저자: TomLee/Brian · 외국인
요약 보기
S&P500의 1분기 실적이 예상보다 좋아 이익 상향이 시장을 끌어올렸다고 진단. 올해 7,300 이상 상승 후 77 부근까지 갈 수 있으나 9~10월까지 조정(5~10%) 가능성을 언급. 원인으로 Fed 정책, 에너지 쇼크, SpaceX IPO 물량을 제시. 중간선거 이후 상승, 2027년이 역대급 수익 해일 가능성. 장기로 S&P 10,000~13,000 목표(2029~2030). 이후 AI 인프라 수요가 공급을 앞서는 상황과 추론(inference) 수요 확대로 엔비디아 중심의 성장 지속을 강조. 전반적으로 낙관적 장기관, 단기 조정 경계.
다듬은 글
here, on the set . Uh, I mean, Tom, you see activity in microns and snowflakes, and you think, watching this market? Well, I think it was a great conversation with Liz, but one thing to remember is that now that the first quarter earnings are out, people thought the S&P would be in the $70s. It will be at 80.
So that's an excess of $10. That's $40 annually. This means that the added earnings growth potential is somewhere between 800 and 1,000 points of S&P growth. I think all the growth since April can only be explained by the above-average first quarter profit figures. You are still calling for a three-phase market.
Explain to our viewers again what this means. Yes. Our base case for this year, which we expected to be challenging, and it looks like it, is that we will initially grow to 7,300. We are above that level now, but I think it's almost 76. Yeah. And I think we can get to 77, all the way to 77, but then I think we'll go through a lot until October.
And this is a new Fed action. This is the energy shock that Liz was talking about , especially the shortage of petroleum products and lubricants. You know, Auto Nation talked about it. And the third is the SpaceX IPO, which opens up the anthropogenic market, and when it unlocks, there will be a lot of additional supply.
So, I think this could put pressure on stocks in a way that would make it look like a bare market. But then, after the midterm elections, I think we'll grow a lot, and 2027 is the year we could see some of the best returns we've ever seen in our lifetimes. Okay, Brian. So, you've had a chance to listen to Lisanna, and now Tom's response.
How does this match what you think? It's not that different, because when we released our 2026 forecast, we explained to investors that the market environment in 2026, Scott, would be very different from the last two or three years of bullish growth. That is, it will be a profit-driven market . Profit-driven markets are much more volatile than momentum-driven markets.
Something Tom spoke about so well. But they are also rewarding in both directions. If, if, as Liz says, and I think what will eventually happen is that you will start to see a reduction and a slowdown in earnings per share of large caps. You will have some concerns, Scott, and people will act accordingly.
This is kind of number one. Number two, this also suggests that during a profit-driven market, more corrections occur. And we said that we would have some kind of correction. I don't think it will be a completely bare market, but about 5 to 10% by the fall, and then we will finally get the expansion theme.
I still firmly believe in the expansion theme. And I think that's what will really drive things in 2027. Why do we need a correction? Do you mean that the profit will not match the current moment and this will cause a correction? Theoretically, there should be a mechanism. So if you...Well, I think we should get a pushback.
I'm trying to focus people on the long-term goal that I have in the market, which is 10,000 to 13,000. I think that's where we're really moving. Um , and is it by 2400, by 2029, 2030, 2020...well, we still have a few years. Achieve one goal at a time . You have to do either one or the other. Well, I set a target of 10,000 to 13,000 around 2029-2030 .
Good. And that will put an end to the age-old bull market that we started in 2013. How long will a century-old bear last? Then after 15-20 years you move into the age-old naked market. What ends a bull market? Usually, low prices end in a bull market. Usually it's something else . Every time you reach a peak, you know, you had that in 2000, it was the tech bubble.
We had a great run. Um, but we peaked in 2007, and then you go into the age-old bare market of the great financial crisis. So it will be something different every time, but it was about three years. Marian, well, it wasn't a 10-year-old, it wasn't an age-old naked market. We went from 780 in 1981 to where we are now.
