Nvidia’s Success Could Be Its Undoing

We reviewed the charts and indicators of NVIDIA (NVDA)  last week,  and recommended this strategy — “In this Point and Figure chart of NVDA we can see an extended market, but also a $198 price target…. Slower volume, weaker momentum….all point to caution ahead. Long NVDA? I would suggest raising sell-stop protection to a close below $170.” NVDA traded to a new all-time high this morning of $195.80.

Let’s see if our strategy suggestion needs any updating.

In this updated daily bar chart of NVDA, below, we can see that prices are above the rising 50-day moving average line. Prices have stayed well above the rising 200-day line for the past twelve months. The daily On-Balance-Volume (OBV) line is higher than it was a year ago but it has suffered through two sideways periods. Recently the OBV line made a new high to confirm the price strength. The 12-day momentum study in the bottom panel shows a small bearish divergence with equal momentum highs in September and October compared to higher highs in price over the same time period. This is a small bearish divergence and while it might work in foreshadowing a downward correction it doesn’t look that dangerous. A bearish divergence in May and July only resulted in sideways price action.

In this weekly bar chart of NVDA, below, we can see that prices are above their rising 40-week moving average line. This longer-term indicator has done an excellent job since early 2016. The weekly OBV line has not made much upward progress the past three months. The weekly Moving Average Convergence Divergence (MACD) oscillator is turning upwards to a fresh outright go long signal.

In this Point and Figure chart of NVDA, below, we can see that NVSDA is extended on the upside with a $198.64 price target.

Bottom line — sell side analysts have been raising their price targets on NVDA to the point that I think this is “crowd behavior” and could mean that the stock has become “over owned.” Aggressive traders with a high average cost could consider a sell stop below $180 now and investors should continue with stops below $170.

NVIDIA’s New Geforce GTX 1070 Ti Gets First Gaming Benchmarks

The first ever benchmarks of the GTX 1070 Ti have leaked out via the AotS database. While this  isn’t a particularly good metric or indicator of overall game performance by any means, it does show that that the company is gearing up for a launch soon and the final testing is underway. I have taken a screenshot in case the benches get pulled down, like they usually do.

Geforce GTX 1070 Ti gets Ashes of the Singularity: Escalation benchmarks leaked

The GTX 1070 Ti gets an overall score of 6200, which is an acceptable score from the GTX 1070 successor. We have seen some highly overclocked 1070s reach this range but we have also seen lower clocked 1080s reach this range as well. All in all it looks like NVIDIA will finally be plugging the hole that the Vega 56 is sure to carve in its lineup. The most impressive thing however, is that the average frame rate in the normal batch is at an all time high. This is actually faster than all of the GTX 1070s and many of the GTX 1080s and goes on to show the potential this card could have once performance tuning is completed. Here are some GTX 1080 benchmarks for comparison within the same Extreme 1440p preset.

The GTX 1070 Ti uses NVIDIA’s GP104 GPU, specifically the GP104-300 variant. While the maxed out GP104 has a total of 20 SMs, the GP104-300 variant has only 19. Basically these are chips that were originally meant to be a full fledged GTX 1080 Ti but had one dysfunctional SM due to yield and were therefore re-purposed into a 1070 Ti. The chip features 7.2 Billion transistors and a 314mm² die for a total of 2432 CUDA Cores. The 1070 Ti houses a total of 152 TMUs, 64 ROPs and 8 GB of GDDR5 memory (another difference when compared to the GTX 1080 which uses G5X). The memory is clocked at 8 Gbps for a total bandwidth of 256 GB/s.

Now there have been rumors that the card will not be overclock-able. Word on the grape vine is that the clocks of this card are maintained at 1607 MHz base and 1683 MHz boost frequencies. This would result in a maximum compute performance of 8.1 TFLOPs at the given specifications. Most NVIDIA GPUs usually boost far higher than the rated turbo boost spec but if this is true it is possible that what you read is what you will get with the 1070 Ti – with no dynamic boost occurring over the rated spec.

Such a restriction would almost certainly have to be enforced by software – one I presume to make sure that sales of the GTX 1080 aren’t cannibalized and it would be interesting to see whether anyone is able to bypass this and unlock the full potential of the card (which should be able to stretch all the way up to 9 TFLOPs). Not only that but NVIDIA will not be launching any reference editions this time and all custom AIB cards will be locked to the aforementioned frequencies. The GPU will be launching on the 26th of October, 2017, in a few weeks time and will reportedly retail for $429.

