Investor's Corner
Tesla stock (TSLA) one week after the Q1 2016 Report
Post Q1 Report Action
The technical response of the stock market to last week’s Tesla Q1 2016 report has been mostly negative. The stock lost quite a bit since last week, standing at around $208 when I write this, but overall 12-month Analyst Price Targets have actually increased with the average raising from $253 to $277, indicating that the Top Analysts did not see the report as negatively as this past week’s market action.
This is a small sample of the reactions from Top Analysts, noting that none of them changed their position to BUY, SELL or HOLD.
Adam Jonas of Morgan Stanley, reiterated a BUY with $333 price target, commenting that “we forecast ~70k units in 2016 (vs. the reiterated guidance of 80-90k shipments), which is composed of ~16k Model X and ~54k Model S units. In 2Q, we forecast ~17k deliveries–inline with the outlook.”
Charlie Anderson of Dougherty resumed coverage of TSLA with a BUY and price target of $500, noting that “the focus coming out of the Q1 report is on managements decision to pull-forward its production goal of 500K vehicles from 2020 to 2018. While this aggressive schedule certainly increases the risk of nearer-term stumbles, it also significantly pulls forward the earnings power. Tesla has set a goal to produce 1MM vehicles by 2020, roughly 2x what most observers previously believed. Our view is that demand is not the question; it is solving the manufacturing challenges deftly as they come.”
Brian Johnson of Barclays reiterated a SELL with $165 price target.
Ryan Brinkman of J.P. Morgan reiterated a SELL with $185 price target, as he “Doubts Tesla Motors Can Meet Accelerated Production Target.”
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Colin Rusch or Oppenheimer reiterated a BUY with $385 price target, indicating that “we believe the critical characteristic of TSLAs business model over the next 24 months will be operating leverage. We believe the company can achieve 15%+ incremental operating margins as it ramps the Model 3. We modeling TSLA reaching 500k vehicles in 2019 vs. the target of 2018, noting the company has a history of setting nearly unachievable goals. Effectively we are accelerating ramp by a year from our previous expectations, but calculate that if the company reaches its 500k vehicle target in 2018 and 1M in 2020, our EPS estimates will prove ~30% too low.”
See the table below from TipRanks (tipranks.com) for a complete summary of the current top analyst ratings.
![TSLA analyst coverage [Source: TipRanks]](http://www.teslarati.com/wp-content/uploads/2016/05/TipRanks-1.png "TSLA analyst coverage [Source: TipRanks]")
TSLA analyst coverage [Source: TipRanks]
Swing Trading TSLA using the MACD
This is the first post where I will start outlining techniques that traders may want to use when trading TSLA stock.
I am mostly a “swing trader”. Swing Trading is a short term trading method that can be used when trading stocks and options. Whereas Day Trading positions last less than one day, Swing Trading positions typically last two to six days, but may last as long as two weeks (for TSLA sometime six-seven weeks). Swing traders use technical analysis to look for stocks with short-term price momentum. These traders aren’t interested in the fundamental or intrinsic value of stocks, but rather in their price trends and patterns.
There are a number of technical indicators that swing traders use. Today I will cover the MACD. The Moving Average Convergence Divergence (MACD) is a trend-following momentum indicator that shows the relationship between two moving averages of prices. The MACD is calculated by subtracting the 26-day exponential moving average (EMA) from the 12-day EMA. The Exponential Moving Average (EMA) is a type of moving average that is similar to a simple moving average, except that more weight is given to the latest data.
The good thing is that you really do not have to calculate any of these indicators yourself, as pretty much all trading platforms that I know of provide you with such indicators as an option when displaying the stock chart of a given security.
The following stock chart from Wall Street I/O shows the TSLA market data as “candlestick” (showing open, close, high and low of the day) for the past year, plus it also shows the MACD for the same period.
Source: Wall Street I/O
One technique that swing traders use is to enter a “long” trade when the MACD “crosses to the bulls”, and exit the trade when the MACD “crosses to the bears”. I have indicated these points in the chart for the huge run up between the February low and April high.
Micah Lamar is the CEO of Wall Street I/O (wallst.io), where together with his team of experts he helps people learn stock and option trading. Disclosure: I have been a subscriber to wallst.io for a few years.
