Source: Wall Street See, Author: Li Xiaoyin

On July 13th, in the monthly series program "In the Know", well-known investor "Cathie Wood", also known as "Mudou Jie", discussed with Tasha Keeney, the investment analysis and institutional strategy director of ARK Invest, and Sam Korus, the company's research director on autonomous technology and robotics, on how ARK values companies and makes investment decisions. Mudou Jie also expressed opinions on issues such as US bond yields and market concentration in US stocks.

This article collects the brilliant ideas of three people in the show:

1. ARK holds a combination of top-down and bottom-up evaluation methods to value different business lines.

2. In ARK's scoring system from 1 to 10 for companies, if one score is below 7, it is worth paying attention; but if two or more scores drop, we will seriously consider reducing the risk of the investment portfolio.

3. Most of Tesla's commercial value comes from Robotaxi, which will change Tesla's business model from one-time revenue from selling electric vehicles to recurring revenue generated by RoboTaxi.

4. We believe that Tesla may be the first auto manufacturer to launch a large-scale robot taxi service, and after achieving economies of scale, the price of robot taxi service may drop to as low as 25 cents per mile.

5. Tesla's 'ups and downs' depend on its execution power, and key factors that may affect it include key personnel (Musk), personnel changes, moats, impact of cutting-edge technology/adoption, and battery costs.

6. Due to the cash generated by its autonomous driving technology and successful production scale, it is expected that Tesla can expand its annual car sales from the current less than 2 million to 6 million-14 million.

7. We believe that Tesla is very likely to launch a robot taxi network in the next few years, and it is very likely to be launched at least in the next three to five years.

8. It is expected that by 2029, the ratio of Tesla's electric car business valuation to EBITDA will shrink from the current 60 times to 19 times, and revenue growth and profit expansion will remain strong.

9. In the long run, robotics, energy storage, artificial intelligence, blockchain technology, and multi-micron sequencing technology will raise the actual GDP growth rate from 3% to the range of 6%.

Here are the minutes of the conversation:

Cathie Wood: Hello everyone, today we are going to do something out of the ordinary - we hope to launch a new section every month, focusing on some stocks and companies that we focus on in the innovation field.

Today, we will specifically introduce how we conduct bottom-up analysis. I think we are famous for using the rights law to analyze the market from top-down. But we want to explain more about our analysis, not only top-down analysis, but also bottom-up analysis, especially our valuation scoring system. For this reason, I would like to introduce Tasha Keeney and Sam Korus, who have done an outstanding job on Tesla. Tasha is our Director of Investment Analysis and Institutional Strategy, and Sam is our Director of Autonomous Technology and Robotics Research.

So we want to introduce our valuation system, and we will use Tesla as an example because we have already published a lot of content about it. Although we haven't released too much information about other stocks yet, we will discuss Nvidia in another webinar. Next Thursday is our quarterly webinar, so please stay tuned. After that, I will conduct a non-commercial case demonstration once a month. Now, Tasha, Sam, and I will take you through the valuation system. Tasha?

Tasha Keeney: Thank you, Cathie. As we all know, ARK is very focused on disruptive innovations, and our investment team is divided by technology. So Sam and I have been working together for almost ten years, and are now researching autonomous driving technology and electric vehicles. We have considered all the top-down analyzes we have done in these two areas, and we will discuss them later.

Then, once we find potential names for the portfolio, we will do bottom-up work. Bottom-up work includes qualitative and quantitative indicators based on evaluations. On a quantitative basis, you are very clear about our Tesla blog, which contains our 2029 target price. Similarly, this is also a combination of top-down and bottom-up. So, Sam, why don't you first introduce your top-down research on electric vehicles?

Sam Korus: Of course. This is related to what Cathie said earlier, which really makes use of the rights law and cost structure. So take a look at the decline in battery costs and explain what we think will happen to price parity for electric vehicles. This has already happened in China, where you can see that their adoption rate is far ahead of that in the United States, while this transformation has not yet occurred in many areas in the United States. All of this leads us to make top-down predictions, and we expect electric vehicle sales to increase from about 10 million in 2023 to 74 million in 2030. So, we combine it bottom-up, which is how we get differentiated prospects.

Tasha Keeney: In terms of the prospects for autonomous driving cars, we believe that by the end of this century, the value of the robot taxi industry may reach 28 trillion US dollars. That's why when you look at our Tesla valuation, we believe that most of Tesla's value will come from this because it will completely change the business model—from the current one-time revenue of selling electric cars to the recurring revenue stream brought by Robotaxis.

