"Wood Sister" elaborates: ARK's company valuation method, using Tesla as an example

On July 13th, in the monthly series program "In the Know," renowned investor "WoodSis" Cathie Wood, along with Tasha Keeney, the Investment Analyst and Institutional Strategy Director of Ark Invest, and Sam Korus, the Director of Autonomous Technology and Robotics Research at the company, discussed how ARK evaluates companies for valuation and makes investment decisions. WoodSis also shared her views on topics such as U.S. bond yields and stock concentration.

This article highlights the insightful viewpoints of the three individuals in the program:

1. ARK adopts a combined top-down and bottom-up evaluation method, valuing business lines separately.

2. In ARK's scoring system ranging from 1 to 10 for companies, if a score falls below 7 in any aspect, it is worth paying attention to; but if two scores decline, we will seriously consider whether to reduce the portfolio's risk.

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

4. We believe Tesla may be the first automaker to mass-produce robot taxis, and once scaled, the price of robot taxis could drop to as low as 25 cents per mile.

5. Tesla's "ups and downs" depend on its execution, with key factors that may be affected including: key personnel (Musk), personnel changes, moats, adoption of cutting-edge technology, battery costs, etc.

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

7. We believe Tesla is highly likely to launch a robot taxi network in the coming years, with a strong possibility of being launched within the next three to five years.

8. By 2029, the valuation-to-EBITDA ratio of Tesla's electric vehicle business is expected to decrease from the current 60 times to 19 times, with strong revenue growth and profit expansion.

9. In the long term, robotics, energy storage, artificial intelligence, blockchain technology, and multi-micron sequencing technology will increase actual GDP growth from 3% to 6%.

The following is an excerpt from the conversation:

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

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

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

Tasha Keeney: Thank you, Cathie. As we all know, ARK is very focused on disruptive innovation, and our investment team is tech-focused. So Sam and I have been collaborating for nearly a decade now, researching autonomous driving technology and electric vehicles. We have considered all the top-down analysis we have done in these two areas, which we will discuss later.

Next, once we identify potential names for the portfolio, we do bottom-up work. Bottom-up work involves qualitative and quantitative metrics based on evaluation. On a quantitative basis, you are probably aware that we have published a Tesla blog with our 2029 price target. Again, this is a combination of top-down and bottom-up. So, Sam, why don't you start by introducing your top-down research on electric vehicles?

Sam Korus: Of course. This ties into what Cathie mentioned earlier, leveraging the empowerment law and cost institution. So, looking at the decline in battery costs and explaining what we think will happen in terms of price parity for electric vehicles. This situation has already occurred in China, where you can see their adoption rates far ahead of the US, while in the US, this shift has not yet occurred in many areas. All of this guides us in making top-down forecasts, where we expect electric vehicles to expand from about 10 million in 2023 to 74 million by 2030. Therefore, by 2030, they may occupy almost all of the automotive market share. Then we combine it bottom-up, which is how we get differentiated perspectives.

Tasha Keeney: In terms of the outlook for autonomous vehicles, we believe that by the end of this century, the value of the robotaxi industry could reach $28 trillion. That's why when you look at our Tesla valuation, we believe that most of Tesla's value will come from this, as it will completely change the business model—shifting from one-time revenue from selling electric vehicles to recurring revenue from Robotaxi.

Of course, we believe that robotaxis are disruptive because their prices can be lower than all current ride-hailing options and significantly lower than the cost of driving a private car in the US today (about 70 cents per mile). Therefore, after scaling, the price of robotaxis could be as low as 25 cents per mile

