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

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Flawless Starlink launch.

I'd like to note that SpaceX is now already the largest commercial satellite operator in the world, and they are probably only another ~2 Starlink launches away from having the largest operational commercial broadband Internet service in space.

They also have by far the lowest launch costs per new Internet service bandwidth in space: with every 60 satellites they are launching more than 1 Terabit of bandwidth into space, at a cost of about $20m-$30m/launch.

Nobody comes even close to those costs at the moment, and I believe Starlink is going to have a significant first-mover advantage.

SpaceX's success will also benefit Tesla - this is probably why we are seeing a small TSLA pop every time the second stage reaches parking orbit.
 
So deliberate rust?

You know, that's funny, but it's actually a pretty good analogy :) Like bluing a gun (e.g. with rusting it to black oxide / magnetite) so that it doesn't rust away (as red oxide / hematite or yellow oxide-hydroxide / limonite). Only difference being that you still need *some* flow (in this case, lithium ions) to get through. But yeah, you're "rusting" to a durable protective layer so that the underlying bulk mass doesn't "rust" any further.
 
Indeed, today's MMD seems decidedly peckish... wonder what 3 * Starships / day will do to the MMD? :p

SpaceX‏Verified account @SpaceX

"Falcon 9’s first stage has landed on the Of Course I Still Love You droneship – our 49th successful landing of an orbital class booster"

SpaceX on Twitter | link to 9 sec video of successful drone ship landing

Cheers!
 
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They also have by far the lowest launch costs per new Internet service bandwidth in space: with every 60 satellites they are launching more than 1 Terabit of bandwidth into space, at a cost of about $20m-$30m/launch.
I took your numbers, and extrapolating based on a 20:1 sharing scheme came up with 0.6 MB/sec/$
That does sound really, really cheap
 
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I've had the WSJ TSLA up on my screen (Yes, I know it is a garbage rag) because the SP is well behaved and updates by itself. I was amused to see this:

upload_2020-1-29_8-3-39.png
 
I realize I'm just being a human and seeing a random pattern. But anyway here are some numbers.

Closing prices on day following earnings releases.
Q4 2012: $35.15
Q3 2019: $299.68

Closing prices on day before next earnings release:
Q1 2013: $55.79
Q4 2019: $5xx?

In terms of percentage this pre-ER run-up was bigger than in 2013. This puts anyone who is short in a potentially worse position than in 2013. That being said there are more shares available to covering and shorts are a lower percentage of the float this time around. Either way lets see what happens to the closing price on Monday:
2013: $87.80
2020: $878???

I'll tell you what though I'm far from being all in on this one. I've kept some cash from the run-up so I'm ready to buy if it goes down. Are the shorts ready to short more if it goes up?
 
That's a graph of various strikes on a particular date, not the implied probability of given strikes over time.

I wanted to show first how the implied probabilities on a given date don't necessarily show a clear picture (i.e. overlapping long and short probabilities). Over time, it's even messier; I'm assuming this is because there are some very different beliefs held by people who trade weeklies, and as the expiry moves further out there may be more protective puts. Here's the implied probability curves generated by the options chain for the next 10 expiry dates:

TSLA_over_time.png


If I understand this chart right it is implying most of the short value people are paying for is for a stock price move of about -50% in less than 5 trading days. Aren’t these state price distributions usually much more centered around current price?

Yes, that's what I meant when I said the generalized inverse can cause some weirdness. It doesn't really show the magnitude of the probability, just the inflection points. In theory you can calculate the state prices of a security by multiplying the inverse of the payoff matrix by the price matrix, but in reality I've found that the payoff matrix is always rank deficient, so instead of making massive deficient matrices I'm finding smaller full-rank matrices and averaging the resultant state prices. This particular chart below took 4 hours of processing to find all of those full-rank matrices! Just like the one generated by the generalized inverse it shows a long peak at around 650 and a short peak below 300, but you can also see all of those really highly priced states right above the underlying being marked as outliers by the boxplot.

full_rank_TSLA.png
 
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This is the beginning of the end for ICE companies. Car sales fall as people start saving up for a really nice EV. Used (ICE) car values drop along with a reduction in new ICE car above and beyond the additional EV sales. Because people are holding off purchases until they have saved enough for a new EV. This was all predicted years ago:

Nissan takes the axe to the house Ghosn built
Remember, the ICE-AXE was what killed the Trotsky in the age of the hoarse.
Now almost all Ghosn, as Elon noted earlier.
:cool:
 
5 points up, flat or 5 points down. What SP does today really doesn't make a difference, in light of what will happen overnight and tomorrow. It's completely irrelevant.

The average move, up or down, on the day after ER during the last three years was 8,38% (thanks @EVNow for the chart). If we get that tomorrow it's a move of 47,8 points.

Fun fact: if we get the same 17,67% change we got three months ago - hopefully up - we're looking at a 100,7 point move.
 
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