Of course, we believe that robot taxis are disruptive because their prices can be lower than all current options for online car-hailing, and far lower than the price of driving a private car in the US today (about 70 cents per mile). Therefore, once scaled, the price of robot taxis may drop to as low as 25 cents per mile.

But initially, we set our target price higher. Therefore, when we evaluate companies like Tesla, we hope that each company can achieve a compound annual growth rate of at least 15% in our valuation within five years. When we conduct the preliminary evaluation of Tesla, we will conduct a qualitative evaluation of it. Therefore, you can see on the slides that we first examine personnel management and corporate culture. This takes into account our thoughts on the management team. Sam, why not start with Tesla?

Sam Korus: Yes, I just want to say that these qualitative scores are usually supported by quantitative measurements. So you will see that the investment team will have a lot of effective discussions about this.

Therefore, for personnel, management, and culture, you know that we look at it from the perspective of disruptive innovation. Therefore, we actually want a founder who is also a CEO, who is willing to make a long-term bet and may invest in the short term, which may not be what the market wants or what those who care more about short-term results want.

But for Tesla, having someone with a great vision like Elon Musk who has formulated plan after plan, and is willing to sacrifice short-term profits to pursue huge opportunities such as autonomous driving, is a huge positive factor. Therefore, although Elon is an insightful founder, this is good, but we will also pay attention to the ability to get talent and departure of personnel. So, you know, Cathie, you are an important member of the Tesla team, they have reviewed our previous conversations.

Cathie Wood: Yes, the departure of key personnel has been asked many times. For example, after JB Straubel (Note: Co-founder of Tesla, long-time Chief Technical Officer) left, who is the real person in charge of Tesla's battery and transmission system strategy? We received many similar questions when he left the company. An important person for the whole story left. The interesting thing about this departure is that JB left after his main job was completed, which means that the battery part and the powertrain part of the story are already in place, and now the main driving force for the strategic vision will be autonomous driving. Andrej Karpathy (Note: Director of AI at Tesla) has worked at Tesla and then left, and now he has returned. In short, this is a very difficult environment, and many people are exhausted.

So we do see people coming and going, and we understand that. But Elon is obviously a visionary. He is surrounded by some of the best engineers in the world who want to engage in very difficult projects, the most difficult projects in the world, which is the AI part of the strategy. As you have heard, our description of Tesla is that it is the largest AI project on earth, and we believe it is attracting the best talent in the world.

Sam Korus: Yes, in fact, in an annual survey of where new graduates want to work, SpaceX and Tesla are still at the top, which is a good proof.

Tasha Keeney: We have also discussed this issue in the past, and our idea is actually that Musk's leadership of many companies does help recruit talent. Therefore, as Cathie mentioned, although it is a difficult place to work, it is also a very ideal workplace. That's why, you know, there are rumors that Andrej Karpathy may come back.

Cathie Wood: I would like to add another thing here. You will find that from the perspective of risk control, you can see what affects our scores.

I just gave an example, which is the departure of key personnel. JB opened this door and his departure occurred when the electric vehicle story was accelerating. But another risk area is governance, especially for Tesla. Of course, we will evaluate the governance of any company. But to make you understand the problems we face in this area, you will remember when Elon tweeted that he was considering privatizing the company. He said in the tweet that the funding was in place. Of course, this angered the SEC. In fact, there were also some lawsuits. So when this happened, we learned that the SEC was indeed investigating whether the funding was guaranteed, and if this is an accurate description of what is happening within the organization, we know that it will distract the company's attention, and for this reason, we did reduce this score.

Therefore, when we think that something constitutes a risk, we will adjust the score. But what was interesting at the time was that a few weeks after we lowered this score, Tesla released the specifications of its own AI chips, and when we looked at them, we said, 'Oh my God, they are much more advanced than we expected and earlier than we expected,' so another score, the 'moat' score, was raised again.

So you can see the dynamics of our scoring system. What I want to say is that in this 1 to 10 scoring system, if one of the scores is below 7, it is worth paying attention to. The governance level at the time did not drop below 7, and the moat score was raised again. But if two scores drop, we will seriously consider whether to reduce the risk of the investment portfolio. So Tasha?