Nvidia Geforce GTX 1070 Ti Specifications

Wccftech NVIDIA GeForce GTX 1070 NVIDIA GeForce GTX 1070 Ti NVIDIA GeForce GTX 1080
Graphics Core GP104 GP104 GP104
Process Node 16nm FinFET 16nm FinFET 16nm FinFET
Die Size 314mm2 314mm2 314mm2
Transistors 7.2 Billion 7.2 Billion 7.2 Billion
CUDA Cores 1920 CUDA Cores 2432 CUDA Cores 2560 CUDA Cores
Base Clock 1506 MHz 1607 MHz (TBC) 1607 MHz
Boost Clock 1683 MHz 1683 MHz (TBC) 1733 MHz
FP32 Compute 6.5 TFLOPs 8.1 TFLOPs 9.0 TFLOPs
VRAM 8 GB GDDR5 8 GB GDDR5 8 GB GDDR5X
Memory Speed 8 Gbps 8 Gbps 11 Gbps
Memory Bandwidth 256 GB/s 256 GB/s 352 GB/s
Bus Interface 256-bit bus 256-bit bus 256-bit bus
Power Connector Single 8-Pin Power Single 8-Pin Power Single 8-Pin Power
TDP 150W 180W 180W
Display Outputs 3x Display Port 1.4
1x HDMI 2.0b
1x DVI
3x Display Port 1.4
1x HDMI 2.0b
1x DVI
3x Display Port 1.4
1x HDMI 2.0b
1x DVI
Launch Date 10th June 2016 26th October 2017 27th May 2016
Launch Price $349 US ~$429 US $499 US



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Hands-On with NVIDIA’s Holodeck, Early Access Announced

In addition the Drive PX Pegasus, NVIDIA announced Holodeck Early Access at GTC Europe 2017 in Germany. First announced at the primary GTC 2017 as Project Holodeck with early access slated for September, NVIDIA elaborated on the name change that Holodeck had moved from an exploratory project to a real product. To recap, Holodeck is essentially a photorealistic VR environment for collaborative design and virtual prototyping, where high-resolution 3D models can be brought into a real-time VR space. The idea today is that NVIDIA is soliciting community feedback and input via early access as they continue to develop Holodeck as a product.

As earlier disclosed at GTC 2017, Holodeck is powered by the Unreal Engine. Holodeck is also featured in NVIDIA’s Isaac Lab, a virtual AI training environment. For the online collaboration feature, multiple users currently connect to the same session. Due to using Unreal, sessions will be similar to hosting a video game, whereby one person acts as the host and all other players will require the assets in advance to connect. This may require some fine tuning, especially when some high-resolution models will run into the gigabytes of data and need to be shared with all parties intending to connect in advance.

While Holodeck does feature PhysX, the technology was described as powering primary interactive scene physics, as opposed to solely secondary physics processing. This differs from the previous use of the PhysX terminology, and to that end, NVIDIA confirmed the terminology change.

In terms of Holodeck Early Access workflow, a CAD model is brought into Maya or 3ds Max where the materials/geometry/textures are exported to a specific file format, and then imported to Holodeck using a plugin. Other CAD environments will be supported over time due to the use of Holodeck APIs. On that note, NVIDIA commented that Holodeck is intended for users with pre-existing CAD expertise. 

Holodeck will be distributed through Steam and will be managed via Steam Keys. As it is a graphically intensive VR experience, Holodeck Early Access will officially support the GeForce GTX 1080 Ti, Titan Xp, or Quadro P6000, in addition to an HMD. Early Access will be limited to a fixed number of passes being issued every week but is intended to be open to all later.

Hands-On Experience: Holodeck
Ian Cutress

So perhaps the first thing I should say when I tested out the Holodeck Demo is that I managed to break it to the point of needing to restart the software. The whole ecosystem is still in an early beta stage, so there are some rough edges to get around, but for the most part it worked.

NVIDIA gave me an HTC Vive headset in a dedicated Holodeck room, and placed me in what could be described as a Google Tilt Brush type of environment. The main difference was that in front of me was a supercar, and we went through the various that Holodeck currently provides in single-user mode.

This means walking around the very detailed car, and exploding the car into each one of its 30000 individual pieces.