>
> **Sam Korus:** Yes, in fact, in an annual survey of the most desired companies for recent graduates, SpaceX and Tesla still rank at the top, which is a good proof.
>
> **Tasha Keeney:** We have discussed this issue in the past as well. Our idea is actually that Musk leading many companies does help with talent recruitment. So, as Cathie mentioned, even though it's a challenging place to work, it's also a very ideal workplace. That's why, you know, there are rumors that Andrej Karpathy might come back.
>
> **Cathie Wood:** I'd like to add another point here. You will find that from a risk control perspective, you can see what affects our scores.
>
> **I just gave an example, which is the departure of key personnel.** JB opened this door, you could say, his departure happened as the electric vehicle story was accelerating. But another area of risk is governance, especially at Tesla. Of course, we evaluate the governance of any company. But to give you an idea of the issues we face here, you will remember when Elon tweeted that he was considering taking the company private. In the tweet, he mentioned that funding was secured. Of course, this angered the SEC. In fact, there were some lawsuits. So, when this situation occurred, we understood that the SEC was indeed investigating whether the funding was secure, and if this was an accurate description of what was happening within the organization, we knew this would distract the company's attention, and for this reason, we did lower that score.
>
> So, when we feel that something poses a risk, we do adjust the score. But what was interesting is that a few weeks after we lowered that score, Tesla released the specifications of their own artificial intelligence chips, and we looked at them and said, "Wow, these are much more advanced than we expected, and earlier than we expected," so the score for another moat was raised again.
>
> So you can see the dynamics of our scoring system. What I want to say is, **in this 1 to 10 scoring system, if a score is below 7, it's worth paying attention to.** At that time, the governance level did not drop below 7, and the moat score increased. **But if two scores drop, we will seriously consider whether to reduce the risk of the portfolio.** So, Tasha?
>
> **Tasha Keeney:** Thank you, Cathie. Yes, so I want to turn to the moat. You know, some of the things we have been considering here over the years are Tesla's vertical integration advantage. We believe they have been ahead of their peers for many years in terms of batteries, artificial intelligence, and data. As Cathie mentioned, Tesla also internally produces hardware, chips, and inference chips. Sam, tell us about Tesla's battery integration
**Sam Korus:** Okay, I want to say, especially when a company is at the forefront of a new revolution, there may be no supply chain. Therefore, Tesla's investments in battery manufacturing chemistry, as well as investments in power inverters, do set its performance apart from its peers. The current situation is still that **only one or two other competitors have similar efficiency to Tesla, but none can vertically integrate as quickly as Tesla.**

**Tasha Keeney:** In terms of autonomous driving, Tesla has access to billions of miles of driving data. As a peer, the data with Waymo is only at the million level. **So, this is an order of magnitude difference.**

This data will be used to train neural networks, allowing Tesla to layer autonomous driving functions. We believe these functions will eventually create a fully autonomous car, where you can actually take the wheel off the steering wheel. Of course, this is the basis of a robot taxi network.

Another point I want to make is that **the Supercharger network also provides a great moat for Tesla.** Of course, it is now the North American charging standard, and many other car manufacturers have also signed up to be part of this network.

**Cathie Wood:** Just look at the risks of emerging disruptive technologies. I can't tell you how many times we've encountered such situations: oh my god, this is a new type of battery, Tesla will be left behind because it is locked into its current strategy. We know how difficult battery technology is, and the likelihood of Tesla adopting new battery technology is very high because its expansion is built on batteries, so it certainly wants to maintain its lead. **So we will definitely consider the risks of new technologies emerging.** We will certainly discuss emerging technologies with Tesla, but every time we are confident and assured that they are very aware of what is happening in new technologies, especially in batteries.

**Tasha Keeney:** Yes. In terms of execution, another important qualitative score we judge each company on. Sam, tell us about production hell. Let's understand the history here.

**Sam Korus:** I think Tesla's ups and downs depend on its execution. You know, during the Model 3 production process, Tesla was called "production hell". I think we all remember that time vividly, when we saw this bright future, their delivery volume was thousands of units short, the stock price plummeted, and everyone's thoughts were like, "Well, they delivered a few thousand units less this quarter," what we need to consider is, is this quarter important? Or is there any flaw in the long-term story? Are they still expanding?

I think with Tesla, we see a real momentum in execution, they went through tough times, and now even Toyota says, you know, they make one of the best cars in the world. This is high praise for a company that is considered one of the best manufacturers in the world
**With the help of China, Tesla can expand its factories faster than anyone else in the world.**

Therefore, **I believe that in the field of electric vehicles, we have indeed seen a continuous strong improvement in execution.** However, this is also a problem we often discuss, with ups and downs. Perhaps, Tasha, I can throw this question to you, as there is definitely a start and stop somewhere, that is autonomous driving, claiming it will be achieved this year, what do we see in terms of execution in autonomous driving?

**Tasha Keeney:** Tesla plans to launch a robotaxi network, which we see as an exploration of the next major milestone. This is not an easy task, right? Making a fully autonomous driving car is very difficult. We know it is possible. Because competitors like Waymo have already launched on a small scale, **but we believe Tesla may be the first car manufacturer to launch on a large scale.** Tesla has already released the most advanced driver assistance features to date, and likewise, we believe they can stack these features to create a fully autonomous driving car.