Tasha Keeney: Thank you, Cathie. Yes, so I'm going to turn to "moat," and some of the things we've thought about here for years are Tesla's vertical integration advantages. We believe they've been ahead of their peers in battery, AI and data for many years. As Cathie mentioned, Tesla also produces hardware, chips and inference chips internally. Sam, tell us about Tesla's battery integration.

Sam Korus: Okay, I would say, especially when a company is at the forefront of a new revolution, there might not be a supply chain available. So, Tesla's investments in battery manufacturing chemistry, and the investment via the power inverter, really did set them apart in terms of performance compared to their peers. Still to this day, it's only one or two other competitors that have a similar efficiency to Tesla, but no one was able to vertically integrate as quickly as Tesla.

Tasha Keeney: On the autonomous driving side, Tesla has access to billions of miles of driving data. And as peers, it’s in the millions with Waymo. So, it's an order of magnitude of difference.

This data will be used to train neural networks so that Tesla can layer autonomous driving features, and we do believe those features will eventually create a fully autonomous car where you can actually take the wheel off the dashboard. And of course, the basis for that is the robotaxi network.

Another point that I want to make is the Supercharger network also gives Tesla a great moat. Of course, it's the North American charging standard right now, and a lot of other automakers have also signed up to be part of that network.

Cathie Wood: You just have to look at the risks of any new disruptive technology as it's emerging. I can't tell you how many times we've been in this situation: Oh my goodness, this is a new type of battery, Tesla is going to be left behind because it's locked into its current strategy. We know how difficult battery technology is, and the likelihood of Tesla adopting new battery technologies is very high because its expansion is built on the battery. So, it certainly wants to keep that lead. So, we will definitely consider the risks of new technologies emerging. And we certainly have conversations with Tesla about emerging technologies, but every time we come away convinced and confident that they are very much on top of what's happening in the new technology space, especially on the battery side.

Tasha Keeney: Yeah, and on the execution side, another important qualitative score by which we judge each company. Sam, tell us about Hell’s production. Let's get a history lesson here.

Sam Korus: I think Tesla's roller coaster ride is dependent on its execution. You know, during the Model 3 production ramp, Tesla was called 'production hell.' And I think we all remember that vividly when we saw this bright future and their delivery was X thousand cars short, their stock price plummeted, and we all thought, 'Okay, they missed a few thousand deliveries this quarter,' but what we should be thinking is, is this quarter important? Or is there something wrong in the long-term story? Are they still expanding?

And I think what we've seen with Tesla is real execution momentum. They went through a tough time, and now even Toyota's saying, you know, they manufacture one of the best cars in the world. That's a really high praise from one of the best manufacturers in the world. And with the help of China, Tesla was able to build factories faster than anyone in the world.

So, I think in electric vehicles, we really do see a continued strong execution. But, again, it's up and down. Maybe, Tasha, I can throw this back to you because there's one place that is definitely going to have a start and stop and that's autonomous driving. And it claims it will achieve it this year. What are we seeing in terms of execution in autonomous driving?

Tasha Keeney: Tesla plans to launch a robotaxi network, which is really an exploration towards the next major milestone, we think, and it’s not an easy feat, right? Manufacturing a fully autonomous car is really hard. We know it's possible because competitors like Waymo have deployed it on a small scale, but we think Tesla might be the first automaker to deploy it at scale. Tesla has already released the most advanced driver-assistance features to date, and likewise, we think they can layer these features to create a fully autonomous car.

Going back to Sam's point about how qualitative versus quantitative interact with each other, as we evaluate Tesla modeling off of all of these execution metrics is what we consider. Due to the cash generated from autonomous driving technology and the successful scale of it, we believe Tesla can grow from selling just under 2 million cars a year today to, in our bear case, about 6 million. In our bull case, there could be 14 million cars.TSo, we'll consider all of these metrics when we're modeling the company.

Sam Korus: Yeah, the other execution area we see on Optimus, is really the simultaneous use of autonomous and manufacturing technology, right? That's true fusion. I think their momentum in execution has been surprising to everyone. You have to remember, if you go back a few years, people would laugh at someone wearing a robot suit dancing on stage. And now, Tesla has at least a couple of robots completely autonomous working in their factories. It's really amazing to see all of this come to fruition.

Cathie Wood: I want to emphasize the importance of execution, especially as it relates to Tesla. We know that Elon has a great vision, and often he will articulate that vision on "Elon Time," which we all have had to adapt to. But why does he do that? He does that not only to signal to suppliers, "Hey, this is my schedule." to get all of the suppliers ready and also to motivate employees to focus their energies on accomplishing goals in a very short time frame. So another thing to focus on during the execution is that you will see the first thing we focus on is lack of R&D or the dip in R&D.

