Tesla, TSLA & the Investment World: the Perpetual Investors' Roundtable

[ZachF]

The question is, will we hold these gains or will they push it to max pain if volume gets low in the afternoon?

 

[phantasms]

The question is, will we hold these gains or will they push it to max pain if volume gets low in the afternoon?

My gut is any serious push down will get bought up. Maybe we'll see one of those YOLO dive downs right at the end.

 

[TheTalkingMule]

Huge amount of volume there that was separate from any other stock moves/volumes. Sadly......that volume is now disappearing again. Shucks.....I was like "Is this the day we finally get a big up day on 30+ million volume??!?"

Hey, I'll take this sign of a pulse. And the sheer wall it created when someone just wanted a few hundred k shares. If that's the SP reaction to our first purchase for 3Q earnings, this bodes well!

$850 then $1000 for 3Q and 4Q is making a lot of sense. Perhaps a bit of macros and mania could even drive us at least temporarily higher after 4Q. Infrastructure passed, etc...

 

[StarFoxisDown!]

The question is, will we hold these gains or will they push it to max pain if volume gets low in the afternoon?

You answered your own question. If volume stays consistent and strong, it won't be dropped. In fact I could see it breaking free to 780 before they'd really try to step in.

But if the volume drops, like it's been doing in the past 45 mins, then good chance we get dropped to under 760 at minimum.

 

[woodisgood]

It feels like our whale is getting a pretty good idea - should he have desired to study the information gleaned during his purchasing spree - of exactly how tight this float is.

 

[Maarten]

Somebody already posted this video, but something about Mayur’s focus on ROIC and comparison of Tesla’s 23% to Apple’s 40% bothered me and I believe I figured it out.

ROIC on EXISTING (already deployed) capital (like Apple) is not that pertinent.

E.g. Assume another company (Apple Prime) has 2.5X more capital deployed than Apple but only has a 20% ROI vs Apple’s 40%, but is identical in every other way. Apple Prime should be more highly valued, because the cash flow would be greater.

Apple OBVIOUSLY cannot get a 40% ROI on NEW capital deployment, because if they could, they would immediately halt buybacks, dividends, deplete their bank account and borrow as much as possible to invest that new capital at a 40% rate of return

So ROEC (Return on existing capital) is just not important. Nobody cares about how much capital you had to deploy to get your present cash flows. Only the size of the cash flows and your present debt/cash balance matters.

So while Tesla has 23% ROEC, that’s not important. What IS important is their RONC (Return on New Capital).

Supposedly GF Shanghai Phase 1 only cost $1B. At 250k units per year and $10k gross profits / unit, that’s a staggering 250% gross profit return on that capital. I would imagine net cash flows from that factory would be a huge portion of that as OpEx shouldn’t be that high for that factory alone and/or China operations. Note: I believe GF Berlin and Austin are not that cheap, so I wouldn’t expect that RONC.

So RONC is one of the largest determinants on growth rate. And it is growth rate that is important! I believe Mayur mentioned legacy auto gets 10% RONC, but since new capital costs them 10%, they have no motivation to expand.

So ROEC is an historical measurement that is only important in so far as it helps predict RONC, which is EXTREMELY important as well as the total addressable market which helps decide how long a very high RONC can continue. In Tesla’s case, the addressable market for transport and energy is GIGANTIC, so they have a huge runway, which becomes infinite if they solve TeslaBot.

I would say that $10k gross profits/unit for GF Shanghai is quite a bit on the pessimistic side.

 

[TheTalkingMule]

The question is, will we hold these gains or will they push it to max pain if volume gets low in the afternoon?

I think it's too early for people or algos to be desperately gobbling up shares at $759 this afternoon, there's a whole week before P&D. Lets see what the MM appetite is to maintain order. As of now there's no volume and $760 would be easy peasy for them to nail.

 

[AudubonB]

Peripherally relevant news from the North Country:

A discussion two days ago with the on-site manager for Yukon Electric's Destruction Bay* mini-station (three generators; largest is 400kW), as well as manager/proprietor of the adjacent hotel/gas station/restaurant "Talbot Arm" was similar to one he and I had five or six years ago: he would be amenable to hosting EV charging, but he remains of the opinion that EVs are not appropriate for the remoteness of his location (ours is even more isolated). I did not counter his viewpoint at all but the advancement of Tesla's industrial battery banks makes it super-obvious to me that far-flung locations such as that one (and us) are so perfectly appropriate.