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This past weekend, Micah run a “MACD Validation” experiment on TSLA 1-year behavior up to last Friday close. The results are as follows.
Micah found that “if one had bought TSLA stock exactly a year ago, and held it for the full year, one would have incurred a $30 loss per share.
If one had bought and held TSLA stock while the MACD was bullish, one would be up $22 for the year.
If one had sold (short) TSLA stock while the MACD was bearish, one would be up $51 for the year.”
Someone trading both sides (long and short the stock) would be up a whopping $73, or a $30% gain.
Of course, trading the same entry and exit points based on the MACD with put or call options instead of stock would have resulted in returns 10 to 100 times or better than if just trading TSLA stock.
Micah indicates that “TSLA is a great stock for swing traders: the reason is that it has so much “beta.” A high beta indicates that a security is much more “volatile” than the rest of the market. Most high-tech stocks like TSLA have a beta of greater than 1, offering the possibility of a higher rate of return, but also posing more risk.
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As far as where TSLA is today, it is still in “bearish” territory (as far as the MACD and other indicators are concerned), which for me it means that it is untouchable on long trades as “too risky”, and since I do not like to play on the downside for stocks of companies that are in my “buy what you know” list, I will not trade it again until the MACD crosses back to the bulls.
Elon Musk
SpaceX’s next trillion dollar bet has nothing to do with rockets, Musk tells staff
Elon Musk told SpaceX staff AI revenue will soon dwarf rockets and Starlink combined entirely.
Elon Musk told SpaceX employees this week that artificial intelligence, not rockets, will soon carry the company’s revenue. In a roughly 29 minute internal address posted on SpaceX’s X account on Tuesday, Musk said AI revenue will pass every other line of business at SpaceX “probably in September” and pull further ahead by the fourth quarter.
The numbers he gave are specific. SpaceX currently runs 1.4 gigawatts of AI compute capacity. Musk wants that at 10 gigawatts by the end of 2027, a jump he tied directly to revenue: “if we bring 10GW of AI online by the end of next year, it will be $300 billion to $500 billion a year in revenue.” He called those “big numbers,” which undersells a projection larger than what most countries produce in a year.
We made rockets reusable and are rebuilding the internet in space. The next challenge: making life multiplanetary and understanding the true nature of the universe
Watch @ElonMusk deliver a company update to @SpaceX employees pic.twitter.com/5c8rxoCQfu
— SpaceX (@SpaceX) August 11, 2026
Musk went further on where AI fits into SpaceX’s future. “Probably in four or five years, AI will be 99% of the value of SpaceX,” he told staff, adding that digital intelligence would eventually run “a trillion times” ahead of biological intelligence as computing scales. He tied that growth to the company’s founding mission, telling employees “we must win on AI, because the future is overwhelmingly AI and robots,” with the payoff meant to help fund Starship and a Mars program that increasingly runs through Terafab, the joint Tesla, SpaceX and xAI chip plant.
Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry
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None of this is entirely new territory. SpaceX told investors much the same story during its first earnings call as a public company on August 4, where Musk moved the company’s $1 trillion revenue target up a year to 2030 and said Starlink could someday carry a majority of the world’s internet. What the all hands video adds is a hard deadline and a specific power figure Musk had not given publicly before, along with a franker pitch to his own workforce that AI, not launch cadence, is now the thing SpaceX is betting its future on.
The AI revenue itself is not coming from SpaceX training its own models. It is largely Starlink acting as the network layer for xAI’s workloads, plus SpaceX renting out compute capacity directly, the same approach behind the roughly $16 billion the company spent on AI infrastructure in a single quarter.
Musk closed the video with a pitch aimed at recruiting and retention rather than investors, telling employees that anyone who helps SpaceX win the AI race will eventually get the chance to go to the moon or Mars themselves. Whether SpaceX can turn 1.4 gigawatts into 10 in seventeen months is the more immediate question, and one that will show up in quarterly numbers well before anyone leaves Earth.
In a new note to investors on Tuesday, Morgan Stanley analyst Andrew Percoco said that Tesla has one big financial question to answer for investors regarding its Robotaxi rollout, Full Self-Driving software, and Optimus.