Now we're going to look at this issue from two different angles. R&D is 1% of sales, where do they spend that money? Because sometimes we don't agree with the direction. When Toyota went from electric to hydrogen fuel cells, we owned the stock at that time and saw them shift their R&D spend to hydrogen fuel cells. We know how much more expensive the infrastructure for hydrogen fuel cell is, especially compared to electric fuel cell. So we sold the stock based on that.

Tasha Keeney: Great. You know, we've talked about a lot of these points already, but let's continue to discuss product leadership. I believe in the electric vehicle space, we have a lot of evidence from Tesla.

Sam Korus: Yeah, and again, this is an ongoing debate and quantifiable debate. You know, as other automakers continue to roll out their products, Tesla's market share is definitely going to be questioned in the US. But when we compare it to Apple's profitability, we can see that as the industry develops, Apple's sales are declining but their profits are increasing. So these are all ongoing internal dialogues and discussions. People like to talk about them on Twitter as well. In any area where Tesla stock is down, you can see people talking about this. So this is also something we're closely paying attention to.

Cathie Wood: One of the recent things that has happened is that General Motors and Ford have bowed out of EVs because they couldn't see profits. We know that Ford loses $100,000 per car, and maybe Tesla's market share in the US will be higher than we think in the next few years. Of course, it's going to come down from 90% or 95% wherever it is. Just like Apple and smartphones.

But what signals are we getting from the other automakers in terms of investment in this area? The retreat is interesting. The only way to be profitable is to scale. So from a market-share perspective, this is a very interesting moment for us.

Sam Korus: Then, Tasha, you've mentioned it, maybe it involves autonomy as well. I know just this morning we had a big discussion comparing Waymo and Tesla and their leadership position in self-driving products.

Tasha Keeney: Yeah, you know, combining Cathie's points, when we look at traditional automakers like General Motors and Ford, we see that they've pulled back their self-driving businesses - Ford sold their self-driving unit and GM's self-driving unit Cruise is on pause - though they're now trying to restart. So as we observe the competitive landscape in the US, you really only have Waymo and potential Tesla. Again, Waymo has a few hundred cars on the road. Tesla has millions of cars on the road, and they believe that they can turn those cars into self-driving cars. So as I mentioned before, in terms of data advantage, they've already got scale, we believe they can translate that into AI advantage on the road, to launch a robo-taxi network that will be in many cities and not just select cities that Waymo has been able to roll it out to so far.

Sam Korus: Yeah, and I guess just one more time to hammer that home, it's also an ongoing debate and a quantitative debate. You know, as other automakers continue to roll out their products, Tesla's market share is definitely going to be questioned in the US. But when we compare it to Apple's profitability, we can see that as the industry develops, Apple's sales are declining but their profits are increasing. So these are all ongoing internal dialogues and discussions. People like to talk about them on Twitter as well. In any area where Tesla stock is down, you can see people talking about this. So this is also something we're closely paying attention to.

Cathie Wood: One final thing I want to talk about is regulatory risk. When we first started down the Tesla path, we thought regulatory risk was very high. But what's happened over the last decade since we started our research is that the US auto accident rate has skyrocketed after decades of decline. I think the lowest it got was around 30,000 deaths, in 2014. Since then, that number has risen to 45,000. This has caught the attention of regulators. So they're looking at the data now. And Tesla can provide a lot of safety data.

And the final point I think we've talked about here is the theoretical risks. We've done a Monte Carlo analysis on Tesla in terms of valuation and assessing risk impact across a variety of scenarios. We have a lot of variables, and we change the upper and lower ranges based on what we think is appropriate probability. For example, we think it's highly probable that Tesla will launch a robo-taxi network in the next few years at least. We've also factored in timeline delays that we've discussed, right? Elon has promised several times that they'll make a fully autonomous car, and that hasn't happened yet. Again, crossing that threshold is a difficult thing to do. So we can't be certain of the launch dates for the robo-taxi network, whether it's July 9th or some other specific date. But we try to use our research and analysis to come up with a framework that we think is reasonably likely to happen.