*This is on the shore of Kluane Lake, in far western Yukon Territory.

A few zillion miles further south, here are pix from yesterday of the second-furthest north site of SpCs as they march north in Canada: Quesnel. I hadn't time to wander around downtown Prince George to assess the situation there, at the #1 most northerly so far. Quesnel's are ready to go; awaiting BCHydro to flip the switch.

 

[jhm]

I have a hunch that NHTSA will want more than 95% confidence that it's better before declaring it's acceptable; otherwise I agree. Also, because of the politics of it, they might want strong proof that it's significantly better than humans by a large margin, not just that it's better by any nonzero margin. At first glance, such a policy might appear irrational or arguably unethical, but I see room for more nuance. The general public is predictably irrational, has very little appreciation for statistics and mostly reacts to scary or enraging anecdotes. If public backlash ends up shutting down the Lvl 4/5 autonomy program shortly after it arrives on the scene, this will likely push the advent of widespread adoption years into the future, maybe even a decade. This is an unacceptable opportunity cost given the profound benefits of widespread FSD.

So, what if the real goal is proving that it's 10x safer with 99.9% confidence, instead of proving it's 1.01x safer with 95% confidence? This would align with Tesla's MP Pt 2 which states a target of 10x safer than humans before "Beta" label is removed. In Excel, the formula is =POISSON.DIST(0,0.12*6000/100,TRUE). It turns out that 6 billion miles of data with zero deaths is precisely the minimum amount needed to make this conclusion. This can't be just a coincidence.

Moreover, this simple hypothesis test structure also assumes that the sample is fully representative of the scope of possible driving conditions. As we know, driving conditions vary wildly across the country and across different times of day, and as such the likelihood of producing fatalities or injuries is not 100 across all miles. The case is a lot weaker with using only 250 million miles of data if there are representativeness concerns. It could be tricky to demonstrate convincingly that beta testing of the software is not being done in some way that biases the answer, even if unintentionally. But with 6 billion miles of data, odds are that even underrepresented situations are still getting plenty of attention.

Also, I'm a longtime lurker and TSLAnaire. Thanks for all the great analysis and fun over the years. Time to start contributing.

Thanks for your response. I'm not going to address the politic here, which can easily take us out of realm of statistical analysis. Rather, I'd point out that you seem to be confusing the null hypothesis with the alternative hypothesis, which is pushing you to suggest a test size which larger than it needs to be on purely statistical grounds. So let's be clear about a proper setup of the statistical test.

Null Hypothesis: Tesla death rate = 1.2 per 100M miles
Alternative Hypothesis: Tesla death rate = 0.12 per 100M miles

Since we wish to show that Tesla has 1/10 the average rate, this is our alternative hypothesis. The hypothesis testing framework actually become much simpler when you have a specific alternative hypothesis in mind.

Let's consider a test with 800M miles. The number of fatalities is our test statistic. Under the null hypothesis, it is Poisson with mean 9.6, and under the alternative hypothesis it has mean 0.96. To achieve 99.9% confidence (0.1% significance), we reject the null hypothesis if the number of deaths is 1 or fewer. This test has significance 0.07% and power 75.05%. That is, if the alternative hypothesis is true, there is a 75% chance that this test will correctly reject the null hypothesis. If we can relax the significance of this test to 5% or lower, then we can reject the null with 4 or fewer deaths. Here the significance is 3.78% and power 99.69%. From a purely statistical viewpoint, 800M miles quite enough exposure for excellent significance and power, assuming that the exposure is representative of national exposure.

I'd also add that under the alternative hypothesis, there is only 7.31% chance that the number of death are greater than 2. So with very high probability, the observed death rate is at most 2 deaths per 800M or 0.24 per 100M. The important thing for Tesla is that they engineer a system that is truly 10 times safer than humans. If they do that, any reasonable test will have very good power.

