저자: CathieWood · 외국인
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비트코인 2025년 10월 플래시 크래시는 바이낸스 소프트웨어 오류 기인 디레버리징(약 280억 달러 손실)이며 대부분 해소됐다고 봄. 4년 주기 하락장 탈피 여부가 핵심이며 8~9만 달러대에서 바닥을 다질 수 있으나 다음 변곡점은 상승으로 판단. 스테이블코인이 송금·신흥국 역할을 가져갔지만 비트코인의 디지털 금 역할은 여전하고 금과의 상관관계는 0.14로 낮음. AI 데이터센터 투자 사이클은 약 5000억 달러에서 2030년 1.4조 달러로 증가 전망, 실제 GPU는 활용 중이라 닷컴 버블 광섬유와 다름. 2030년까지 실질 GDP 성장률이 7% 이상으로 가속될 것으로 봄.
다듬은 글
And I think the main question on uh Bitcoiners minds is okay, are we finished with the traditional 4-year downdraft? Every four years a downdraft in uh the cycle. Uh we're beginning to think we are uh although we could base here in the 80 to90 uh,000 range for a while, but we do believe the next inflection is up.
Kathy Wood begins by addressing the turbulence in Bitcoin markets over the past year, particularly the draw down following the October flash crash. She attributes much of that carnage not to a collapse in fundamentals, but to a software glitch reportedly at Binance that triggered automated deleveraging across the crypto ecosystem.
That forced liquidation wiped out an estimated 28 billion dollar in value, creating what looked like a catastrophic market breakdown. In her view, the bulk of that deleveraging has now worked its way through the system. The key question for Bitcoin investors, she argues, is whether the asset has finally escaped the traditional 4-year boom and bust cycle that has defined its histor.
It's been controversial this year because uh we had the draw down after the flash crash 1010 uh in October. Uh we think that a lot of the deleveraging associated with really that was a software glitch I think at Binance uh that that deleveraging automated deleveraging um caused 28 billion dollars of carnage.
uh we think we've worked through that now and I think the main question on uh Bitcoiners minds is okay are we finished with the traditional 4-year downdraft every four years a downdraft in uh the cycle uh we're beginning to think we are uh although we could base here in the 80 to90 uh000 range for a while but we do believe the next inflection is up.
And while I know I got we got a lot of publicity this year because we talked about stable coins usurping uh one of the roles we expected Bitcoin to play. Uh now we expected this 10 years ago before stable coins happened on the scene. Um but uh in terms of remittances uh and emerging market uh activity, we're seeing stable coins usurp that role that we thought uh Bitcoin uh would would provide.
Uh that doesn't take away though from what we think ultimately will happen to Bitcoin. Bitcoin's role as digital gold has miles to go. Interestingly, and you'll see this in my new year letter, the correlation between Bitcoin and gold has been almost non-existent over Bitcoin's life. 0.14. Um, uh, nonetheless, we do think it is not only a riskon asset thanks to the new technology, uh, but it is also a riskoff asset.
It's a hedge against inflation. Uh, its growth rate is lower than gold's growth rate. And I'll bet gold miners are doing their darnest to get more of that stuff out of the ground now that they're being paid so much more. That can't happen with Bitcoin. Uh, and Bitcoin miners mathematically metered to top out at 21 million units.
Uh so uh we do think it [snorts] will be a very important store of value going forward uh particularly as we go through the intergenerational wealth wealth transfer that we expect during the next um during the next 5 10 15 years. Um we also uh had a lot more on DeFi and tokenized assets. Uh stable coins just a little bit more uh on that.
I think we passed $300 billion globally in stable coins. We saw a a very large increase in the in tokenization on on public blockchains up to uh 19 billion. Now, that's a large increase. I think that was a tripling or maybe even more in the last year, but we ultimately think that's going to 11 trillion uh highlighted by public equities, sovereign debt, and bank deposits.
So, it's going to be a very big market. And we are putting out a DeFi quarterly now uh to uh accompany our Bitcoin quarterly. Uh so stay tuned, pay a pay a lot of attention there uh because there's a a lot of excitement brewing and there will be a lot of dislocations uh in the financial sector uh because of this wholesale shift uh really to a new technology.
Uh and so we're pretty excited about that. Um the other thing we'd like to highlight is you know these these companies their their productivity the companies that are emerging their productivity is astonishing. Uh Tether for example last year uh we believed uh I believe uh delivered uh $50 million per employee.
Um that is unheard of unheard of. Uh but we think that the capitalizing uh on all of these new technologies is going to drive productivity gains much higher than people can even postulate right now. And with that, while many people are afraid given the robotics movement of, you know, and AI, everyone being thrown out of jobs, we disagree.
Uh we think this is going to be one of the greatest opportunities for the entrepreneurial spirit in history. Contrary to widespread fears that AI and robotics will destroy jobs, Wood believes these technologies will unleash one of the greatest waves of entrepreneurial opportunity in history. She frames AI not as a late stage hype cycle, but as a technology still in its early innings with enormous untapped potential.
