저자: JeremySiegel · 외국인
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제목 속 Jeremy Siegel 발언 중심으로 연준의 완화적 통화정책, 유동성 증가(통화량 3~4개월 성장), 유가 100 미만 안정, 인텔 감가상각 재평가 등으로 AI 랠리 환경이 우호적이라고 봄. 장기채(10년물) 금리 상승으로 단기 금리인하는 어렵다고 평가하며, 다음 주 연준 발표를 주목. 엔비디아는 밸류에이션이 하락했고 AI 인프라 수요가 지속되어 리스크-리워드가 개선됐다고 제시. 다만 AI 투자의 수익성 입증 여부가 핵심 쟁점이라고 언급. 옵션 전략 설명은 특정 가격 방향 예측이 아닌 기법 설명으로 분류.
다듬은 글
leaving everything as it is. So this is, I think Livermore called it the devil's search that the market is constantly doing. But usually I find a few you'll find out later what it was, were there any good things, was it still AI, was it profits remaining I think there were a lot of factors. And, first of all, oil is not rising, you know, above 100, which is certainly acceptable, and of course very acceptable for the United States, because they are an exporter.
You also , we have to admit, had some amazing chip profits that no one could have predicted. I mean, the turning point was when Intel said that its old, fully depreciated chips actually had value, while a large part of the market was worried that these chips were under-depreciated . I mean, that was a big twist, which we talked about as well.
And then we got a much more favorable monetary policy. As you know, I look at the money supply, and over the last 3-4 months we've actually had growth, which means there's liquidity that can fuel the AI revolution. At this point, I've already said it. No one would blame Fed Chairman Walsh. Well, we need to start talking about this.
But no one would have blamed Fed Chairman Walsh if he hadn't done what President Trump so clearly wants , namely lower rates. Because things have changed, and the bond market itself can dictate what the Fed can do, and of course, it doesn't look like a rate cut is coming anytime soon. I mean, the 10-year bond is the ultimate arbiter.
You are absolutely right. But you've even noticed a change in President Trump's tone compared to a month or two ago: from "we definitely need to lower rates" almost to "hey , just don't raise rates." I think his last statement was, "I don't think we should raise rates." They seem to be saying, maybe we could leave them as they are.
And it is clear that he will not raise or lower rates next week. But what is he going to outline? Is he going to change communication, or cancel the "dot charts"? I mean, a new agenda will be announced. He really didn't give us many clues before we met him. No speeches before the period of silence we are currently in .
So actually next Wednesday will be the big reveal and I will be listening very closely to the Fed statement. Yes, yesterday we had Loretta Messer saying that certainly, as rates are rising and also given the number of jobs, the Fed is not tightening policy right now . On the contrary, people say that the Fed may even be acting too leniently.
Too soft, perhaps too loyal for current market conditions. Yes. I mean, in my opinion, especially when I look at the volume of loans currently offered in the market and we look at the market itself; It doesn't seem like there 's any shortage of capital, given the enthusiasm for SpaceX and everything else.
You know , we absolutely, we just don't see it. So yes, I think the market is probably with a lot of room. So, that's what we're trying to figure out. What is the long-term plan? They report earnings on July 29th, Joe and Diana, so I think it's going to be pretty interesting , because the stocks have been tough and, frankly , haven't rebounded much from those lows.
So I think we'll get a lot of information in a couple of weeks. That's a good question you started with Kevin: Is the IBM problem just IBM-specific, or is it an industry-wide issue? And you know, the market feels like they're trying to figure that out today in software, although we're seeing mostly a decline, certainly not as dramatic as IBM.
But let's move on to your examples of deals, Joe. Let's start with yours. What is your approach today? Yes, I'm trying to avoid the earnings announcement on the 29th . So, this expires on the 27th. This is a weekly option, the sale of a cash-backed put to finance the purchase of a vertical call spread.
So, this is a bullish strategy. Moderately bullish. Selling a put with a strike of 375. You should be able to execute this combination: selling a put of 375 and buying 390/405. Call spread. You should be able to do this for about zero net cost. That is, you can sell a put to finance the purchase of this call spread.
It seems like when I looked at it, there was parity or a slight difference. I think it can even be done with a small loan now. Ah , the shares have now rolled back a bit. Demand for put options has increased slightly. But I drew attention to this for several reasons. First, the volatility of these stocks is currently quite high.
The current volatility rank is around the 90th percentile, which means you can make a good profit selling premiums. Another point, Diana, that I find interesting is the skew: if you compare call options and put options, there is a significant demand for out-of-the-money call options right now . They have many buyers.
So what you can do with a vertical call spread: if you buy an option "at the money", it usually has a little less implied volatility compared to the 10% "out of the money" and 5% "out of the money" that you can sell. Therefore, this makes vertical spreads a little cheaper. You can buy a cheaper vertical spread, finance it by selling a put, and come out at about zero.
This lowers the breakeven point to your sold put strike, which in this example is 375, and gives you the potential. Something unusual is happening beneath the surface of AI trading this month. Investors rushed to hot segments of the semiconductor market. Memory stocks skyrocketed, and AI infrastructure companies became market leaders.
Anything related to data centers, advanced chips, or high-bandwidth memory seems to attract huge amounts of capital. Meanwhile, Nvidia has been doing something much less exciting most of the time. It has consolidated, and that is what may make the stock interesting now. While other semiconductor companies experienced wild rallies followed by sharp corrections, Nvidia began to show signs of relative stability.
Some investors believe the stock may be entering a new phase, where market momentum is finally catching up with a company's fundamentals. The argument begins with an assessment of value. While , its valuation has declined significantly year- over-year, although this does not automatically make the stock cheap.
But when you combine the lower valuation with continued spending on AI infrastructure, strong demand for accelerated computing, and Nvidia's dominant position in GPUs, the risk- reward ratio starts to look different. That's why some investors who previously favored Broadcom, hardware makers, or memory stocks are starting to look at Nvidia.
Perhaps the opportunity is hiding in plain sight. But to understand why, we need to look further than Nvidia itself. The entire AI infrastructure market is currently driven by a fundamental imbalance. Demand continues to exceed available supply, and we see this in memory. We see this in computing power and in advanced semiconductor manufacturing.
We see it in the availability of data centers, and most importantly, we see it in energpending extraordinary amounts of money trying to expand the power of AI. There are still signs that they can't build infrastructure fast enough; this tells us something important. The AI investment cycle can be expensive, but there is little evidence at present that the largest companies are going to scale back their ambitions.
In fact, the opposite seems to be happening: cloud demand continues to grow, and AI workloads continue to increase. Companies are securing additional compute capacity, hyperscalers continue to invest aggressively, and the infrastructure needed to support this expansion is becoming increasingly complex.
This creates a potentially powerful environment for Nvidia. Every new AI data center requires computing infrastructure. Every increase in AI consumption creates additional demand somewhere in the technology stack , and while Nvidia doesn't get every dollar spent. The company remains located almost at the center of the ecosystem.
But an important debate is developing. Can this level of spending really continue? Ultimately, investors need to see profits. The largest technology companies cannot spend hundreds of billions of dollars endlessly without demonstrating that artificial intelligence creates economic value. The problem is that the return on investment in AI can be difficult to measure directly. AI does not necessarily generate revenue through one single product.
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