While the Global Trading Dispatch focuses on investment over a one week to six-month time frame, Mad Options Trader, provided by Matt Buckley, will focus primarily on the weekly US equity options expirations, with the goal of making profits at all times. Read more
When John identifies a strategic exit point, he will send you an alert with specific trade information as to what security to sell, when to sell it, and at what price. Most often, it will be to TAKE PROFITS, but, on rare occasions, it will be to exercise a STOP LOSS at a predetermined price to adhere to strict risk management discipline. Read more
When John identifies a strategic exit point, he will send you an alert with specific trade information as to what security to sell, when to sell it, and at what price. Most often, it will be to TAKE PROFITS, but, on rare occasions, it will be to exercise a STOP LOSS at a predetermined price to adhere to strict risk management discipline. Read more
When John identifies a strategic exit point, he will send you an alert with specific trade information as to what security to sell, when to sell it, and at what price. Most often, it will be to TAKE PROFITS, but, on rare occasions, it will be to exercise a STOP LOSS at a predetermined price to adhere to strict risk management discipline. Read more
When John identifies a strategic exit point, he will send you an alert with specific trade information as to what security to sell, when to sell it, and at what price. Most often, it will be to TAKE PROFITS, but, on rare occasions, it will be to exercise a STOP LOSS at a predetermined price to adhere to strict risk management discipline. Read more
Global Market Comments
February 13, 2018
Fiat Lux
Featured Trade:
(FEBRUARY 14 GLOBAL STRATEGY WEBINAR),
(THE UNICORNS ARE OUT OF THE CORRAL),
(CDLX), (SNAP),
(HOW TO EXECUTE A VERTICAL BULL CALL SPREAD)
My next global strategy webinar will be held on Wednesday, February 14 at 12:00 PM EST, which I will be broadcasting live from Silicon Valley in California.
We'll be giving you my updated outlook on stocks, bonds, commodities, currencies, precious metal, and real estate.
The goal is to find the cheapest assets in the world to buy, the most expensive to sell short, and the appropriate securities with which to take positions.
I will also be opining on recent political events around the world and the investment implications therein.
I usually include some charts to highlight the most interesting new developments in the capital markets. There will be a live chat window with which you can pose your own questions.
The webinar will last 45 minutes to an hour. International readers who are unable to participate in the webinar live will find it posted on my website within a few hours. I look forward to hearing from you.
We recently have taken in a large number of new subscribers. If you miss it the webinar will be posted on the website within the hour.
To log into the webinar, please click on the link we emailed you yesterday entitled "Next Bi-Weekly Webinar - February 14, 2018" or click here
It was perhaps the worst timed IPO (initial public offering) of the decade.
Cardlytics (CDLX) went public at the Friday open, one of the worst days in the history of Wall Street.
The shares were priced at $13, and closed later in the day at a strong $13.33. The Dow Average then collapsed some 1,100 points in hours.
A lesser underwriter would have delayed the issue, given the dark stormclouds building on the horizon. Not so for JP Morgan Chase, which had heavily presold the deal, and went ahead, come hell or high water.
Cardlytics is a data platform that specializes in the collecting purchase and transaction data from financial institutions and converting the data into highly targeted marketing offers.
Cardlytics' flagship offering is called Cardlytics Direct - advertisements to customers that are placed directly in their banks' webpages and mobile apps in the form of "cash back" offers that most are familiar with.
Firms that purchase intelligence data from Cardlytics can target ads to customers who are most likely to respond.
A major part of the appeal of Cardlytics was its use of artificial intelligence in matching the buyers and sellers of ads.
AI is the hottest investment theme in Silicon Valley these days. However, there are very few public companies that allow investors a pure, or even peripheral AI play.
The Cardlytics IPO raises the urgent question of whether there are more unicorns to come. Unlike past market and economic cycles, unicorns, or successful companies still in the private startup stage, are delaying public filings longer than at any other times in the past.
Managers say they want to mature their companies and delay the high legal and regulatory costs that come with going public. The REAL reason is that founders want to milk their firms for all they're worth and sell them only after they go ex-growth.
The end result has been to create a shortage of high tech firms with the most cutting-edge technologies. This has caused investors to price the few public firms that are out there at even higher valuations.
Music streaming service Spotify is thought to be next in the IPO parade, followed by cloud firm Dropbox, followed by AirBnB and the $70 billion mammoth, Uber.
In the nine months ending in September, Cardlytics lost $16 million on sales of $91 million.