Going back to Sam's point about how qualitative and quantitative interact, when we discuss all these execution metrics, this is what we consider when modeling Tesla. We believe that, due to the cash generated by autonomous driving technology and its successful production scale, **Tesla can expand from selling less than 2 million cars annually to, in our bear case, about 6 million. In our bull case, there could be 14 million cars.** Therefore, when we model the company, we will once again consider all these metrics.

**Sam Korus:** Another area of execution we see on Optimus is the simultaneous use of autonomy and manufacturing technology, right? This is true fusion. I think their execution speed has surprised everyone. You know, if you go back a few years, people would laugh at someone wearing a robot suit dancing on stage. Now, Tesla has at least a few robots working autonomously in the factory. Seeing all this come to fruition is truly amazing.

**Cathie Wood:** I want to emphasize here the execution, especially the execution related to Tesla. We know that Elon is very committed to his vision, and many times he will articulate his vision on "Elon time," and I think we all have to adapt to Elon time. But why does he do this? He does this not only to signal to suppliers, "Hey, this is my schedule." Get all the suppliers ready, but also to motivate employees to focus on achieving goals in a very short time. Therefore, **another thing to focus on in the execution process, you will see the first thing we focus on is insufficient or declining R&D.**
Now let's look at this issue from two perspectives. Research and development accounts for 1% of sales, where do they spend this money? Because sometimes we disagree on a certain direction. I know when Toyota shifted from electric to hydrogen fuel cells, we owned stocks at that time and saw them redirecting R&D funds to hydrogen fuel cells. We have studied how expensive the infrastructure for hydrogen fuel cells will be, especially compared to electric fuel cells. Based on this, we sold the stocks.

**Tasha Keeney:** Great. You know we have touched on some key points, but let's continue discussing product leadership. I think in the electric vehicle industry, we have a lot of evidence from Tesla.

**Sam Korus:** Yes, emphasizing again, this is an ongoing debate and a quantitative debate. You know, as other car manufacturers continue to launch their products, Tesla's market share in different regions in the US will certainly be questioned. However, in comparison with Apple's profitability, we can see that as the industry develops, Apple's sales are declining but profits are increasing. So, these are all ongoing internal dialogues and debates. People also like to discuss these issues on Twitter. In any region where Tesla's stock price drops, you can see people discussing this issue. So, this is also an issue we closely monitor.

**Cathie Wood:** One of the recent developments is that General Motors and Ford have exited the electric vehicle market because they couldn't see profitability. It is well known that Ford loses $100,000 per car, maybe in the coming years Tesla's market share in the US will be higher than we imagine. Of course, it will drop from the level of 90% or 95% wherever it is. Just like Apple in the smartphone industry.

But we have received signals from other car manufacturers, how much are they investing in this area? The withdrawal is very interesting. The only way to achieve profitability is to scale up. So, from the perspective of market share, this is a very interesting moment for us.

**Sam Korus:** And Tasha, you have mentioned it, maybe it also involves autonomy. I know just this morning, we had a large-scale discussion comparing Waymo and Tesla as well as the leading positions of their autonomous driving products.

**Tasha Keeney:** Yes, you know, combining Cathie's views, when we observe traditional car manufacturers like General Motors and Ford, we find that they have withdrawn from the autonomous driving business - Ford sold its autonomous driving division, General Motors' autonomous driving division Cruise temporarily ceased operations - although they are now trying to restart.

So, when we look at the competitive environment in the US, **actually there are only Waymo and potentially Tesla.** Once again, Waymo has hundreds of cars on the road. Tesla has millions of cars on the road, and they believe these cars can become self-driving cars
Therefore, as I mentioned, from the perspective of data advantage, they have already had a larger scale. We believe they can translate this into an advantage in artificial intelligence on the road. They can launch a robot taxi network that will be available in many cities, not just the selected cities where Waymo has been able to offer services so far.

The last point I want to talk about here is theoretical risk. We discussed some key points in this regard again. In terms of the valuation of theoretical risks, we conducted a Monte Carlo analysis on Tesla (evaluating the potential risk impacts in various real-life scenarios). We have many variables and adjust the upper and lower limits of these ranges based on the probabilities we consider appropriate. For example, we believe it is very likely that Tesla will launch a robot taxi network in the next few years, at least within the next two to three years.