Percoco said in the note that, for the most part, investors are still very positive about the direction the company is headed. However, there are some things the firm would like to see, and they have to do with financials.
Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue
Tesla bulls are more than convinced that the company’s Full Self-Driving software is proof it can develop physical AI. Financially, however, there are still some questions, especially on elevated spending, which CEO Elon Musk said would occur as the company works to roll out Robotaxi faster and continue developing its Optimus robot.
The latter two are where Tesla will have to prove progress to investors, as Percoco writes that both projects “will require clearer evidence that Robotaxi is scaling and more tangible Optimus proof points to support the ROI on elevated capex.”
Percoco said the second quarter earnings call did not change his long-term thesis of where Tesla is positioned in the AI race, which is out in front. However, there are concerns that weaker gross margins and higher R&D spend will stress financials, and that has “sharpened our (and investors’) focus on measurable progress across Robotaxi and Optimus.”
Additionally, Robotaxi still needs to be proven with more operation in existing cities while maintaining safety but improving how many rides it gives in any given time, he said. For Optimus, Percoco wrote that he is “still looking for evidence beyond commentary around SOP.”
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Morgan Stanley put Percoco in charge of covering Tesla after long-time analyst Adam Jonas transitioned to the automotive side.
Currently, Morgan Stanley has a $415 price target on Tesla and a ‘Hold’ rating on the stock. It is trading at around $330 at the time of publication, which was 2:30 P.M. on the East Coast.
SpaceX’s massive investment in AI will make it a big winner, Argus Research said after the company’s successful earnings call last week.
The firm also upgraded shares to a Buy from Hold and set a $160 price target.
SpaceX (NASDAQ: SPCX) is currently recovering from its heavy AI infrastructure investments, as it spent nearly $16 billion in Q2 alone. The company did this primarily by monetizing high-demand GPU compute capacity at a much faster pace than traditional data center economics would suggest.
Company CFO Bret Johnsen said that SpaceX would be able to pay back anything on new deployments within a year.
There are plenty of ways the company can do this:
Leasing excess compute capacity through contracts
SpaceX has already built Colossus and Colossus II, largely for its own model training. However, much of that capacity is already rented out to third parties. It already has major deals with Anthropic, Google, and Reflection AI. These partnerships are adding billions per month to SpaceX’s spreadsheet.
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High utilization driven by industry-wide scarcity
The demand for advanced AI training and inference capacity continues to exceed what is available for use. SpaceX can fill new racks quickly after they come online, so the capital deployed converts into revenue with minimal idle time.
Additionally, management and outside observers have described the new compute capital as behaving more like a cost-of-goods-sold than traditional multi-year capex, especially because of this rapid monetization pattern.
Capacity has already scaled from ~0.4 GW a year to 1.4 GW annually by the end of Q2. There are targets of more than 2 GW by year-end.
High incremental margins on the rental business once capacity is online
GPU cloud providers often operate at strong gross margins. SpaceX can monetize capacity that was already partially built or can be added efficiently. This means that incremental EBITDA margins on the rental revenue are usually high. This accelerates cash recovery relative to the gross capital outlay.
Parallel monetization of its own AI software and applications
Beyond pure infrastructure rental, SpaceX also generates revenue from Grok through subscriptions and usage, from X through ads, data, and other related services, enterprise APIs, and the planned integration of the Cursor coding tools acquisition.
These application layers ride on the same compute infrastructure and provide additional high-margin streams that could offset build-out costs. AI-segment revenue overall rose sharply to about $2.6 billion in Q2, according to Motley Fool. This was driven primarily by the infrastructure contracts, but the software side is also partially responsible.
Efficient, large-scale deployment and vertical integration advantages
SpaceX has emphasized the rapid construction of power and cooling infrastructure and favorable cost-per-megawatt economics relative to industry benchmarks in some disclosures.
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Combined with its ability to scale capacity aggressively and the fact that many contracts start generating revenue within months of capacity coming online, the effective payback compresses dramatically compared with more conventional multi-year data-center projects.
SpaceX’s dominant near-term recovery path will turn the AI clusters into a hyperscale-style compute rental business for other leading AI companies while still using a portion for internal models.
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