A test based on 6B miles would have a Poisson test statistic with mean 72 under the null vs 7.2 under the hypothesis. Rejecting the null hypothesis with 46 or fewer fatalities has 0.07% significance and power 100% (beta < 10^-15). It is very unusual to require a test that has stronger limits on the Type II error rate than the Type I error. Indeed, if the alternative is true, then the probability of more than 12 deaths is a mere 3.27%. So requiring a test at this scale (6M miles) is massive overkill. Indeed, considering how many beta testers are required and how much the risk the general public would be exposed to at this scale, it make much more sense to pilot a smaller 250M mile test to rule out the possibility that the risk of this driving system is not substantially above average. Once you can reject the null hypothesis at about 5% significance, then you have reasonable confidence that you are not subjecting the public to unusual risk just to keep testing the safety of the system so to achieve a smaller alpha. So to be sure, there are social costs that argue against making any test of public safety like this larger than is necessary to achieve reasonable statistical control.

I should also point out that fatalities should not be the only outcome tested. For example, collisions are much more frequent than fatalities. If Tesla is able to reduce the frequency of collisions by 10 or so, then a 100M test may well be adequate to demonstrate this. Basically, if demonstrates that the rate of collisions is substantially reduced, then it is reasonable to argue that rate of fatalities is also reduced. To argue against such a position would require making specious objections like: "Given that there are 90% fewer collisions, how can we be sure that, when a collision does happen, it is not 10 times more likely to yield a fatality?" Such an objection can be countered by examination of collisions. Certain kinds of collisions have higher probabilities of incurring fatalities. I would expect a highway safety organization to have models that predict fatalities per collision attributes. It is straightforward for an analyst to use such a model to compute expected fatalities for each observed collision. These probabilities can be tested against actual fatalities to show that Tesla does not have an unusually high rate of fatalities per collision. And secondly, the total number of expected fatalities from observed collisions can be divided by exposure to arrive at an expected fatalities per 100 mile rate.

For simple, example let's consider only collisions where there is an injury or fatality. Corresponding to 1.2 fatalities per 100M vehicle miles nationally, there are also about 96 injured persons per 100M miles. Within a 100M mile test, Tesla will be able to estimate its injury rate with precision. Indeed, under the alternative hypothesis that its injury rate is 9.6 per 100M miles, Tesla has a probability of about 98% of observing 16 or fewer injured persons. Granted Tesla only expects 9.6 injuries, let's suppose they observe 16 (a rather unlikely number) and no fatalities. Given that there are about 80 injured persons per fatality. Conditional on 16 injuries, one would expect just 0.2 fatalities. Given that there were 0 fatalities, using the expected fatalities per injury, we obtain an estimate of 0.2 expected fatalities per 100M miles with evidence against the objection that Tesla has a higher than average ratio deaths per injuries. Specifically, it has 0 deaths per 16 fatalities. Even if in such a test 1 fatality had been observed, you'd have very thin evidence against the null hypothesis that the Tesla has the national average of 1 fatality per 80 injuries. So arguably a fair point estimate of the fatality rate is still between 0.2 and 1.0 deaths per 100M. The problem for Tesla is that you really don't want to be in a position where just one fatality compromises your case around substantially reduced injury rates. If Tesla were to offer 400M mile test, it would be in stronger position to tolerate 1 fatality. Here the significance is 4.77% while the power is 91.58%. So there is a 62% chance they avoid any fatalities, which would be the best case for using the ratio to injuries approach to estimating the fatality rate. But even if there were one fatality, they'd still have a 4.77% p-value on the narrow test around fatality counts and still have a very robust case on based on injury rates.

So my view is that Tesla can make a solid preliminary case based on a 100M mile test, but further testing in range of 400M to 800M miles may be needed if there are observed fatalities. The analysis above also illustrates why Tesla wants to study every crash with an injury very closely. From a business impact viewpoint alone, every injury crash is probably worth detailed simulation so that the AI system learns very well how to avoid them. The key issue is cutting injury rates 10-fold. If they do that, the rest will follow.

Now if a government agency wants to impose absurd testing requirements on Tesla, that is a matter of politics, not statistics.