We also took into account the timeline delays we discussed, right? Elon has promised multiple times that they will manufacture a fully autonomous vehicle, but this has not happened yet. Once again, crossing this threshold is a very difficult thing to do. So we cannot be completely certain whether the launch date of the robot taxi network will be July 9th or any other specific date. But we try to use our research and analysis to establish a timeframe that we believe may happen.

**Cathie Wood:** I would like to add some content about regulatory risks. When we first started the Tesla journey, we thought regulatory risks were very high. But since we began this research, what has happened in the past decade is that the U.S. accident rate has sharply increased after decades of decline. I believe the lowest number of car accident deaths in the U.S. was around 30,000 people, around 2014. Since then, this number has risen to 45,000 people. This has caught the attention of regulatory agencies. So now they are studying the data. And Tesla is able to provide a large amount of safety data.

I will hand over this topic to Tasha, who has done a lot of research on safety. Interestingly, this has not received much attention, as the entire Volvo brand is built on safety. Some of the numbers Tasha found in her research are quite astonishing.

**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 that of manually driven vehicles, **in terms of accident rates, 80% safer**. We actually have data to prove this. So we have seen that Waymo is actually safer than the national average for cars. When you look at Tesla, **Tesla's FSD driving is about 5 times safer than manual driving Tesla**. This is actually based on the latest available data points.

Elon has said they believe visibility could improve four to five times. When you compare it to the national average, you'll find its safety is about 14 times what it used to be. So, you know, we have seen evidence that autonomous driving vehicles are safer than human-driven vehicles
We believe that this is what regulatory agencies are seeking when deciding whether to allow these vehicles to operate on public roads.

Another point I will mention is that Tesla is in discussions with China regarding the implementation of FSD, 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 have already discussed Elon's central role, especially in fully realizing the vision of people driving autonomous vehicles. So, we have indeed taken this into consideration, as well as the importance of his role in the rollout of Robotaxi. I think, even he himself has said that at a certain point, it would not make sense for him to continue as CEO and take on a more visionary or product-driven role. But I think we have discussed this issue, **it is very important to empower the autonomous team to achieve commercial launch.**

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

Let me set the stage. The measure we have chosen is the enterprise value-to-adjusted EBITDA ratio, and we adjust EBITDA in two ways:

First is equity incentives. We do believe that incentivizing employees (including Elon, by the way) and aligning them truly with shareholders is very important. So, the second adjustment is for R&D, specifically normalizing R&D standards. Our companies tend to spend too much on R&D, and of course, we want that. We want them to sacrifice short-term profitability because, especially in the world of artificial intelligence, the winners take all.

Therefore, our assumption is that **the ratio of electric vehicle business valuation to EBITDA will deteriorate over the next five years, declining 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 issue?

**Tasha Keeney:** If you look at Tesla's electric vehicle business, today's EBITDA is around $57, approaching $60 in the final year of our model. We have our own valuation multiples for each business line, and by 2029, the largest part of the valuation cake under evaluation is autonomous driving. It is expected that the multiple of electric vehicle business valuation to EBITDA will be 19 times at that time. So, as Cathie mentioned, **from around 60 times now to a significant compression to 19 times.**

In fact, in other business areas including electric vehicles, we assume lower multiples, around 12 to 13 times. Therefore, the blended average multiple is even slightly below 19. Thus, based on our revaluation of Tesla's business, it can basically be considered a mature business, and in fact, **we believe Tesla will maintain a considerable 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, ARK Invest:** Let me say it again, we set a minimum annualized return of 15% over a five-year period. Therefore, when I say from 60% to 18%, our revenue growth and profit margin assumptions must outweigh it. Everyone knows that in our empowerment methodology, we are very rigorous in how we build models for long-term cost reduction and scale expansion. So, I think what we will discuss here might be a condensed version of the "Global Report". No, this time we won't spend too much time on fiscal or monetary policy. Fiscal policy, for obvious reasons, Washington is in trouble.