Cathie Wood: I just want to add a little bit about regulatory risk. When we started researching Tesla, we thought that regulatory risk was very high. But over the past decade, vehicle accident rates in the United States have increased sharply after declining for several decades. I think the lowest number of car accident deaths in the US was around 30,000 in 2014. Since then, the number has risen to about 45,000. This has attracted the attention of regulators. So they are now looking at the data. Tesla can provide a lot of safety data.

Tasha, I'll pass this topic on to her. She has done a lot of research on safety. Interestingly enough, this hasn't received much attention as Volvo's entire brand is based on safety. Tasha found some pretty amazing numbers in her research.

Tasha Keeney: Yes, I'll say it again, this is something we can quantify in our analysis. We estimated a long time ago that the safety of autonomous vehicles could be 80 times higher than manual driving based on accident rates. We actually have data to support this. So we've seen that Waymo is actually safer than the national average for cars. When you look at Tesla, FSD-driving Teslas are about five times safer than manual-driving Teslas. This is actually based on the latest data points available.

Elon said they think visibility could improve four to five times, and when you compare it to the national average, you'll find it's about 14 times safer. So, you know, we've already seen evidence that autonomous driving is safer than human-driven vehicles. We think that's what regulators are looking for when deciding whether to allow these vehicles on public roads.

Another point I will talk about is that Tesla is discussing the landing of FSD with China, although no decision has been made yet. But if this is true, it will be an important step forward. Sam, why don't you talk about key person risk? This is another important component of theoretical risk.

Sam Korus: Of course, we've already discussed Elon's core role, especially in fully realizing people's driving vision. So we've definitely taken that into consideration, as well as the importance of his role in launching Robotaxi. I think even he himself said that it wouldn't make sense for him to be CEO and take on a more visionary or product-driven role at a certain point. But I think we've already discussed that it's important to push the autonomous team to achieve commercial launch.

Cathie Wood: So, Tasha, let's summarize the valuation issue and bring our valuation exercise to reality.

Let me set it up first. We chose the metric of enterprise value divided by adjusted EBITDA, and we adjusted EBITDA in two ways:

One is stock-based incentives. We do think it's very important to incentivize employees (Elon included) and his compensation plan and make sure they're really aligned with the shareholders. So the second adjustment is for R&D, which is to normalize R&D expenses. Our company usually spends too much on R&D, and of course we want it that way. We want them to sacrifice short-term profit-making ability, because especially in the world of AI, winners take all.

So our assumption is that the EV/EBITDA ratio for the electric vehicle business will deteriorate in the next five years and decay towards market multiples. And our analysts believe that the combination of revenue growth and profit expansion will outweigh the valuation decline. Tasha, can you talk more about this?

Tasha Keeney: If you look at Tesla's electric vehicle business, today's EBITDA is about $57, and in our model, it's close to $60 in the final year. We have our own multiple for each line of business, and by 2029, the largest part of the value cake assessed under this line of business is autonomous driving, and we expect the EV/EBITDA multiple for the electric vehicle business to be 19x at this time. So, as Cathie mentioned, from around 60x today to a significant contraction to 19x.

Actually, in other business areas, including electric vehicles, our assumed multiples are even lower, at around 12-13x. So the blended average multiple is even slightly lower than 19. So based on our valuation of Tesla's business, we basically view it as a mature business, and in fact, we believe Tesla will maintain a respectable growth rate in the fifth year of this model. Therefore, our valuation of Tesla over the next five years is actually a relatively conservative assumption.

Cathie Wood: Again, we set a minimum five-year annualized rate of return of 15%. So when I say going from 60% to 18%, our revenue growth and margin assumptions have to outweigh that. You know, in our empowerment methodology, we're very rigorous about how we build models for long-term cost declines and scale expansion. So I think we're going to have a discussion here, perhaps a summary version of the 'Global Report.' No, we won't spend too much time on fiscal or monetary policy this time. Fiscal policy, for obvious reasons, Washington is in trouble with that.

Chairman Powell seems to be emphasizing monetary policy in his latest testimony, and he's now focusing on employment. He's studying some published statistics and admits that inflation is continuing to ease. This week, Austin Ghoulsby, who I think is probably the biggest dove, said 'aha, this is what I've been waiting for' after the CPI report was released. So we'll only be discussing economic indicators, last week's employment report, the headline was stronger than the consensus expectation I think for 190,000. The actual number was 206,000. But adjusting for a downward revision, the actual number is 95,000, and household employment increased by 116,000 after a decline of 408,000 last month. So household employment is weak, flat, or declining year over year, and non-farm employment is still slightly above half a percent. Emergency aid numbers continue to decline, with a significant drop of 49,000. So I think Chairman Powell appropriately focuses on these points.