For the most part these models were detailed, but we were approaching the fine limits of what we can currently do with VR: while 50 million polygons were on screen for all the parts, when I tried to focus on one, such as a screw, the model of the screw only consisted of 100s (or even 10s) of polygons and was not very detailed. My perception would be that I could determine the direction of the screw thread, but not in this case. I could barely make out that it required a Philips screwdriver, due to the lack of detail. Unbeknownst to me at the time, Holodeck can pick up and place parts (with or without physics), so I didn’t try and pick up the parts before de-exploding the vehicle.

The next feature on display was the clipping tool. This is a bubble that can be used to adjust the clipping of the view and rearrange parts of the z-order buffer to look inside the vehicle.

The bubble can be resized and replaced, with the idea that several people can use their own bubbles in the environment, or pass them around. In this view it was very detailed again, however where two surfaces were near to each other there was some obvious texture clipping going on, causing a flickering between the two. This could be a function related to the engine, as from previous experience game engines sometimes do not handle polygon clipping or texture clipping very well.

At one point we also saw a small minor issue – come parts in some designs are flexible (e.g. hoses), and this caused an issue on the demo as it was put through as a fixed model, meaning that some of the flexible parts did not line up with the rest of the design. Again, it’s still a beta.

Aside from the visual tools, there were also some adjustment tools. Using one of the options, certain objects and surfaces could be selected and adjusted for color, transparency, and material. I somehow changed the wheel rims to be made out of concrete and pink, which also rendered them immune to the bubble clipping tool. Making the bonnet transparent was interesting as well. Along with the adjustment tool was also a laser measurement tool that provided a means to measure point to point distances, much like IR distance laser pointers work in real life.

The simulation also allowed for a pencil tool, to write in the air (like Tilt Brush), as well as a note taking tool that provided a whiteboard to write on in a 2D fashion. It was at this point that I learned that objects could be picked up as well, meaning that I could pick up my 3D writing and place it on/through the car, or pick up the whiteboard and place it elsewhere. I was unable to write on the reverse of the blackboard, interestingly enough.

So then I broke the simulation. I managed to pick up the car. Somehow picking up a supercar easily was somewhat amusing, especially as I was able to use my other hand to use the previous tools and look through the car. I asked about picking up in a multi-user environment, and was told that it is a first come, first serve arrangement with picking up items. I tried to let go of the car, but somehow the simulation kept it linked to my hand. The shadow of the car was still fixed from when it was on the floor, at which point the person giving me the demo stated that one of the issues still to be solved in Holodeck is one of global illumination and point illumination.

Near the end of the demo, I played around with a few other tools, and ended up in the model loading area to be able to pull in new models into the scene. My thoughts went immediately to video game development, allowing developers to exist inside a room of their game and collaborate with the writers into where objects should be placed for the best atmosphere. NVIDIA’s main focus for Holodeck seems to be with the commercial industry first, such as automotive and architecture, although I can see plenty of game development use too.

As an aside, the ability to bring in local models is going to be a tough hill to climb. If developers from different geographical regions have local models they want to import but not everyone has the latest up-to-date versions of the models, it may require gigabytes of data transfer between all the parties before such a model can be imported. This could limit the ability to interact if all the assets are not directly shared the night before, and allowing for synchronization to happen overnight.

Unfortunately, the demo was not of a multi-user experience, but from the snippet of experience I had, it is clear that this is the next stage of VR interactivity and multi-user is going to be a part of it. I was unsure whether to be amazed from the demo, or to actually say ‘well this is what they promised, why was I expecting anything different?’. There are two main things that I think NVIDIA want out of holodeck that were not obvious from the discussions: fully interactive physics (see above for the redefinition of PhysX, for example), and also haptic feedback in a physical environment. From our discussions with NVIDIA, it sounded very clear that this was a third party problem to solve, not NVIDIA’s own. From NVIDIA’s standpoint, it sounds like they will implement an API for haptic feedback, but how that manifests will be someone else’s problem.

*Images for the Hands-On were taken from NVIDIA’s presentations, as I forgot to set up a video camera while taking the demo

Holodeck Early Access

Interested parties may fill out NVIDIA’s Holodeck early access application form. Note that this is separate from the Holodeck news notification form.