> Chairman Powell seems to have emphasized monetary policy in his latest testimony, now shifting his focus to employment. He is looking at some published statistics and has stated that he also acknowledges that inflation is continuing to ease. This week, Austin Ghoulsby, whom I think may be the biggest dove, said "aha, this is what I've been waiting for" after the CPI report was released. So, we will only discuss economic indicators, last week's employment report, which once again exceeded consensus expectations in my opinion. But I think the consensus expectation was 190,000. The result was 206,000. But after adjusting for another downward revision, the actual number was 95,000, with household employment increasing by 116,000 after a decrease of 408,000 last month. So household employment is weak, flat or declining year-on-year, while non-farm employment remains slightly above half a percent. Temporary assistance numbers are declining rapidly, down by 49,000. This is a fairly large number for temporary assistance. So I think Chairman Powell rightly took note of these.

> Of course, another variable the Fed is watching is inflation. This week we got the CPI, which was below expectations, which did not surprise us. As I mentioned in the previous article, no, we see price cuts, not just reducing inflation, but price cuts. Walmart, Costco, Best Buy, McDonald's, Wendy's, and even Starbucks all have promotional packages, which is very unusual. So the CPI actually decreased by 0.1%, which is headline news, making the figure grow by 3% year-on-year, not yet reaching 2%, but we believe it will soon reach this target. The core only rose a bit. Yes, 0.1%, slightly lower than expected after an increase of 0.2% last month, the current core year-on-year growth rate is 3.3%. We once again believe this ratio will reach 2%, I mean close to 2%. We also got the PPI, which is a bit hotter than expected.

> What does this tell us? **This tells us about profit compression.** Therefore, for many observers, they are concerned that we will see cost-push inflation, just like we saw in the 70s, where costs kept rising, they were forced to raise prices, and consumers did not accept higher prices. We see some companies, even PepsiCo, also announced a 4% decline in its sales in North America this week, which is very unusual for a consumer staple company
Now we have indeed experienced some unusual events, the COVID-19 pandemic may be one reason, but we do believe the economy is another reason. So, these factors may each account for half, maybe, who knows. We believe that Pepsi will have to respond with lower prices.

I won't list all the economic statistics now. What I want to tell you is that when I carefully studied and prepared for this, I found that almost all statistics are weaker than expected, especially in housing and capital expenditure. Both of these have high multipliers associated with them.

Interestingly, one number that is stronger than expected now is personal income growth of 0.5%, but spending only increased by 2%. What does this tell us? This tells us that the consumer savings rate is starting to rise. When does this happen? This situation usually occurs when people are generally worried about their jobs and the economy.

So, I will show you charts related to this content in this group of charts. So let's start with the charts now. Okay, you can see here the issues the market is currently grappling with.

This is a long-term chart of the 10-year U.S. Treasury yield in the early 1960s. You can see that the trend has been upward from the 1960s to the early 1980s, significantly rising from low to mid-single digits to over 15%.

Since then, we have been in a downward trend. You can see that the downward trend seems to have ended. And this is also one of the reasons that has caused a lot of controversy. One of the reasons it ended is that the Fed raised rates 22 times to combat inflation, feeling it was behind and decided to take a tough stance. This is one of the reasons for the rise in long-term Treasury yields. If it hadn't risen, our yield curve would have inverted by about 500 basis points or 5 percentage points, which is a very unusual situation.

The question now is, have we broken this downward trend? The answer may be yes, as we are close to zero, and negative interest rates are not a good thing. This may be related to a very difficult economy. We expect the future economy to be softer in the short term than most people expect, possibly due to consumer spending. In the long run, the type of economy we expect is priced much lower than expected.

In fact, due to cyclical reasons, we see a trend of deep deflation brewing in the short term, pricing has gone too far due to supply chain shocks. Consumer goods companies have taken advantage of this, and now they will have to lower prices, which is cyclical. In the long run, deflation has a long-term reason, which is innovation, real disruptive innovation, which is essentially deflationary.