While capital spending in tech and telecom as a percentage of GDP is approaching levels last seen during the dotcom bubble, wood draws a crucial distinction. During the late 1990s, massive investments in fiber optic infrastructure resulted in much of it remaining unused for years. Today's AI infrastructure, particularly GPUs, is in short supply and heavily utilized.
In her words, these assets are not dark. They are fully engaged in productive activity. She compares the current capital spending cycle to historic transformations such as the railroad boom of the 1800s and the automobile revolution of the early 1900s. AI is in early stages still and that it has miles to go.
Uh sure it feels like it's a hype cycle because capital spending in the tech and telecom uh uh sectors as a percent of GDP is nearly as high now as it was during the tech and telecom bubble. Uh but if you will remember the tech and telecom bubble laid fiber and most of it remained dark. uh today uh the GPUs are driving this cycle and uh and I'll steal from uh Brad Gersonner at Altimter.
He's saying those aren't dark dark, they're in short supply and they are being used. Uh and we agree completely with that. uh we compare this capital spending cycle uh to the railroads in the 1800s that got up to five to six% of GDP and then uh the automobile uh explosion in the early 1900s that got up to 3 to 4% of GDP and then we get to the tech and telecom bubble that when you added software and hardware comm equipment together.
That was about the same size as the auto capital spending cycle. And uh we're about there now with in this cycle with AI, robotics, energy storage, uh multiomic sequencing, blockchain technology. But we think we're going a lot higher. we think we will go up to or capital spending as a percent of GDP will rise to 12%.
Uh and I'll get into some of the reasons why but key is productivity as usual economics productivity. Uh so uh we've we believe we're fairly early in this cycle. So let me uh before I go on to some of the productivity gains that we see uh also highlight that as a result of this investment boom uh and the increased productivity that we see we believe that real GDP growth will accelerate towards the 7% plus range
uh by 2030. uh the ingredients are all there and it is also a hallmark of technology revolutions that we see a step function change in GDP. Uh the 400 years until 1900 for example uh global GDP averaged 0.6%. And then in the late 1800s, early 1900s, of course, we had the railroads. Uh we had telephone, electricity, the internal combustion engine, a technology revolution.
Uh that 0.6% real GDP growth went to 3%. For the last 125 years, uh and so that was a fivefold step up in GDP growth. We're saying maybe a two and a half uhfold step up, but I actually think that's conservative uh given the five innovation platforms evolving at the same time. , uh multiomic sequencing and blockchain technology.
Uh and those innovation platforms are converging. uh and that's what's causing the great acceleration here. So I'll take you through uh a few of the stats and and the aha moments we've had this year uh as we were doing our research. So Frank and Joseph on the uh AI infrastructure side. Uh so we believe that the data center uh in uh infrastructure cycle which uh is at about 500 billion now up from up two and a half times from prej chat GBT that that is actually going to 1.4 trillion dollars per year uh by 2030.
Thank goodness we had the chat GBT moment because that was the aha moment for all of us. This is somewhat controversial because software stocks have been going through a very difficult time ironically through this AI boom and it is because of the disruption that AI is going to cause uh to the in particular SAS uh but all legacy software.
uh we think that uh software will grow the market will grow at roughly 19% in our bare case to uh I think it's 54% per year in our bull case uh up from 14% per year over the last 5 to 10 years. Uh but you have to get on the right side of change. A lot of those software companies are in the private markets, uh, OpenAI, Anthropic, XAI, uh, and and in the public markets.
The real success story of course has been in the platform as a service part of the tech stack and that of course the poster child there is Palunteer. So again, have to get on the right side of change. I'm not saying that all the SAS providers are going to be crushed. It's going to be like all legacy players.
You'll probably have, you know, the market consolidate and there'll be one very big player. You know, Walmart in retail, for example, uh is is um is how we're thinking about this. or as we get into fintech and blockchain technology and DeFi disrupting the traditional financial world, JP Morgan's probably going to be fine.
It is harnessing these technologies and it probably will consolidate the market. Wood's macro outlook is unambiguously optimistic. She argues that technological revolutions historically produce step function increases in economic growth, not just incremental improvements. For four centuries prior to 1900, global GDP grew at an average rate of only6%.
The industrial and technological revolutions of the late 19th and early 20th centuries lifted that figure to roughly 3% for the past 125 years, a five-fold increase. Looking ahead, Wood believes a new step function change is underway. She projects that real GDP growth could accelerate towards 7% or more by 2030, driven by massive productivity gains from converging innovation platforms.
Even her basease assumptions, she notes, may prove conservative given the scale and simultaneity of these technological advances. On the AI front, Wood highlights the data center infrastructure cycle, which has already surged to approximately $500 billion annually, up 2.5 times from pre-hat GPT levels. By 2030, she believes this figure could reach $1.4 $4 trillion per year.
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