You might not be able to overclock Nvidia’s GeForce GTX 1070 Ti

We are fairly confident that Nvidia is readying a GeForce GTX 1070 Ti graphics card that slip into its product lineup between the non-Ti variant and the higher-end GeForce GTX 1080. However, if you are hoping to squeeze out GTX 1080-like performance through overclocking, you might be in for a rude awakening—the latest rumors suggest Nvidia is locking the frequency on the GTX 1070 Ti.

Bearing in mind that none of this is official, the rumor traces back to two sources, and the reports are slightly conflicting. Eteknix says it heard from an “industry insider” that the GeForce GTX 1070 Ti will not support overclocking in any way, shape, or form. “In addition, we’ve been informed that Nvidia will not release any reference cards and all AIB (add-in-board) partner cards will be locked to the same speeds. However, price and aesthetics are expected to differ across partner cards,” Eteknix says.

Expreview is reporting similar news, but according to a Google translation of the Chinese-language website, Nvidia is only restricting its hardware partners from cranking up clockspeeds at the factory, with the base clock fixed at 1,607MHz and boost clock set at 1,683MHz. The site suggests that “manual overclocking” will still be possible, meaning that consumers will be able to take matters into their own hands.

Rumored specs point to the GeForce GTX 1070 Ti being close in performance to the GeForce GTX 1080. The 1080 has 2560 CUDA cores, while the 1070 Ti is rumored to have 2432 cores—so only one SMM disabled, compared to the five disabled SMs (1920 cores) on the current 1070. The 1070 Ti is said to have the same base clock as the 1080, with a slightly lower 1683MHz vs. the 1080’s 1733MHz boost clock.

That’s not a big difference, and assuming Nvidia allows manual overclocking, it shouldn’t be too difficult to achieve 1080 levels of performance. Which means it would make some sense for Nvidia to restrict its partners from offering factory overclocks that are ‘too high,’ but to date Nvidia hasn’t ever blocked end-user overclocking.

Whatever the truth may be, we shouldn’t have to wait long to find out—leaks and rumors to this point suggest the GeForce GTX 1070 Ti will be announced by the end of this month, with a suggested price of $429.

Nvidia’s Free GeForce NOW Beta Lets You Play System Intensive PC Games on Your Mac

Apple’s Macs aren’t optimized for gaming and often don’t have powerful enough GPUs to run the latest gaming titles, a problem that Nvidia is aiming to solve with its GeForce NOW service designed for Macs.

GeForce NOW for Mac, currently in beta testing in North America, lets you use a virtual GeForce GTX gaming PC in the cloud to run games that otherwise may not be possible to play on a Mac. The only requirement is a good internet connection, with the virtual gaming PC handling all of the GPU and CPU requirements.


Since Macs aren’t known for being gaming machines, PC makers don’t typically design new titles to run on Macs. That’s also an issue that can be solved with GeForce NOW, because it can stream PC-only games too. So if you’ve been wanting to play Player Unknown’s Battlegrounds on a Mac, for example, you can do so with GeForce NOW.

GeForce NOW integrates with Steam and works with the games you already own, so it’s not a gaming service that provides access to games. You need to purchase the games you play, with GeForce NOW providing the power to play them.

I’ve been testing GeForce NOW this week and while it’s not perfect, it’s promising. Setup is as simple as downloading the GeForce NOW for Mac app and then connecting a Steam account. Since you’re essentially streaming the gameplay from the cloud, when you choose a free-to-play game or a game you’ve purchased on Steam, you don’t need to install it because it’s already installed and ready to go.


With Player Unknown’s Battlegrounds, I bought it on Steam, logged into GeForce NOW, and had it up and running on my 2013 iMac in about 30 seconds. GeForce NOW runs a system check when you launch it so you can tell if your connection is going to be good enough for optimal streaming.

GeForce NOW is heavily reliant on a fast internet connection, requiring a 25Mb/s download speed at a minimum and a 5GHz wireless router. Nvidia recommends a 50Mb/s connection or higher to account for other potential internet traffic. Even with a Wi-Fi connection that met those demands, I ran into some problems with frame loss that made the game unplayable a couple of times.


When switching over to a hardwired ethernet connection, the game ran more smoothly, so if you don’t have a Wi-Fi connection that’s robust enough, a physical connection might be necessary to use the service. I was able to successfully play over WiFi for most of my testing, though, as I didn’t see the frame loss issue consistently. To ensure players get a low ping, Nvidia has servers located across the United States.