Of course, another variable that the Fed is concerned about is inflation. This week, we got CPI, which was lower than expected, which didn't surprise us. As I mentioned in the previous post, no, we see markdowns, not just lower inflation, but markdowns, Walmart Costco, Best Buy, McDonald's, Wendy's, and even Starbucks have promotional packages, which is very unusual. So CPI actually fell 0.1%, which was headline news, making that number up 3% year-over-year, not yet up to 2%, but we think it is about to reach this target. The core only rose a little bit. Yes, 0.1%, slightly below expectations after rising 0.2% last month, and the current core year-on-year growth rate is 3.3%. We again believe that this ratio will approach 2%, which means close to 2%. We also got PPI, which is hotter than expected.

What does this tell us? This tells us profit compression. So, for many observers, they are concerned that we will see cost-push inflation, like what we saw in the 70s where costs keep going up and they are forced to raise prices and the consumers won't accommodate the higher prices. We see some companies, even Pepsi-Cola, announcing this week that their sales in North America have declined 4%, which is very unusual for a consumer staple company.

Now we do have some unusual things going on, perhaps attributed to the coronavirus and maybe the economy of course. So, it's probably half of each and maybe, who knows. We do believe that Pepsi-Cola will have to come down in price.

Now I'm not going to list out all of the economic statistics. What I'm going to tell you is that, as I dug into it and prepared for this, I think almost all of the statistics have been weaker than expected, particularly housing and capital expenditures. Both of them have high multipliers associated with them.

Interestingly, the one stronger number that's popping up now is personal income growth at 0.5%, but spending only up 2%. What does this tell us? This tells us that consumer savings rates are starting to go up. And when does that happen? That tends to happen when people are universally worried about their jobs and the economy.

So, I'm going to show you some charts here on this subject. So, we'll start with the chart now. Okay, you can see here the problem the market is trying to solve.

This is a long-term chart of the 10-year Treasury yield back to the early 60s. You can see that the trend was going up from the early 60s to the early 80s, went up significantly from low to mid single digits to up over 15%.

And we've been coming down since then. You can see that the downtrend seems to have ended. And this is one of the things that is causing a lot of controversy. One of the reasons it ended was because the Fed raised interest rates 22 times in response to inflation, feeling it was lagging behind, and decided to get tough. That was one of the reasons why the long-term Treasury yield went up. If it hadn't gone up, our yield curve would have been inverted by about 500 basis points, or 5%. That's a very unusual situation.

Now, the question is, have we broken that downtrend? The answer is probably yes, because we're approaching zero, negative rates are not good. This may have something to do with very difficult economics. We expect the economy to be softer than most people anticipate in the short term, and that may be because of consumer spending. Over the long term, we expect the pricing of the type of economy we envision to be well below expectations.

In fact, cyclical reasons, we see a brewing trend of deep deflation in the short term, and prices are too far, pushed out by supply chain shocks. Consumer companies take advantage of that, and now they will have to bring prices down, which is cyclical. Long term, deflation has a long-term reason, which is innovation, real disruptive innovation, which is essentially deflationary.

It follows the learning curve. We see efficiency and productivity going up, they manifest themselves in declining costs of technology itself, making a lot of mass market opportunities today. So, we will see the prices of these technologies come down but the unit quantity grows significantly. So, nominal GDP may be in the range of 5% to 10%. Over time, long-term, the Treasury yield has stayed consistent with the nominal GDP growth rate. So, we think that in the short term, we will see a decline in the Treasury yield due to cyclical reasons.

Yes, we do believe that the long-term downtrend in the Treasury yield has been broken, because we believe that the unit growth brought about by these new technologies will be quite substantial and may cause real GDP growth to achieve surprising levels. In past webinars, we've shared that we believe that actual GDP growth rates may be outside of the 3% range we've seen over the last 125 years for a period of 10-15 years, as multiple innovation platforms evolve simultaneously.We saw the telegraph, electricity, power, and internal combustion engine in the early 1900s, which brought GDP growth rates up from 0.6% to 3%. We believe that long-term, robots, energy storage, AI, blockchain technology, and multi-micrometer sequencing technology will bring actual GDP growth up into the 6% range from the 3% range.