It follows a learning curve. We see efficiency and productivity constantly improving, manifested in the cost reduction of the technology itself, creating many mass market opportunities now. So, we will see the prices of these technologies drop, but the unit quantity will increase significantly. Therefore, nominal GDP may be in the range of 5% to 10%. Over time, in the long run, the U.S. Treasury yield has been consistent with the nominal GDP growth rate
Therefore, we believe that in the short term, due to cyclical reasons, US bond yields will decrease.
>
> Yes, in the long run, we do believe that the long-term downward trend of US bond yields has been broken, as we believe that the substantial unit growth brought by these new technologies may lead to a surprisingly high level of real GDP growth. In past webinars, we have shared that we believe that in the next 10-15 years, with the simultaneous development of multiple innovative platforms, the real GDP growth rate may exceed the 3% range seen in the past 125 years. In the early 1900s, there were the telephone, electricity, power, and internal combustion engine, which raised the GDP growth rate from 0.6% to 3%. We believe that in the long run, robotics, energy storage, artificial intelligence, blockchain technology, and multi-micron sequencing technology will raise real GDP growth from 3% to the range of 6%.
>
> The next chart involves the cyclical part of the economy. We are closely monitoring the ratio of metals to gold. You can see how close the correlation has been since 0.8. When the price ratio of metals to gold decreases, they reflect each other until recently, when US bond yields also declined. Then you will find that this correlation has been broken recently. The ratio of metals to target prices has decreased. It has dropped to the 0.8, 0.9 level. But yields have not yet fallen, and we believe they will.
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> As I mentioned earlier, for cyclical reasons, we have been waiting for some signals from the ratio of metals to gold to guide us in another direction. That has not happened. Therefore, we do believe that the 10-year US bond yield will decline. I want to remind everyone that we are in a long-term downward trend, with the actual downward trend starting at $0.8 after energy prices soared to the $47 price range. Since then, this trend has been declining. The COVID-19 pandemic brought it to very low levels. Supply chain shocks have intensified again and are currently on a downward trend. Today's commodity prices are the same as in the early 1980s. This does make sense.
>
> The next chart is something I have described before, but here it is described last, which is the yield curve. So, this is measured by the US 10-year Treasury yield relative to the 2-year Treasury yield, and you can see that the 10-year Treasury yield is lower than the 2-year Treasury yield. This usually happens before an economic recession. The shaded area on the chart is a recession. You can see that when we see an inverted yield curve, we usually fall into a recession within a year and a half. This situation has not happened yet, although I do believe that with all the downward revisions we are seeing in employment indicators and many other indicators, the National Bureau of Economic Research's score for an economic recession may date back to sometime last year.
>
> So you can see another thing, which is the downward trend of the yield curve since the global financial crisis. I think during Covid, you can see that we did see the yield curve steepen, meaning it rose from about 0% to 1% and a/2%
I think it will go higher like it did during the global financial crisis. Why not? Governments around the world, whether monetary or fiscal policymakers, are doing their best to tighten the financial environment, but it should have returned to the range of 200 to 300 basis points. Why not? We can see obvious deflation in commercial real estate, office space, and we are increasingly considering multi-family residential space. So this is one of the roots of cyclical deflation.

I mentioned another issue before, consumers, pro-consumer companies are lowering prices. Here we are upside down, you can see we have been upside down for a long time. In fact, Fed Chairman Volcker tried to curb double-digit inflation in the late 1970s and early 1980s, a time longer than any time since Fed Chairman Volcker. We never reached double digits, but Fed policy based on this looks as tight as it did then. That's why I keep coming back to the potential downside risks and the Fed may have to change direction.

The Fed has four more opportunities to reverse policy this year. At the end of this month, July, September, November, and after the election in December. We wouldn't be surprised if there were three rate cuts. Because these deflationary forces continue to accumulate over the next few months.

On the next page, I want to explain the adjusted corporate tax rate, these data come from the GDP account, you can see that since the early 1990s, profit margins have indeed been increasing, and now it seems to have peaked. We believe profit margins will decline further, as companies will be forced to lower prices if they want to maintain unit sales. **Therefore, we do believe that profit margins may fall below the levels of 2014.**

In other words, we generally believe that due to all the new technologies, especially artificial intelligence, artificial intelligence, and the productivity boom we see in the future, the upward trend or at least a high level will continue. Therefore, the decline in profit margins will be more cyclical. But in the long run, we believe that profitability will remain at a relatively high level. Perhaps we will not continue to rise. By historical standards, this figure is already quite high, 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-19 pandemic, this ratio rose to about 32% because no one was spending money. Of course, fiscal stimulus also provided the necessary funds. People saved a lot at first, but now it's completely exhausted. By historical standards, our savings rate is at the low end. You can see in the shaded areas, these are periods of economic recession where the savings rate rises.

We just got another reading on the savings rate. It has now risen to 3.9. I remember it was 3.6. So, as I mentioned before, the reason is that spending growth is lower than income growth. Therefore, this is a cautious signal on the next chart.