Playing PUBG using GeForce NOW was just like playing it on a PC. I was able to play right alongside PC gamers, and while there was still a bit of stuttering and lag, it worked. I was using a late 2013 iMac, but GeForce NOW is supported on a long list of machines manufactured in 2008 and beyond.

Along with PUBG, GeForce NOW supports a number of other popular games, and Nvidia is adding support for more on a regular basis. Some of the supported titles include League of Legends, Fallout 4, Overwatch, Path of Exile, World of Warcraft, The Witcher 3, Rocket League, Destiny 2, and Middle-earth: Shadow of War.

Nvidia will be beta testing GeForce NOW for Mac through the end of the year, so it’s free to download and use for the time being. A launch is planned for 2018, and final pricing for the service has yet to be announced. The beta is limited to the United States and Canada.

Nvidia’s Drive PX Pegasus Is A Royal Flush For Self-Driving Cars – NVIDIA Corporation (NASDAQ:NVDA)

The Auto segment of Nvidia (NVDA) is the smallest contributor in terms of quarterly revenue. It only contributed $142 million in Q2 FY18. The Auto segment can probably see a big spurt in growth when Nvidia starts shipping its Drive PX Pegasus next year. Drive PX Pegasus is Nvidia’s ambitious license-plate-sized in-vehicle datacenter-level processor intended for level 5 (or fully autonomous) robotaxis. There are now 25++ companies developing Nvidia Drive PX-based robotaxis.(Source: NVIDIA)

Anything that can help increase the quarterly revenue of Nvidia’s Auto business unit is an important matter that should be discussed here. To gauge just how important self-driving car technology-related products like the Drive PX Pegasus, read on Google’s (GOOG) (NASDAQ:GOOGL) billion-dollar legal suit against Uber allegedly receiving Waymo trade secrets.

The Drive PX Pegasus is 10x more powerful than the Drive PX 2 hardware. It can reportedly match the compute power of a 100-server datacenter rack. I consider this new hardware from Nvidia as the super-sized version of Intel’s (INTC) neuromorphic processor.

A little tweaking from Nvidia and Drive PX Pegasus can also self-learn like a human brain. Simultaneously, it can still deliver over 320 trillion operations per second compute performance without being tethered to the cloud.(Source: NVIDIA)

The Drive PX Pegasus could catapult Nvidia as the go-to processor supplier of the $38 billion/year ride-hailing industry’s adoption of robotaxis. Goldman Sachs also expects the ride-hailing industry to grow to $285 billion by 2030.

The Drive PX 2 Pegasus level 5 autonomous car processor can make Nvidia the enabler of some unicorn companies. The massive valuation of ride-sharing firms/taxi-hailing like Uber ($68 billion) and Didi Chuxing ($50 billion) can probably come true when they start augmenting their human-driven cars with Nvidia-powered robotaxis.

Nvidia can usher in the datacenter-in-a-car concept. Now that AMD is encroaching the high-end gaming/workstation GPU market with its Vega GPUs, Nvidia needs to work harder growing its Auto and datacenter GPU businesses.

Why I Am Optimistic About Robotaxis

Since Intel and Advanced Micro Devices (AMD) won’t have an equalizer to the Drive PX Pegasus, Nvidia can sell it at a high markup. After government regulators approve level 5 autonomous cars on the road, taxi fleet operators and ride-sharing companies will start using them. It is probably going to take 3-5 years before government regulators approve level 5 robotaxis. However, Nvidia’s surging valuation is already boosted by its potential role as the top supplier of semiconductor products for self-driving cars.

The three-year return of NVDA is more than 1,000%. Nvidia launched its Drive PX hardware/platform in March 2015. Nvidia priced its first Drive PX car processor at $10,000 and it still found acceptance. There are now more than 25 car manufacturers who work with Drive PX hardware. We have to conclude that the Auto segment is a contributor to the massive 3-year return of NVDA. No other company has matched Nvidia Drive PX’s level of acceptance among car manufacturers.

(Source: Morningstar)

Going forward, self-driving taxis can be better taxi-hailing service providers than human driven cars. More often than not, human drivers tend to burden me with stories about politics, their health, their family, their favorite TV shows and sports teams. I am ride-sharing to get from Point A to Point B. I do not need the additional aggravation of listening to another person’s ills/problems/thoughts.