The next chart deals with the cyclical part of the economy. We're watching very carefully the ratio of metals to gold. You can see how close the correlation has been since 0.8. When the ratio of metal to gold prices goes down, they reflect each other until recently, the US Treasury yield also went down. Then you see that this correlation has been broken recently. The ratio of metal to target prices has gone down. It has gone down 0.8 and 0.9 levels. But yields haven't gone down yet, and we think they will.

As I mentioned before, for cyclical reasons, we have been waiting for some signals from the ratio of metal to gold to guide us towards another direction. That didn't happen. So, we do believe that the 10-year Treasury yield will come down. I want to remind everybody that we're currently in a long-term downtrend that started .8 after energy prices, when oil prices ran up to that $47 price range. Since then, this trend has been down. The coronavirus has taken it to very low levels. Supply chain shocks have intensified again and it's currently in a downtrend. Commodity prices today are at the same level they were in the early 80s. That does have some significance.

The next chart is something I've already described, but it will be described here finally, the yield curve. So, it is measured by the 10-year treasury notes yield relative to the 2-year treasury notes yield. You can see that the 10-year U.S. Treasury yield is lower than the 2-year U.S. Treasury yield. This usually happens before an economic downturn. The shaded area on the chart is a recession. You can see that we usually slip into recession within a year and a half when we see an inverted yield curve. Now, this hasn't happened yet, although I do think that with all the downward revisions we're seeing in employment indicators and many other indicators, the National Bureau of Economic Research's score for a recession may well go back to sometime at the end of last year.

So, you can see another thing, which is the downward trend of the yield curve since the global financial crisis. During the Covid period, you can see that we did see the yield curve turn steep, meaning it went from around 0% up to 1% and then a/2%. I think it will go higher like it did during the global financial crisis. Why not? The fiscal and monetary policy makers of every government around the world are doing everything they can to tighten the financial environment but we haven't gone back to the range of 200 to 300 basis points that we should. Why not? We can see obvious deflation in commercial real estate and office space, and we're thinking more and more about multi-residential space. So, this is one of the roots of cyclical deflation.

I mentioned another issue before, which is the lower consumer or pro-consumer company pricing. Here we have the opposite, and you can see we've been having the opposite for a long time. In fact, Chairman Volcker of the Federal Reserve in the late 1970s and early 1980s tried to curb double-digit inflation, a longer period than any time since the Fed's Chairman Volcker. We never got to double-digit inflation, but the Fed policy on top of this looks as tight as it did then. That's why I keep coming back to the possibility of downside risk and the Fed having to change course.

The Fed still has four chances this year to reverse policy. End of this month, July, September, November, and December after the election. We wouldn't be surprised if there were three rate cuts because these deflationary forces are building up in the next few months.

Next, I want to show the adjusted corporate tax rate, which comes from the GDP account. You can see that the profit margin has indeed been growing since the early 1990s and now it seems to have peaked. We think the profit margin will go down more because if companies want to maintain unit sales, they'll be forced to lower prices. So, we do think that profit margin may go down to below the level of 2014.

That said, we generally believe that the trend of rising or at least high levels will continue due to all the new technologies, especially artificial intelligence, AI, and the productivity boom we see in our future. Therefore, the decline in profit margins will be more cyclical than anything else. But in the long term, we think profitability will remain high. Perhaps we won't continue to rise. This figure is already quite high by historical standards, but all these new technologies will increase profit margins.

The next page just wants to show how low the consumer savings rate is in historical context. You can see that during the Covid pandemic, it rose to about 32% because no one was spending money. Of course, fiscal stimuli also provided necessary funds. People were initially saving a lot, but now it's completely exhausted. Our savings rate is at the low end by historical standards. You can see in the shaded areas that these are periods of rising savings rates during economic downturns.

We just got another reading on the savings rate. It's up to 3.9 now. I remember it was 3.6. So, as I mentioned earlier, the reason is that spending is growing slower than income. So, this is a cautionary signal on the next chart.

Now we're going to talk about market indicators. This is a chart made by Goldman Sachs. It's a measure of market concentration. Perhaps you've heard of the tech sector's "Seven Sisters," which has become the "Six Show." When Tesla started performing poorly this year, the people who named it kicked it out. So, Mag 6 led us to break the record for market concentration. Many people think, okay, I feel safe with Mag 6, they have cash flows and seem to be in the best position of artificial intelligence. But we would say the more concentrated the market, the higher the definition of risk in these stocks.

