Lee believes the next leg , and that's exactly where his argument goes next. Well, let's think about stablecoin transactions, which we had said last year was the chat GPT moment for crypto.
And you can see stablecoin volumes now exceed Visa payments. This is according to data from Bitwise. And Grayscale believes that the tokenized market is going to reach 300 trillion dollars as we tokenize , commercial real estate, basically everything. What does this mean for layer one blockchains? Well, this is Ethereum, which is in pink, and the total value locked of tokenized assets, and you can see Ethereum moves pretty closely with that tokenization.
Meaning that, according to Grayscale, networks that host a large share of tokenized activities may capture a meaningful portion of economic value. In other words, if Ethereum is the leading tokenization platform, its price will go up a lot. And uh Marc Andreessen, who's a very visionary about the future, says the grand unification of AI and crypto are age AI agents cuz they're going to need money.
And we've talked about this before that there's numerous reasons why blockchains are a better way for AI agents to use money. Okay. Well, let's bring this all together. If tokenization is the future of assets and money's becoming digital and AI agents are going to use money, well, we should think about what it means for the most profitable banks in the future.
Well, today JP Morgan is the most profitable bank in the world with 59 billion of net income projected this year, almost 60 billion, and 300,000 employees. But let's mix in two new types of companies, Jane Street, which just is a trading firm, and Tether. Jane Street's on track to make $40 billion this year with 3,000 employees, 1/1000 the number of employees of JP Morgan.
In fact, Jane Street in the first quarter of this year is reporting about 10 billion in net income. That means moving money, which is what Jane Street does, is starting to capture more value than the entire operations of a global bank. Again, going back to this chart, Jane Street makes more money than Bank of America, Wells Fargo, Citigroup, Morgan Stanley, and Goldman Sachs.
Okay. And then let's look at Tether, which is the largest stablecoin operator in the world. It's going to earn about 15 billion this year with 300 employees. So, 1/1000 the number of employees of JP Morgan. These are two new types of financial institutions. Didn't exist 20 years ago. But keep in mind, that's sort of the story that technology as it gets introduced to sectors, creates disruption, and it reduces the value of incumbency.
Now, I'm going to highlight a bunch here. Automobiles. We don't remember any of the horse buggy makers. We only think of the new entrants. With mobile, all these old names really largely don't exist. It's mostly mobile today. In digital media, nobody really remembers names like Hearst, Viacom, News Corp as the giants.
They were the giants in their day. Today, it's more Google, Meta, and TikTok. Even more recently, cloud computing. Before cloud computing, there were PC names, IBM, Compaq, Dell, Gateway. They've given away to Amazon, Microsoft Azure, Oracle, Google Cloud. And finally, in EVs, these traditional auto makers are still around, but Tesla is far bigger.
So, markets tend to overestimate the value of incumbency. And it's really the new entrants that capture a lot of that value. Well, what does that mean? I believe in the next 10 years, half of the largest financial institutions in the world are going to be native digital companies, native digital asset companies.
Many of them in crypto. What Li is basically describing is a structural shift in what money is and who controls it. The data points he's using to support it are not theoretical. Stablecoin transaction volumes have already crossed what Visa processes annually. That already happened. Grayscale's research puts the total addressable market for tokenized real-world assets at $300 trillion as bonds, equities, real estate, and derivatives move on chain.
And the Ethereum network has been tracking that tokenization growth closely, meaning as more real-world value moves onto blockchain infrastructure, Ethereum's total value locked has moved with it. The AI agent argument is the one that tends to get the least attention, but may carry the most long-term weight.
Andreessen Horowitz framed it clearly. AI agents are going to need money. These are autonomous systems that book, compute, pay for data, license APIs, and transact at speeds and volumes that human-initiated payment systems were never designed to handle. Visa processes transactions in seconds for humans making deliberate purchasing decisions.
AI agents running at machine speed across thousands of simultaneous tasks need something programmable, permissionless, and instant. Blockchain infrastructure is the only payment rail that currently fits that description, and Ethereum is the dominant smart contract platform by total value locked. The disruption argument Li closes with is where the macro picture snaps into focus.
JP Morgan is the most profitable bank in the world with nearly $60 billion in projected net income this year and 300,000 employees. Jane Street, a trading firm that essentially did not exist in its current form two decades ago, is on track to generate $40 billion dollars year with 3,000 people. Tether, the largest stablecoin operator in the world, is projected to earn around $15 billion this year with just 300 employees.
These companies are producing bank-level profits with a fraction of the head count because they are operating on digital infrastructure that removes entire layers of the cost structure that traditional banking cannot shed. Lee's conclusion from this is that within the next 10 years, half of the world's largest financial institutions will be native digital asset companies built from the ground up inside this ecosystem the way Tether and Jane Street were, rather than traditional banks trying to retrofit blockchain onto legacy systems.
That pattern has played out in every major technology transition before this one. The horse-drawn carriage makers did not become automobile companies. The PC hardware giants did not become cloud companies. The incumbents who survived those transitions did so partially, not completely. The new entrants captured the majority of the value being created.
Lee is arguing that finance is the next industry where that dynamic runs its course, and that Bitcoin and Ethereum are the foundation assets sitting underneath the companies that will define what that new financial system looks like. Now, the case Tom Lee is making is not built on sentiment or cycle optimism alone.
The historical pattern around Ethereum's consecutive monthly closes is real data. The portfolio math around what a small allocation has done over the last decade is verifiable. The stablecoin volume crossing Visa is documented. The tokenization buildout is happening at institutions that were dismissing this entire space just a few years ago.
Bitcoin at $250,000 and Ethereum somewhere between $12,000 and $62,000 are the destinations Lee is pointing to. And the road he has drawn to get there runs through tokenization, AI agents, and a slow collapse of the cost advantages that traditional banking has taken for granted for a century. Whether the timeline holds and whether Ethereum specifically captures the dominant share of that value as competing networks continue to develop are the real questions that the next two to three years will answer.
But the direction Lee is pointing and the structural forces he's pointing to are already in motion. The data has been moving for a while now. The narrative is just starting to catch up. That is all for today. Share your thoughts in the comments, and see you in the next one.
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