Cardlytics has raised more than $200 million in venture funding from ITC Holding Co. LLC, Kinetic Ventures, Canaan Partners, Polaris Venture Partners and TTV Capital, which are all cashing big paychecks today.
Given the recent performance of small tech IPO's, I'll be holding back on sending out a "BUY" recommendation on (CDLX) at this time.
Traders are still too freshly burned from their 2017 experience with SNAP (SNAP) (for more on this unfortunate company, please read the Mad Hedge Technology Letter piece "Don't Fall Into the SNAP Trap" by clicking here for tech letter subscribers only.
SNAP launched in March at $17, and then soared 44% on the first day to $29. It then collapsed to a low of $11.40, off a heartbreaking 60.68%. It was a classic case of investment banker incompetence, greed, and mispricing.
Once burned, twice forewarned, as they say.
Mad Hedge Technology Letter
February 13, 2018
Fiat Lux
Featured Trade:
(CHASING NVIDIA),
(NVDA)
Long term readers of this letter know too well that after tripling from my initial forecast of $68 a share, that the shares of NVIDIA would double again.
After listening to their Q4 earnings call, I now have to confess that I was wrong my in assessment.
It now looks like NVIDIA shares will triple off of the recent $180 low.
From what I heard, the call was nothing less than amazing.
When considering companies limited by imagination, the last one I would anoint is Nvidia (NVDA).
I have been pounding the table for years, pleading with readers to drop everything and get into this battering ram of a stock.
If you didn't, well, you aren't buying at the bottom, but the future potential for Nvidia cannot be understated. Nvidia stands atop a parapet, scoffing at its enemies who simply cannot compare.
Its superior strategic position in GPU (graphics processing units) chips has forced the tech community to adopt its platform as the building blocks of A.I., machine learning, data center, and autonomous car technology.
In fact, Nvidia has only scratched the surface of its potential. The sustained growth story is not only intact but accelerating at a rapid clip.
The first chapter of Nvdia's rise to glory was on the back of e-gaming and the subsequent demand for their GPUs. The most talented gamers require the superior GPU's for faster processing speeds and crisper visuals that aid playing levels.
Casual gamers seem to upgrade their GPU's as well, since many of these participants cut their teeth jostling with their online counterparts 10 hours/day.
The main beneficiary of the GPU gaming upgrade boom is the model NVIDIA Pascal. This chip has the world's most advanced gaming GPU architecture, delivering truly game-changing performance, innovative technologies, and immersive, next-gen virtual reality.
Offering scintillating gameplay, it's a rung up in the gaming world. Additionally, the companies that manufacture gaming consoles are part and parcel in this GPU game of thrones. Sales of the Nintendo Switch provided a boost to Nvidia's Tegra processor revenue, tallying up to $450 million, up 75% YOY.
On a stand-alone basis, Nvidia is knocking the ball out of the park in terms of a pure gaming stock, but it is so much more than that. Nvidia IS the future. This was all apparent in last week's earnings call, which I shall outline below.
Data Centers
Revenue of $606 million was up a staggering 105% YOY, and up 20% QOQ. This over performance reflected strong adoption of Tesla V100 GPUs based on the Volta architecture, which began shipping in Q2 and continued to solidify in Q3 and Q4 2017.
V100's are present in every mainstream computer made by every major company, and have been chosen by every major cloud provider to deliver A.I. and high-performance computing.
Cloud customers adopting the V100 include Alibaba, Amazon Web Services, Baidu, Google, IBM, Microsoft Azure, Oracle and Samsung.
Nvidia perpetuates leadership in the AI training markets where their GPU's remain the platform of choice for training and machine learning networks. Any well-known company looking to A.I. functionality in the data center space relies on Nvidia to carry the load.
Nvidia posted a growing traction in the A.I. inference market where NVIDIA's platform can improve performance and efficiency by many degrees of magnitude over CPU's.
"Inference?" is the technology that puts sophisticated neural networks, trained on powerful GPUs, into use, solving problems for everyday users. Nvidia considers A.I. inference as a cogent new opportunity for the data center GPUs.
Nvidia is also gaining influence for A.I. in a growing number of vertical industries such as transportation, energy, manufacturing, smart cities, and healthcare.
The most poignant data center technology innovation was Tensor Core, a unique feature of the new Volta GPU Architecture. This technology alone can successfully complete rapid deep learning, and it officially increases the throughput of deep learning by 800%.
Autonomous Driving
Nvidia flaunted their leading position in autonomous vehicles with several salient landmarks and new partnerships. A.I. self-driving cars are trending towards moving from deployment to production.