We saw this chart right at the beginning and said, oh my gosh, when we get to such a high level of concentration, my eye falls on two points on the chart: 73 and 2000, because I experienced it. Of course, 2000 was the peak of the technology internet, and then we had a bear market. So, this concentration is a warning sign of a bear market. Back to 73. I wasn't involved in the market then, but I did read about it, and when I got into the industry, it was just folklore. That's the end of the Nifty 50 index. The market again became concentrated on 50 stocks, leading to a terrible recession since the Great Depression.

So I look at these and say, if you look at other concentration peaks, you'll find that they tend to be associated with the enormous fear that a bull market is expanding.

Let us explain this. By 1932, there was an economic recession, and the Great Depression began in 1929. Of course, the unemployment rate was as high as 25%, not the current 4.1%. Real GDP actually fell by 30%, and consumer and producer price inflation fell, with real prices falling by 25% to 30%. Of course, those companies that had huge cash cushions and could generate cash flow even during an economic downturn were in a leading position, with disproportionately large capital flows. So, what happened next? We entered a bull market.

I believe that the market will rise by more than 50% or 60% in the next three and a half years. And its scope has significantly expanded, to the extent that the performance of small-cap stocks, mid-cap stocks, and even large-cap stocks at that time far exceeded the performance of large-cap stocks. Large-cap stocks have done a lot of work and are currently treading water. Meanwhile, those who were hit hard during the first three years of the Great Depression are doing better. We believe that this is still the case today. Of course, this will benefit strategies like ours, which have little overlap with broad benchmarks, and now Mag 6 and stocks like ours are disproportionately represented. All of our stocks focus on disruptive innovation. Therefore, as interest rates drop, our long-term bonds should be the primary beneficiaries of the expanding bull market.

As you know, we believe that inflation will continue to cool more than expected, and consumers have basically filled the rolling recession we have been in since the Fed began to raise interest rates. The housing market has almost randomly fallen and is still falling and actually is relapsing. We see housing, commercial real estate, cars, and now broader consumption slowing down.

This is a chart that shows how quickly mean reversion can occur. So you can see that with the rise of technology and the internet, value stocks outperformed the market for quite some time. Then suddenly, the bubble burst and in less than a year, value stocks went from underperforming by over 3000 basis points to outperforming by nearly 5000 basis points. Thus, as we approach the end of the bubble, the style of many investment portfolio strategies has shifted towards the internet. Those who do so may lose a great deal of commercial value. Strategies that stick to their style have undergone great transformations, reverted to the mean, and then performed well. Interestingly, as the dot-com bubble burst, we saw a reversal and mean reversion once again.

As you can see here, value stocks have been underperforming recently, as have long-term investment strategies like ours. We believe that both of these strategies will revert to the mean as interest rates fall.

Finally, I'd like to show you one of Mag 6's stocks, Apple. As you can see, we were shocked to see that Apple's valuation is now much higher. I think it's tripled. If I'm not mistaken, it's much higher than when the iPhone was launched, when Apple's valuation was supposed to rise sharply. Instead, what has happened recently is that its cash flow, especially when interest rates rise, looks very attractive. I've never seen the market buy into cash flow before, but that's the reality because Apple's revenue growth is zero. As of now, Apple's revenue growth has been low and zero for several years.

Now, through our collaboration with OpenAI, or at least by opening up to OpenAI and other large basic language models, it has gained some traction. We do believe that there will be a refreshing cycle. We believe that artificial intelligence will add some nice attributes and features, but we believe that this multiple re-evaluation, simply because it has cash, will give way in the next few years, especially as interest rates fall, as we believe. So the valuation rise in Mag 6 in recent years is due to cash. This tells us that there is a lot of concern in the market that the reallocation of stocks disproportionately flows into higher-cash safety stocks. We believe that we will see a return to the mean as interest rates fall over the next few years.

Now, through our collaboration with OpenAI, or at least by opening up to OpenAI and other large basic language models, it has gained some traction. We do believe that there will be a refreshing cycle. We believe that artificial intelligence will add some nice attributes and features, but we believe that this multiple re-evaluation, simply because it has cash, will give way in the next few years, especially as interest rates fall, as we believe.

So the valuation rise in Mag 6 in recent years is due to cash flow. This tells us that there is a lot of concern in the market that the reallocation of stocks disproportionately flows into high-cash safety stocks. We believe that we will see a return to the mean as interest rates fall over the next few years.

Editor/Lambor