How To Justify The Valuation of Tesla Stock?
Photo by Austin Ramsey on Unsplash

That’s it. Tesla is now part of the S&P 500 index, achieving the status of a safe bet and representing one of the first weightings of this prestigious index, whose members include Apple or Amazon.

Many financial analysts have long been skeptical of Tesla’s valuation. Elon Musk himself tweets, in May, the stock price is too high.

But it looks like the pandemic has not had an effect on Tesla which signs a very convincing third quarter. The stock price is only going up. So what’s happen? What can we find in the leader of the electric car?

Market Value

Why is difficult today is to differentiate the quality of the company from the stock price? We must therefore analyze Tesla as a stock market valuation and not as a company. Tesla has a technological advance in electric cars. We all agree.

Tesla’s turnaround in fortunes this year came after the company managed to report profits for five consecutive quarters.

But for a market valuation, the central question is whether Tesla is really worth that much. As of December 2020, Tesla has a market cap of $658 billion. It makes Tesla the world’s 9th most valuable company by market cap. More than General Motors, BMW, Volkswagen, and Chrysler… Can Tesla reach a market cap of $ 1 trillion?

As Tesla’s loyal investors reap the rewards of their faith in Musk’s vision, the big question for 2021 is how to trade this stock in the future. The analyst community is divided. Is Tesla a bubble or the new El Dorado?

A major challenge for investors and analysts is how to justify further gains for a stock that is trading well above high valuations. For this to be justified, it is not enough just strong growth. This is already the case but it is not enough. It takes more than that. In fact, the market is already betting on the fact that it will become number one in the world as it has done with Amazon in the past. This helps to understand what is called a high valuation on the stock market.

What is the motivation of buyers to buy so high? What are they based on?

For instance, Piper Sandler recently raises Tesla’s price target to $ 2,300. Market studies notice competitive advantage, a strong balance sheet, and finally the ability to generate cash for the company of Elon Musk.

Tesla’s cash position is improving but in these three points what I am really interesting to analyze is one aspect of the competitive advantage. How is tesla different from others? So how can Tesla get ahead of it never to be caught?

Of course, we could focus on all material innovations such as batteries to defend Tesla’s lead over others. But technological innovation at Tesla is quite different, it could well be software.

Tesla’s innovation strategy, which focuses on transforming the automotive industry as a whole, demonstrates, in particular, the validation of hypotheses and the implementation of new technologies in the market.

Tesla’s hardware architecture is an assembly of batteries at the base, two electric motors, no transmission… All of this also gives it an advantage over competing electric vehicles built on traditional vehicle architectures.

What makes this part of the strategy truly unique is not only the fact that Tesla produces electric vehicles, but also that it introduced a vision for assembling them. These are new hardware and software architecture. A Tesla has more software than the average vehicle and is integrated around a single central software architecture. Tesla has a great ability to update their software and optimize vehicle performance thanks to this very unique architecture that most traditional cars, which also have the software, find it hard to emulate.

Full Self-Driving (FSD)

Autonomous driving is Tesla’s biggest opportunity. Much of Tesla’s earnings call was devoted to discussing the company’s efforts to achieve full self-driving capability (FSD). Let’s dig a little deeper into this technology.

Tesla’s vehicle software, which currently enables the FSD capability, has improved over time. Its release followed a “fundamental rewrite” of the FSD (for “full self-driving”) software, and which now combines imagery gathered from all eight cameras of a Tesla vehicle into a series of linked images, as opposed to the image after image.

New steps for the autonomous car? On October 21, Tesla released the beta version of its FSD update.

In August, Musk promised a “quantum leap” as to the capabilities of this option at $ 8,000, explaining that the software had not been simply improved but completely rewritten by his teams. Explaining himself to use the alpha version of the FSD mode between his home and work, he promised in particular that the cars with them were able to perceive their environment in “four dimensions” and not in two.

This improvement of the FSD allows cars to drive alone on small roads or in town, and no longer only on freeways or expressways. Only a few customers have been chosen by the brand to test this advanced mode, which is not yet available to the general public. Drivers should keep their hands on the wheel and be extra vigilant because the vehicle can do the wrong thing at the wrong time.

Thanks to many kilometers of data gathered by enthusiastic beta testers and feedback to Tesla, FSD appears to be getting rapidly better.

Tesla Autopilot FSD Oracle Park to Crissy Field at Night 1x Raw Footage — Whole Mars Catalog

When activated, the digital instrument cluster takes on new graphics: vehicles and obstacles are framed, along with traffic signs. This visually represents the observations of the software.