 

[22522]

In my news feed

Why this super successful growth investor no longer owns Tesla shares - MarketWatch

Excerpt->

“Tesla has high capital intensity and constantly needs to get funding from the capital markets. That "isn't necessarily bad, but it does put you in a position of potentially, during times of uncertainty, of relying on the kindness of strangers to continue that business model” Peter Lynch said

Lynch acknowledged that founder Elon Musk has done "really amazing things." But he goes back to whether the company can be profitable.

"When you rely on capital markets, and you're dreaming big, there's a fine line between inspiring and making promises that maybe you can't keep," he said.

—-

I am amazed that this perception lives on among supposed experts. I keep thinking successful investors who make billion dollar decisions must have deep knowledge and have reams of data about the companies they invest or divest in.

I’m so glad I found this place. Woe betide the folks getting their investment advice from cable TV

Dennis Lynch is not Peter Lynch!

This is why this super-successful growth investor no longer owns Tesla shares

Dennis Lynch, head of Counterpoint Global, Morgan Stanley Investment Management, points to unit economics.

www.marketwatch.com

Now I have to call and apologize!

 

[redan]

OT, but Elon-related and by definition TSLA-related. Elon & Grimes have separated. We'll see if there is any impact from his personal life on his work life. Not always easy to separate the two.

https://twitter.com/x/status/1441429974326579208

 

[woodisgood]

It was posited before that the 750 call wall may have been formed mostly by retail (ie TMC). If that indeed is the case, it is not surprising there is no MM assist, and on top of that, if the MMs knew something like this, they’d make sure to steal those shares.

 

[Chunky Jr.]

Given the current TSLA rally and very encouraging delivery info from China and elsewhere, there must be a point fairly soon where the shorts start running for the hills before Q3 numbers come out. Hopefully it won't be long before @Curt Renz fires up the band.

 

[TheWalkingDad]

Broke thru short term resistance ~764. If it closes near these highs; bullish. Next wall ~780.

 

[StarFoxisDown!]

Broke thru short term resistance ~764. If it closes near these highs; bullish. Next wall ~780.

Regardless of what happens today, options-wise next week is being set up as a free run to 800 and even then, not a big call wall at 800. I'd have to guess MM's are going to step out of the way next week and the week after that to see how far it can rally before trying to step in again.

 

[TheTalkingMule]

Broke thru short term resistance ~764. If it closes near these highs; bullish. Next wall ~780.

Gonna be an interesting finish. If volume slows further, I could see MM's pushing it back to $759.99. If any kind of volume is maintained at $765-770, their algos might just decide it's optimal to cover a bit and let it drift up to $780. Fun times.

Remind me again why I watch this stock every day in the summer?

 

[StealthP3D]

The kid in his souped up Honda was never about beating the quickest car in the Model Y price class at the stop light grand prix. He couldn't do it in 1990 or now.

It was about fun to drive and having something rare that expresses your personality.

There have always been more rational transportation choices. And most people keep making irrational choices buying cars on wants not needs.

True, a Honda with louder farting noises and modified chips didn't aspire to be muscle cars. As long as they stood out from the crowd they had fulfilled their mission. Muscle cars, on the other hand, were always about being the quickest on the road. About being fast, powerful and able to smoke any challengers. 0-60 mph and 1/4 mile times defined how good your muscle car was. Great emphasis was placed on this by car magazines, manufacturers and owners alike.

Nobody needs a Model S Plaid. And yet Tesla can't satisfy orders. The Yoke may be cool but it is certainly not utilitarian.

Utilitarian is reducing accidents from airbags accelerating wrists into faces at speeds above 100 mph in any crash sufficient to deploy airbags. Utilitarian is allowing an unobstructed view of the display without having to adjust it to a less than ergonomic position. Sure, the yoke requires old dogs to learn new tricks but that does not mean it's not utilitarian.

Most people need a compact hatchback or minivan. And those are going the way of the Dodo bird in US/Canada.

The Model Y has the functionality to replace over 90% of the usage of both the compact hatchback and the minivan and to do it more efficiently. That's why it will shortly become the best selling vehicle in the world. The Model Y is addressing real market needs and the market is gobbling them up.

In an Iphone/Apple watch world people keep telling me a Rolex is pointless.

Yet Rolex sells their entire production of 750k units/year at full price. Many Swiss watch companies are doing quite well.