Jensen Huang, the genius who is the CEO of Nvidia, announced that DRIVE Xavier, the world's first autonomous machine processor, will be available for the first time this quarter with more than 9 billion transistors.
DRIVE Xavier is the most complicated system Nvidia has ever delivered to customers. Recently trotted out, NVIDIA Drive is the world's first functional A.I. self-driving platform, enabling automakers to create autonomous vehicles they can operate safely.
This is a necessary component to prove its technology is ready for mass market. Several dynamic collaborations have begun with Uber, which has integrated A.I. video technology for its fleet of self-driving cars and freight trucks.
Production vehicles utilizing NVIDIA drive technology include vehicles from Chariot. Chariot is a privately-owned commuter shuttle service that is currently in the process of being acquired by Ford.
The company's mobile-phone application allows passengers to hop on a shuttle between home and work during commuting hours. Chariot currently operates in several neighborhoods in Silicon Valley and plans to swiftly expand to other locations around the United States. The Chariot fleet expects to be fully functional and possess automation capability by 2020.
Over 320 firms are now using the NVIDIA Drive platform, up 50% YOY, including almost every relevant car maker, truck maker, robo-taxi company, mapping company, car parts manufacturer and start-up in the autonomous vehicle ecosphere.
Nvidia has strategically placed itself on the front line hoping to expedite the roll out of this technology in the form of a massive fleet, servicing the individual. The obsolescence of human drivers is closer than you think.
Autonomous driving is the most significant paradigm shift in the history of the automotive industry. In total, transportation is a $10 trillion industry and I am not exaggerating when I say this will completely reshape our daily lives.
Vehicles will be fully or partly autonomous, depending on the entity. The potential of this market is massive.
The imminent monetization process will commence in 2019 and 2020, but if I had to bet money, I would say widespread profiteering will not occur until 2022.
The first goal is to train a network of autonomous driving capabilities, and this will be aided by creating a platform named NVIDIA GTX that grants everybody the chance to train a neural network promptly.
The inherent development of the A.I. requires top end GPU's, and Nvidia harvests a good portion of the spoils.
The second phase would be development platforms for the cars themselves and all these tasks will be executed by Nvidia Xavier SoC.
A system-on-a-chip (SoC) is a microchip with all the necessary electronic circuits and parts for a given system, such as a smartphone or wearable computer, on a single integrated circuit (IC).
Xavier is the most complex SoC that humankind has ever invented. All previous NVIDIA DRIVE software development carries over and runs with this consolidated architecture.
The prices for Nvidia GPU's split because the mix of solutions are unique. Autonomous vehicles that still have physical drivers will fetch a price between $500 to $1,000 per GPU.
Autonomous vehicles without drivers will command a price of $2,000-$3,000 per GPU. In general, the industry will see large-scale deployment starting FY 2018.
Practically every car produced in 2022 and beyond will have autonomous driving capabilities, requiring copious amounts of Nvidia GPU chips.
Huang repeatedly complains that Nvidia cannot keep up with the insane demand of these new technologies. There will be a persistent GPU shortage for the foreseeable future.
What does the future of AI behold aside from the imminent sensations of autonomous vehicles?
At a basic level, A.I. can be used for many things, such as improving images. For instance, you could reconstruct a photograph using A.I.. You could correct blemishes or parts of the image that haven't been rendered yet. A.I. would be used to fill in the holes, predict the future, and render results.
Let's take it one step further.
Extrapolating this concept to broader designs of everything, say cars, A.I. will be used to generate their designs in the future.
You could draw the first few preliminary scribbles of a car design and based on the inventory, safety, physics, consumer demands and other crucial inputs, the A.I. technology would complete the remaining 90% of the design.
This new type of design technology is called generative design and will revolutionize the way people do business.
My prognosis in the future of developing software is a world where computers can write their own software and this software will be so dense and complex that no human can replicate the task.
Essentially, we will be coaching up data to teach software how to write it's own software through machine learning. And imagine the new business applications introduced by this potential software!
Did I mention that Nvidia is also returning $1.25 billion to shareholders in FY 2019 and receiving another tailwind of high single digit growth in bitcoin mining?
Of course, all of that pales in comparison to the potential big picture profits Nvidia could realize. Jensen Huang has told investors that he expects A.I. to be a $10 billion/year business and autonomous technology to be a $40 billion/year business.
Remember that their most stable segment now is e-gaming GPUs which are only a paltry $3 billion/year in total revenue.
Nvidia could easily triple its business without fulfilling its revenue claims by just partially reaping the fruits of their labor from the A.I., data center, and autonomous vehicle industries. To visit their website please click here.