If the travel time will take more than 30 minutes, I would prefer to nap rather than petty talk with a human driver. Robotaxis will assure me I won’t be driven around by chance by a sickly/DUI driver. Unlike a human driver, the Nvidia Drive PX Pegasus-based robotaxi won’t consider kidnapping or robbing its passenger.

Final Thoughts

The Gaming segment is currently the biggest revenue/profit generator of Nvidia. However, AMD will eventually take more market share in discrete gaming/mining GPUs. Nvidia developing more GPU products for Auto and datacenter is commendable. As far as I know, AMD still has no car-centric GPU in the pipeline.

As per released specs, the 500-Watt Drive PX Pegasus will come with 2 integrated Volta GPUs and 2 discrete post-Volta GPUs. The first Volta GPU, the Tesla V100 comes with 21 billion transistors, 5,120 CUDA cores, and 640 Tensor cores.

(Source: Wikipedia/Nvidia)

The Drive PX Pegasus is a stellar example of how far Nvidia has achieved in making its formerly gaming-only GPUs become in-demand for other enterprise-level, scalable applications. The rapid appreciation of Nvidia’s market cap over the last twelve months is because many investors believe in the future roles of GPUs in datacenter/deep learning and self-driving cars.

NVDA is a buy. According to the Artificial Intelligence-powered Relative Valuation Model of FundamentalSpeculation, NVDA is fairly valued.

(Source: FundamentalSpeculation)

FundamentalSpeculation derived a fair value of $182.74 for NVDA. It came about after FundamentalSpeculation’s AI computed the average valuation ratios of other companies with similar business fundamentals of Nvidia to get the Cohort Fair Value. After which, the Cohort Fair Value was modified with values derived from calculating the average valuation ratios of Nvidia’s peers in the Technology sector and Computer Hardware Industry.

Disclosure: I am/we are long NVDA, AMD, INTC, GOOG.

I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

3 Industries To Thank For Nvidia’s Record Stock Price

Nvidia NVDA has gained more than 74% year-to-date, and the red-hot graphics chip manufacturer has easily emerged as one of Wall Street’s most popular stocks. As shares sit comfortably near their all-time high, many investors are debating whether Nvidia can break even higher-while some are still wondering how the company managed to hit this new peak in the first place.

For years, Nvidia has been a leader in the production of graphics processing units (GPUs). These high-powered chips are designed to facilitate the creation of images in a frame buffer, and in recent years, GPUs have been the go-to choice for people working with complex algorithms and large chunks of data.

This tiny piece of technology packs a serious punch, and its uses are growing nearly every day. For example, demand for GPUs from cryptocurrency miners has picked up lately. As the prices of digital currencies like bitcoin and ethereum have soared, miners have scrambled to build powerful machines that are capable of mining these coins.

But cryptocurrency mining is unlikely to be a major long-term growth driver for Nvidia. Instead, the company is focusing on a few core industries-each with booming addressable markets-that it is already dominating. And as management showed in a recent shareholder presentation, these core industries still have plenty of potential:

(Source: Nvidia )

Video gaming has always been Nvidia’s bread and butter, as the company’s GPUs are the perfect tool to deliver great performance at a reasonable price. Gaming is the world’s largest entertainment industry, and Nvidia says that its products are in the hands of about 200 million gamers right now.

In its recent presentation, Nvidia also mentioned that the rising popularity of esports will expand its potential market, and the company noted that new AAA titles-as well as HDR, 4K, and VR-are helping to drive demand for powerful chips (also read: Esports Is The Next Billion Dollar Industry: 3 Stocks to Watch ).

On top of this, Nvidia has become perhaps the most popular AI pick on the market. We’re just now entering the early days of the artificial intelligence revolution, and Nvidia has already developed an end-to-end AI platform, funded AI research, and worked to define industry-wide standards.

Nvidia has also created the CUDA programming model, which has allowed the GPU to act as a general purpose computing tool. Specifically, Nvidia’s own line of Volta GPUs provide the performance needed to tackle constantly evolving algorithms and applications.

In a similar vein, Nvidia stands to dominate the booming self-driving car industry. Of course, Nvidia is the furthest thing from a car company, but its image processing power is exactly what is needed to fuel the autonomous driving vision technology.