A Rolex is jewelry that you can wear on your wrist and put in a drawer when you don't want to wear it. Rolex has huge margins and sells to a sliver of the market. A car is not jewelry, it can't be put in a drawer when you don't want to deal with it and sells to the mass market. The two can't be compared in the manner you are trying to do.

Robotaxi services will sell to people that hate cars or are indifferent to cars. To people that can't drive or can't afford to drive. And to people that need taxi services like drunks or people going to the airport. Not to people that love cars and love to drive for their daily transportation.

Robotaxis will not take over the transportation services of suburban Americans anytime soon. But they will be a rapidly growing part of our transportation infrastructure that will extend far beyond those who hate cars or are indifferent to them, particularly at the lower end of the market and urban youngsters who actually want to get ahead in the world instead of blowing their retirement savings on urban parking fees. Robotaxis will replace millions of rental cars and, like ride-hailing is already doing, traditional taxis and second or even third family cars.

But back to the original point, yes, Tesla has absolutely made modified performance cars (and all gas cars for that matter) rather pointless. Tesla has taken the shine off them, the "bling", if you will. The transition is not complete yet but the "shiny new thing" is no longer a gas car that makes loud noises and stinky gases that can cause cancer. All the shine is gone and this will only be more obvious as the world continues to warm and storms intensify. It is already obvious to most people what is happening and what caused it. Only "followers" deny it now while leaders are the ones who define what is cool. And gas cars are not it. They have had their day. RIP.

 

[Maarten]

Thanks for your response. I'm not going to address the politic here, which can easily take us out of realm of statistical analysis. Rather, I'd point out that you seem to be confusing the null hypothesis with the alternative hypothesis, which is pushing you to suggest a test size which larger than it needs to be on purely statistical grounds. So let's be clear about a proper setup of the statistical test.

Null Hypothesis: Tesla death rate = 1.2 per 100M miles
Alternative Hypothesis: Tesla death rate = 0.12 per 100M miles

Since we wish to show that Tesla has 1/10 the average rate, this is our alternative hypothesis. The hypothesis testing framework actually become much simpler when you have a specific alternative hypothesis in mind.

Let's consider a test with 800M miles. The number of fatalities is our test statistic. Under the null hypothesis, it is Poisson with mean 9.6, and under the alternative hypothesis it has mean 0.96. To achieve 99.9% confidence (0.1% significance), we reject the null hypothesis if the number of deaths is 1 or fewer. This test has significance 0.07% and power 75.05%. That is, if the alternative hypothesis is true, there is a 75% chance that this test will correctly reject the null hypothesis. If we can relax the significance of this test to 5% or lower, then we can reject the null with 4 or fewer deaths. Here the significance is 3.78% and power 99.69%. From a purely statistical viewpoint, 800M miles quite enough exposure for excellent significance and power, assuming that the exposure is representative of national exposure.

I'd also add that under the alternative hypothesis, there is only 7.31% chance that the number of death are greater than 2. So with very high probability, the observed death rate is at most 2 deaths per 800M or 0.24 per 100M. The important thing for Tesla is that they engineer a system that is truly 10 times safer than humans. If they do that, any reasonable test will have very good power.

A test based on 6B miles would have a Poisson test statistic with mean 72 under the null vs 7.2 under the hypothesis. Rejecting the null hypothesis with 46 or fewer fatalities has 0.07% significance and power 100% (beta < 10^-15). It is very unusual to require a test that has stronger limits on the Type II error rate than the Type I error. Indeed, if the alternative is true, then the probability of more than 12 deaths is a mere 3.27%. So requiring a test at this scale (6M miles) is massive overkill. Indeed, considering how many beta testers are required and how much the risk the general public would be exposed to at this scale, it make much more sense to pilot a smaller 250M mile test to rule out the possibility that the risk of this driving system is not substantially above average. Once you can reject the null hypothesis at about 5% significance, then you have reasonable confidence that you are not subjecting the public to unusual risk just to keep testing the safety of the system so to achieve a smaller alpha. So to be sure, there are social costs that argue against making any test of public safety like this larger than is necessary to achieve reasonable statistical control.