The autopilot was reserved for highways. Another system was used for parking assistance and low-speed maneuvers. Until now, urban speeds were a problem for engineers. Testing in the real world is key to Tesla’s strategy to expose the neural net and algorithms that underpin the self-driving software to “edge cases”, that would not otherwise occur in a simulated environment.

The YouTuber Dr. Know-it-all Knows it all shared his thoughts on FSD and describes the system that allows objects to be identified through an image-based neural network and then find the object in the image database. Semantically, recognizing a cat does not mean that the computer understands what a cat is. It is simply the assembly of edges, pixels, and colors that is associated with a label which it knows is called “cat”.

Trajectory prediction and 4D data continuity — Dr. Know-it-all Knows it all

This affects the driving because the computer only detects what a picture contains in relation to a tag, it doesn’t give the computer any more information about what a cat actually is. It doesn’t give any idea of how a cat behaves.

In order to drive effectively, the computer must know the difference between the images and what they represent as well as being able to anticipate what will be in the next image. This is what Dr. Know-it-all called “continuity”. If the computer detects what is in one image, the computer should be able to tell that it is in the next image, in four dimensions over time. This is why it is the “4D”, he noted. Time, or continuity, is the 4th dimension. A dimension where the algorithm would be able to predict variations in speed or even changes in direction of objects near the vehicle.

We need to move forward in this direction and optimize the semantics of the computer in order to avoid very rudimentary driving errors and achieve the sci-fi autonomous driving that we expect, with the car driving itself. For this to happen, we need data continuity over a long sequence of images or videos and a temporarily semantic understanding of what the car sees. This is where 4D training comes in. He noted that Tesla’s FSD looked at eight individual cameras as well as radar and sonar about every 30 seconds. It is very fast treatment. The FSD has treated all of this information separately. It identified the objects and then he acted on them.

Tesla’s Competitive Advantage

The new beta of FSD with 4D capabilities uses the Tesla inference engine and the chips Tesla has in its vehicles. The eight cameras are now linked together in a single view, and it’s a video sequence instead of individual images. Along with this, there is object detection which has more information.

Besides the likelihood of fewer errors in semantic identification over time. What this 4D training opens the door to is trajectory projection. This would require the computer to have a large amount of knowledge because it has to understand what these objects are. The computer now knows that it must take immediate action to avoid this object which can move on its own or, at the very least, that it must break quickly to avoid a collision with the object, or use different calculations to avoid hitting it.

This type of trajectory projection is what humans do extremely well, at least if we are paying attention while driving. Existing software like Waymo and GM Cruise exactly map the environments around them and can track those things. They can sense objects in the way and brake if they need to, but they lack the understanding of Tesla’s new FSD software.

Not only are there a variety of objects in the world that can get in the way of the car, but the computer must also determine if these objects are moving, standing still, how dangerous they are, and then be able to respond. Along with this, the computer must also determine if things are far enough away.

The software security of such systems seems far from certain. A hacker, known as Green, discovered also the actual system settings of the beta version of the brand’s full self-driving feature. The system has dozens of parameters and settings. But what stands out most is that it is possible to make a detailed view of the vehicle appear in the world while a Tesla is in motion. One can see the internal states of the system, which show the dozens of parameters including controls for FSD, camera information, and ultrasound. Another hacker unlocks the “augmented vision” mode used to understand what the car is seeing and build confidence in the system.

There was a time when manufacturing seemed to be Tesla’s weakness. Manufacturing issues affected the initial production ramp-ups of the S, X, and 3 models. But Tesla’s Model 3 launch at its new factory in China and the company’s new Model Y at its California plant came about not only ran smoothly but also at faster rates than previous launches.

The promise of the new FSD is beautiful and the timing of the competition imposes urgency. Tesla claimed the possibility of 30% gross margins if more customers choose to purchase the company’s FSD software.

Dominating the industry given its size, structure, and politics is a challenge for Tesla. However, the multiple challenges facing the industry’s economic model give it a competitive advantage.

Tesla investors must still be patient. Many criticisms are indeed directed at the manufacturer because of its communication regarding the automation of driving.

Tesla is valued as a technological innovation. Tesla’s current valuation does not imply that it is only an auto company. Tesla buyers and investors are betting that, like Apple, the company will soon have a series of services built into its hardware that will make Tesla more than just a car maker.

Summary
['Daniel Leivas']
['Self Driving Cars', 'Technology', 'Tesla', 'Electric Car', 'Stock Market']