Now we start discussing market indicators. This chart is made by Goldman Sachs, it is an indicator of measuring stock market concentration. Perhaps you have heard of the tech stocks "Seven Sisters", it has now become "Six Programs"
When Tesla started to perform poorly this year, those who named it kicked it out of the game. Therefore, Mag 6 led us to break the record for market concentration. Many people think, "Well, I feel safe with Mag 6," as they have a large cash flow. It seems to be in the best position for artificial intelligence. But we would say, the more concentrated the market is, the higher the risk of these stocks is defined.
>
> Now, as we look at this chart from the beginning, we say, "Oh my, when we reach such a high level of concentration, my eyes fall on two points on the chart: 73 and 2000, because I have experienced it." Of course, 2000 was the peak of the technology internet, and then we experienced a bear market. So, this concentration is a harbinger of a bear market. Going back to 73. I didn't participate in this market at that time, but I read about it. When I entered this industry, it was just a legend. This was the end of the Nifty 50 index. The market once again concentrated on 50 stocks, resulting in a terrible bear market and the most severe recession since the Great Depression.
>
> So I look at these and say, if you look at other concentration peaks, you will find that they are often related to the huge fear of a bull market expansion.
>
> Let's explain. By 1932, the economic recession, the Great Depression began in 1929. Of course, the unemployment rate was as high as 25%, not the current 4.1%. Real GDP fell by 30%, consumer and producer price inflation fell, and real prices fell by 25% to 30%. Companies with huge cash buffers and the ability to generate cash flow even during an economic downturn were in a leading position, gaining disproportionate funding. So what happened next? We entered a bull market.
>
> **I believe that in the next three and a half years, the market will rise by more than 50% or 60%. And its scope will significantly expand**, to the point where small-cap stocks, mid-cap stocks, and even large-cap stocks outperform the market by far. Large-cap stocks have done a lot of work and are treading water. But others who were hit hard in the first three years of the Great Depression are performing better. We believe it is the same now. Of course, this will benefit strategies like ours, which have almost no overlap with broad benchmarks, and now the proportion of stocks like Mag 6 and ours is disproportionate. All our stocks focus on disruptive innovation. **Therefore, as interest rates fall, our long-term bonds should be the primary beneficiaries of the bull market expansion above.**
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> 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 started raising rates, the housing market is almost randomly falling, and still falling, and actually relapsing. We see housing, commercial real estate, cars, and now broader consumption slowing down.
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> This is a chart that shows how quickly the mean reverts. So you can see that with the rise of the technology internet, value stocks outperformed the market for quite a long 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
As we get closer to the end of the bubble, many investment portfolio strategies have shifted towards the internet. Those who do so may lose a lot of business value. Strategies that stick to their own style have undergone significant changes, returning to the mean and then performing well. Interestingly, as the internet bubble bursts, we see a reversal again, returning to the mean.

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

Finally, I want to show one of the stocks in Mag 6, Apple. You can see that what surprises us is that Apple's current valuation is much higher. I think it's three times higher. If I'm not mistaken, this is much higher than when the iPhone was launched, when Apple's valuation should have increased significantly. Instead, what has happened recently is that its cash flow, especially when interest rates rise, looks very attractive. I have never seen the market pay for cash flow, but that's the fact, because Apple's revenue growth is zero. For now, Apple's revenue growth has been very low, zero growth for the past few years.

Now, through cooperation with OpenAI, or at least opening up to OpenAI and other large basic language models, it has gained some momentum. We do believe there will be a refresh cycle. We believe that artificial intelligence will add some good features and functions, but we believe that this multiple revaluation, simply because it has cash, will give way in the coming years, especially when interest rates fall, as we believe. So the valuation increase of Mag 6 in recent years is because of cash. This tells us that there are many concerns in the market, namely that the reallocation of stocks disproportionately flows into safe stocks with high cash levels. We believe that as interest rates fall in the coming years, we will once again see a return to the mean.

Now, through cooperation with OpenAI, or at least opening up to OpenAI and other large basic language models, it has gained some momentum. We do believe there will be a refresh cycle. We believe that artificial intelligence will add some good features and functions, but we believe that this multiple revaluation, simply because it has cash, will give way in the coming years, especially when interest rates fall, as we believe. So the valuation increase of Mag 6 in recent years is because of cash flow. This tells us that there are many concerns in the market, namely that the reallocation of stocks disproportionately flows into safe stocks with high cash flow levels. We believe that as interest rates fall in the coming years, we will once again see a return to the mean