원문 보기
Hello, at called Granny Shots. This is our review for the week of October 19th. I'll start with a few details. As of October 16, the price of Granny Shots, ticker GRNY, our large- cap ETF, was 27.22 with total assets of 4.36 billion. Granny J, i.e. the younger version of Granny Shots, had a price of 26.72 and total assets of 450 million.
And Granny I, or profitable Granny, had a price of $20.55 and 59 million in assets. Over the past week, the Granny Shots large-cap ETF has fallen 4.27% compared to the S&P 500's 2% decline, representing a 234 basis point lag. Granny J fell 10% last week compared to a 2% drop in the Russell 2500 index, or a lag of 800 basis points.
As for Granny Income, it fell 3.48% compared to the S&P's 2% decline, or a lag of 167 basis points. Year-to-date, the October drop has resulted in Granny's return of 10%, compared to the S&P 500's 13% gain, or a 278 basis point lag. For Granny J, the year-to-date return is 4.74% compared to 13.78% for the Russell 2500, or a lag of 900 basis points.
And for Income Granny, the total return is 9.76%, compared to 12.91% for the S&P, or a lag of 316 basis points. So, let's talk about macroeconomics. I think it's most important to discuss the six reasons why we believe in AI trading, as this is what I think investors are most concerned about. First, I want to note that the breakthroughs in the field of AI have become simply incredible.
I mean, for example, a study by OpenAI, published about 2 weeks ago, where 771 mathematical problems were solved. This represents a staggering 81% of all mathematical discoveries in the last 3 years. And this took about 3 hours per model on average. This was so significant that many mathematicians were quite upset.
Second: AI is not only making incredible breakthroughs in just 3 years, we are also seeing it start to increase productivity. Probably one of the best charts I've seen is the revenue per employee of S&P companies. As you can see , since the launch of ChatGPT, revenue per employee has started to grow.
However, bottlenecks in the field of AI still exist. This is good to some extent, because we know that the industry is not oversupplied. This report from Nomura, for example, talks about supply constraints that still exist for memory. And in fact, Jensen Huang talked about this today when he said that not only is there a memory shortage, but even if there wasn't, there are still many areas where it could be used.
So, in this case, the reality is that we don't have excess supply. However, what worries people is that the funding needs for AI are substantial. I actually think it's a question of "the glass is half full or half empty." Because if funding markets get nervous and raise the cost of funds, it actually introduces discipline into the AI itself.
In other words, the fact that there are financing problems prevents a “bubble” from forming. And people point out that there are simply too many securities issues in the market . You know, the volume of AI issues is 50% of Treasury bond issues. And we see that credit default swaps have increased, which means that the risk of default has increased.
And debt issuance by AI companies has actually declined . So, the natural regulator is already in effect. This is where sentiments diverge, and I think the skeptics are much louder here. And that is what causes panic. There is a panic around funding , which I mentioned, for example, regarding Coreweave and Meta.
But you know what? Like I said, this is really nothing new. We already know that there is a lot of funding here. And again , this creates a lot of discipline or eventually leads to it. We also have the "not in my backyard " problem. People simply don't want AI built near their homes. This CNBC survey shows that 63 % of people simply don't want to see an AI center within 10 miles of their home.
And it's mostly Democrats, young people, and women who are opposed. But, in essence, all three actually tend to be Democratic voters. This is a political issue. Republicans support data centers, but I think after the midterm elections, Americans will see that Democrats will understand: opposition to AI and data centers is really propaganda.
Many Democratic senators supported the Clarity Act. So I think after the election they will change their position to support, which will be a political turnaround. We also have concerns about China and their advanced models, as well as weak technicals, but I think in this case a lot of things are already factored in by the market.
Hedge funds actively opened short positions not only in stocks in general, but also in technology stocks. And we are seeing a significant reduction in risks in the technology sector. Actually, look at the positioning of long and short positions. This actually looks like surrender. I think there is a general reduction in risks ahead of the midterm elections.
So perhaps the election will ultimately be the catalyst. But, perhaps, the last thing I want to draw attention to is the presence of historical analogies. The first period I want to highlight is 1994–1997 . This is Cisco. The public Internet or Netscape browser appeared in 1994. Cisco was worth 80 cents then and rose to $9 in 3 years.
But then a few things happened. Alan Greenspan talked about irrational optimism. This caused the initial drop in shares. And Cisco started to get cheaper. And in February 1997, Alan Greenspan declared the need for preventive tightening of policy before signs of inflation appeared. Doesn't this sound a lot like what's happening today?
Yes. And the shares fell even more. Cisco then reported a quarter where revenue growth slowed by half compared to the previous two quarters. Then there was talk of slowing revenue and the threat to Cisco from Internet Protocol Switching, or IPS. She was considered the biggest risk for Cisco. So the stock eventually fell from $9 to $5, a 40% drop.
This is not too different from the correction we are seeing in AI stocks today. But what happened after 1997? Well, Cisco went up to $18. Then came another correction due to the default in Russia, the collapse of Solomon Brothers and Long-Term Capital. And Cisco fell again by almost 50% to $9. But here's the thing.
Ultimately, Cisco rose to $80 in 2 years . And this graph shows how grandiose this movement was. This was a 100-fold increase from the low. So, where are we today? I think we are in 1997 . Since ChatGPT was launched 3 years ago. So I'm buying on this decline in AI stocks. I think we can expect some positive developments.
The first is bond yields. The yield on 10- year bonds began to rise after Jackson Hole and Fed Chairman Wash's speech. The yield on 10- year bonds rose from 4.6% to almost 5.5 %. Many thought we would reach 6%. But instead, profitability declined. This is a " pigeon" signal. Similarly, the probability of a Fed rate hike in October and December fell.
In October, it jumped to 55% after the release of September CPI data . And they jumped to 98% in December. And now they have both fallen. The probability of a December hike has now dropped to 67%, and the probability of an October hike has dropped to five . This is a serious turn and again a " dovey" development of events.
So I think the markets are like a compressed spring right now. And we buy AI stocks on the decline. Now, regarding the performance of individual stocks for retirement portfolios, let's take a look. The top five among such stocks last week: CF Industries, Lockheed Martin, Eli Lilly, TJX, United Healthcare.
The five outsiders here are all AI “bottlenecks” : Intel, Micron, Veritiv, KLA, and Arista Networks. Among the small- cap companies in the top five: Halozyme, Dick's Sporting Goods, Exelixis, H.B. Fuller and Cullen/Frost Bankers. A look at the five worst: Natus, Fabrinet, Lumentum Holdings, Rocket Lab, and Vicor.
In terms of themes, style bias underperformed but still outperformed in relative returns for large caps, followed by PMI recovery, seasonality, and millennials. That's all for now . Thank you for your attention, we'll hear from you soon.
Comments 0