I should also point out that fatalities should not be the only outcome tested. For example, collisions are much more frequent than fatalities. If Tesla is able to reduce the frequency of collisions by 10 or so, then a 100M test may well be adequate to demonstrate this. Basically, if demonstrates that the rate of collisions is substantially reduced, then it is reasonable to argue that rate of fatalities is also reduced. To argue against such a position would require making specious objections like: "Given that there are 90% fewer collisions, how can we be sure that, when a collision does happen, it is not 10 times more likely to yield a fatality?" Such an objection can be countered by examination of collisions. Certain kinds of collisions have higher probabilities of incurring fatalities. I would expect a highway safety organization to have models that predict fatalities per collision attributes. It is straightforward for an analyst to use such a model to compute expected fatalities for each observed collision. These probabilities can be tested against actual fatalities to show that Tesla does not have an unusually high rate of fatalities per collision. And secondly, the total number of expected fatalities from observed collisions can be divided by exposure to arrive at an expected fatalities per 100 mile rate.

For simple, example let's consider only collisions where there is an injury or fatality. Corresponding to 1.2 fatalities per 100M vehicle miles nationally, there are also about 96 injured persons per 100M miles. Within a 100M mile test, Tesla will be able to estimate its injury rate with precision. Indeed, under the alternative hypothesis that its injury rate is 9.6 per 100M miles, Tesla has a probability of about 98% of observing 16 or fewer injured persons. Granted Tesla only expects 9.6 injuries, let's suppose they observe 16 (a rather unlikely number) and no fatalities. Given that there are about 80 injured persons per fatality. Conditional on 16 injuries, one would expect just 0.2 fatalities. Given that there were 0 fatalities, using the expected fatalities per injury, we obtain an estimate of 0.2 expected fatalities per 100M miles with evidence against the objection that Tesla has a higher than average ratio deaths per injuries. Specifically, it has 0 deaths per 16 fatalities. Even if in such a test 1 fatality had been observed, you'd have very thin evidence against the null hypothesis that the Tesla has the national average of 1 fatality per 80 injuries. So arguably a fair point estimate of the fatality rate is still between 0.2 and 1.0 deaths per 100M. The problem for Tesla is that you really don't want to be in a position where just one fatality compromises your case around substantially reduced injury rates. If Tesla were to offer 400M mile test, it would be in stronger position to tolerate 1 fatality. Here the significance is 4.77% while the power is 91.58%. So there is a 62% chance they avoid any fatalities, which would be the best case for using the ratio to injuries approach to estimating the fatality rate. But even if there were one fatality, they'd still have a 4.77% p-value on the narrow test around fatality counts and still have a very robust case on based on injury rates.

So my view is that Tesla can make a solid preliminary case based on a 100M mile test, but further testing in range of 400M to 800M miles may be needed if there are observed fatalities. The analysis above also illustrates why Tesla wants to study every crash with an injury very closely. From a business impact viewpoint alone, every injury crash is probably worth detailed simulation so that the AI system learns very well how to avoid them. The key issue is cutting injury rates 10-fold. If they do that, the rest will follow.

Now if a government agency wants to impose absurd testing requirements on Tesla, that is a matter of politics, not statistics.

Solid piece of work.
Now I hope I will not have a nightmare tonight about my exam statistics In Delft University, which I had to do twice to pass.
What is the chance of that happening? Oooo, here it begins...

 

[Artful Dodger]

Tesla's Full Self-Driving Beta 'button' set to arrive tonight: Here's what to expect

Tesla is set to release its newest version of the Full Self-Driving Beta later tonight via a software update. Among the improvements is set to be the long-awaited arrival of the “Beta Button,” which will allow owners to potentially join the Beta program, giving them full access to the most...

www.teslarati.com

Long story short, if you were testing your instant torque at red lights over the past week, don’t be surprised if Tesla denies your request to join the Beta program. It is crucial for the company only to include drivers who will responsibly utilize FSD, especially as the inclusion of more owners to the program will add more data to the Tesla Neural Network, improving the performance of the FSD suite with every mile driven

 

[elasalle]

It was posited before that the 750 call wall may have been formed mostly by retail (ie TMC). If that indeed is the case, it is not surprising there is no MM assist, and on top of that, if the MMs knew something like this, they’d make sure to steal those shares.

So world is up side down, retail sells the Calls, and MM's buys them