So, the age-old bear market lasted from 2000 to 2013. This period was a sideways trading range. You couldn't break and hold a new high. We tried to do this in 2007 with S&P. In S&P. Good. And then in 2013 you hit your peak. Then you enter a whole new age trend. So, we were in a century-old bull market, right?
I think we've been in a century-long bull market since 1981. I mean, I remember in '19 we were at around 59k. And how long did it take to get back above a thousand? 19 Well, if you look at this graph, even starting in 1969, I think throughout the whole terrible 1970s, uh , I have some memories of the 1970s, the great 50s, like American Express stock, was like a $40 stock , went up to about two.
I mean, it was terrible in 1974, was n't it? Yes. And we didn't break above a thousand until 1982, I think. So 1982 from '69 to '82. '82 was the big bottom and you had a long-term bull market. I can tell you why this happened in the 70s . I-I-I, so we ask what will happen to artificial intelligence, technology, and all these wonderful things.
I think we have started an inflationary cycle. So I outlined that there are three phases of inflation. You have inflationary growth , which we're in right now , where prices are going up and that's helping revenues and profits, and we see that a lot in technology, and then inflation continues, and then you start to feel some pressure.
Um, but stocks can thrive well in such an environment. It's only when you have hyperinflation that you have a real problem. So, in your opinion, you should all exit the market in 2030? Well, it doesn't have to disappear from the market by being something other than technology. So I think the early stages of what will become a new leadership have already emerged.
This will be a small cap. It will be commodities, energy and , for me, a really big one. Hello begin our video. And this next wave of growth may be more driven than markets realize. Over the past few weeks, investors have focused on one issue. Has the commercialization of artificial intelligence gone too far?
After the massive growth of semiconductor AI infrastructure companies and hyperscalers, many investors are wondering whether reality has outpaced expectations . But beneath all the market noise, where a different story is unfolding, the world still lacks computing resources, and this is perhaps the most important fact for understanding where to go next.
Think about what happened recently. Almost overnight, completely new artificial intelligence hyperscalers appeared. Large-scale cloud contracts are being signed. Tech companies are raisry major AI company keeps asking me for more computing power. No less , but more–these are key details that many investors continue to ignore.
The conversation is no longer about whether there is a demand for AI. The conversation is about how quickly investors can build enough infrastructure to satisfy him. And so far, the response doesn't seem to be fast enough. Even after years of investment, computing power remains scarce, memory remains unchanged, advanced packaging remains unchanged, power, data centers, construction remain unchanged.
Almost all major water connections still exist. That's why executives across all technology sectors continue to talk about shortages, not oversupply. Historically, technological power has often been characterized by infrastructure being built before demand emerges. Today, AI markets look almost completely different.
Demand appears before the infrastructure exists. The new capacities are used almost instantly. New clusters are filling up quickly, and customers continue to seek additional computing power whenever they can find it. This is an incredibly important distinction, as it suggests that AI development is still driven by demand, not speculation.
Meanwhile, Nvidia remains at the center of almost every major trend driving this expansion. Whether it's hyperscale solutions, enterprise-based AI project development and robotics automation systems, or next-generation cloud infrastructure and media technologies, they continue to appear almost everywhere, and increasingly, the story goes beyond learning.
Conclusions are becoming the next big growth engine. Learning builds intelligence. Conclusions monetize intelligence . Every AI response generated for a user requires inference. Every AI aid requires conclusions. Every AI agent, every AI-based program requires inference. As AI moves into consumer products, enterprises, software, healthcare, finance, manufacturing, and robotics, the demand for inference could become much greater than many investors currently expect.
This brings us to one of the most interesting developments happening right now. This is consumer AI. For years, artificial intelligence was mostly housed in data centers. Now it is starting to reach everyday users. AI-powered smartphones, AI-enabled PCs, AI personal assistants, device-based thinking, enterprises, capitols, and digital agents.
And the address space becomes much larger, and each new user creates additional demand for software in the computing stack.
Comments 0