According to Nvidia’s presentation, 225 companies are now developing with its DRIVE PX platform. Nvidia also has distinct partnerships with several automotive behemoths, including car companies like Tesla TSLA and Toyota TM , as well as suppliers like Autoliv ALV and Bosch.

Without a doubt, the gaming, AI, and self-driving car industries are what has gotten Nvidia this far. But more importantly, these budding markets hold the key to the company’s future. Investors should look for Nvidia to continue to grow alongside these new trends.

Want more stock market analysis from this author? Make sure to follow @ Ryan_McQueeney on Twitter!

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Nvidia’s AI Developments Don’t Change Self-Driving Car Timeline (NASDAQ:NVDA)

Robotics Analyst: Nvidia's AI Developments Don't Change The Self-Driving Car Timeline

NVIDIA Corporation (NASDAQ: NVDA) stirred the markets Tuesday with news of its groundbreaking supercomputer capable of supporting fully autonomous vehicles. The announcement drove Nvidia shares to the $190 level.

But for all the excitement, the world’s first artificial intelligence computer for “Level 5” autonomy may not widely impact the AV space.

“This is definitely a net positive for the entire self-driving car space but doesn’t change our thesis on electric or self-driving vehicles,” Austin Bohlig, robotics industry adviser at Loup Ventures, told Benzinga. “At the least, it may have modestly shortened the time frame when we begin to see self-driving vehicles on the road, but our 2020 date for the influx to begin still holds.”

Nvidia is already considered a leader among AV suppliers. Loup managing partner Gene Munster previously listed Nvidia as the field’s top components manufacturer and the best way to play the AV theme outside of a Tesla Inc (NASDAQ: TSLA) stake.

The Tesla Impact

Tesla currently uses Nvidia chips, but was recently reported to have partnered with Advanced Micro Devices, Inc. (NASDAQ: AMD) in an alleged step toward self-sufficiency. Analysts posited that the move could be indicative of Tesla’s eventual shift from Nvidia products but insisted that Nvidia investors had little to worry about.

Tesla supporters were similarly unconcerned by Nvidia’s latest demonstration of strength.

“As it relates to Tesla, I don’t think they are second guessing themselves [with regard to the AMD partnership],” Bohlig said. “While Nvidia may have a slight [leg] up in the GPU space, AMD has made great progress over the last couple years and is much more competitive today.”

Loup still considers Tesla and Alphabet Inc (NASDAQ: GOOGL)’s Waymo leaders in self-driving auto manufacturing.

Related Links:

The Autonomous Future: Munster’s 2020 Vision Of The Road

Gene Munster: Traditional Car Manufacturers Face ‘Innovator’s Dilemma’

Posted-In: Analyst Color News Travel Top Stories Exclusives Tech Trading Ideas General Best of Benzinga

Nvidia’s Shares At Risk Of Falling 12%

When it comes to Nvidia Corp. (NVDA), the bulls were out in full force on Monday as usual. The shares have skyrocketed 17-fold in five years and were up more than 2 percent to at least $185 in daily trading. Now, the latest issue of Barron’s is offering investors a new, exotic way to profit off Nvidia: by purchasing call options as a good way to play the stock’s rise to $200.

This optimism may be unjustified, according to a detailed analysis of options trades, which indicate that Nvidia’s shares could fall as much as 12 percent as it enters a period of risky volatility for investors.

Huge Implied Volatility

The big problem: these $180 call options are trading at a significant premium due to the astronomically high implied volatility of Nvidia’s shares. That implied volatility is nearly 6 times more expensive than the S&P 500, which has an implied volatility of 7 percent. This means there is a very real risk that Nvidia’s shares could plunge below $164 a share, as explained further below.

The Nvidia November call options are trading with an implied volatility of 42 percent, which is 16 percentage points higher than high-flying Amazon, and 2 percentage points higher than even Netflix. The options market is pricing in significant levels of volatility, using the at-the-money $185 long straddle set to expire on November 17. The options strategy, which involved buying both a put and call, is pricing in nearly a 12 percent move up or down in the stock by expiration. This means the shares would have to trade below $163.50 or above $206.40 to be profitable, as indicated by options trades.

An earlier story this week looks at the challenges facing Nvidia from a technical and fundamental perspective. (See also: Nvidia Rally Is One Step Closer to Exhaustion.)

Traders Playing Volatility

(Interactive Brokers)

With nearly 8,500 contracts of open interest on the $185 calls and 7,000 contracts of open interest in the $185 puts, it suggests that traders with a bullish or bearish outlook are basically split. Perhaps more important, it tells us that traders are merely playing volatility in this stock, looking for Nvidia’s shares to have a big move either up or down over the next month. Options pricing is derived from time value and intrinsic value. The value of the options is expensive because the intrinsic value is being lifted by high levels of implied volatility.

Bearish Trading Patterns

The trading patterns look especially bearish for the stock over the longer-term. As noted in previous Investopedia stories, the stock is currently in a rising wedge formation, which is a bearish technical pattern, and could symbolize a decline ahead. Additionally, volume has been declining for the stock on its most recent move higher, which also suggests that buyers are not as numerous in the past.

The stock continues to trade with lots of volatility, and the options market is pricing in even more volatility in the coming weeks. Which way the stock will move from current levels is the prominent question. However, declining volume could suggest the bulls are getting tired. That, coupled with rising expectations of volatility, suggests that Nvidia’s shares could be set for a fall.

Positioning for Nvidia’s Next Big Move

Nvidia is red hot in the stock market and lukewarm in the options market. This disconnect creates an intriguing opportunity for anyone who wants a piece of one of the hottest companies on Wall Street.

Though shares are up some 70% so far this year, the chip maker’s options are not priced with a greed (or fear) premium, which is arguably a bit unusual. Hot stocks often have hotter options premiums, but not Nvidia (ticker: NVDA). This is probably due to a combination of stock and options trading patterns and the mathematics of volatility pricing.

When stocks advance, it basically creates a trail of low realized volatility, which measures what happened in the past and functions like a magnet to pull down implied volatility, which measures what may happen in the future.

At about 44%, the implied volatility of Nvidia’s November options is about six times higher than options on the Standard & Poor’s 500 index. But Goldman Sachs’ analysis suggests that Nvidia’s options are mispriced ahead of two key events—a conference and an earnings report—that could spark another rally in the shares.

Goldman’s derivatives strategists, Katherine Fogertey and John Marshall, are telling clients to buy November $180 calls in anticipation of the stock getting a boost after executives speak at the GPU Technology Conference in Munich, scheduled from Oct. 10 to Oct. 12. The conference could serve as a “positive catalyst” ahead of earnings that Goldman expects will be released on Nov. 8.

When the stock was at $179, Nvidia’s November $180 calls cost $11.25. If the stock rallies to, say, $200, the calls are worth $20.

That calculation may seem optimistic, since the stock has not traded higher than $191.20 in the past 52 weeks. But many investors enter options trades planning to double their money, which could happen if the stars align once again with Nvidia. Of course, if the company reports earnings after the November expiration, Goldman’s trade may sputter.

Investors who want to capture some, or all, of that potential sputter can sell Nvidia’s November $170 put for about $6.20 at the same time they buy the November $180 call. The put sale lowers the cost of the call to $5.05 and positions investors to buy shares at $170 or lower.

WHEN MOST INVESTORS want to buy options on an expensive stock, such as Amazon (AMZN), they tend to focus on puts and calls that expire in a relatively short time. They do this to avoid paying too much money for contracts packed with a time premium. So a trade early last week to buy about 2,500 Amazon November $960 calls for about $35.90 to almost $40 when the stock was trading around $956 merited a cameo appearance on screens that feature unusual trading patterns.

The $8.7 million trade had 146 parts, ranging from one to nearly 500 contracts, and lasted just over a second, according to Henry Schwartz of Trade Alert, a trading-volume analysis firm. The expiration, which should cover Amazon’s next earnings report, suggests that an investor is bullish on the stock. If the reasoning is right, the trade suggests this investor thinks the stock may rise above $1,000 by the middle of November. Amazon’s 52-week range: $710.10 to $1,083.31.

Finally, a note of caution: Some $2 trillion has rotated from actively managed and value-focused funds to passive ones—a rotation that Marko Kolanovic, JPMorgan’s top quantitative strategist, contends may ultimately hurt the stock market. In a note to clients, Kolanovic characterized the shift as eliminating “a large pool of assets that would be standing ready to buy cheap public securities and backstop a market disruption.”


STEVEN SEARS is the author of The Indomitable Investor: Why a Few Succeed in the Stock Market When Everyone Else Fails.

Comments: steve.sears@barrons.com

Follow: @sm_sears