Nvidia Stock Forecast: Why You Should Add More Nvidia Shares

motek 1The article was written by Motek Moyen Research Seeking Alpha’s #1 Writer on Long Ideas and #2 in Technology  – Senior Analyst at I Know First.


  • Nvidia’s Q1 FY2019 ER was outstanding. It beat Wall Street’s EPS and revenue estimates. The EPS of $2.05 beats by $0.39.
  • The Q1 FY 2019 of $3.21 billion (+65.5% year-over-year) beats by $310 million.
  • In spite of this excellent earnings report, NVDA still dipped by more than 2.5%. This cynical reaction is uncalled for.
  • My takeaway is that long-term growth investors should add more NVDA. This stock has more upside potential based on it one-year algorithmic market trend forecast.
  • The company’s  runaway leadership in datacenter GPU accelerators and self-driving car processors makes Nvidia a guaranteed long-term winner.

I was one of those who sold Nvidia (NVDA) shares prior to its Q1 FY 2019 earnings report last week. However, I did retain almost 40% of my NVDA stake. The impressive +65.5% year-over-year growth in revenue convinced me that long-term growth investors should still add more Nvidia shares (or go long NVDA).

The cynical reaction to Nvidia’s outstanding beat on EPS and revenue estimates is unfair. Nvidia’s stock dipped by more than 2.5% post-earnings. I see this an opportunity to do a valid contrarian move.  Long-term growth investors should add more NVDA shares while it still trades below $280.

Most Wall Street analysts are still bullish for Nvidia. They have a consensus 12-month price target of $280.59 for NVDA.

(Source: TipRanks)

 Gaming And Cryptocurrency Mining Are Still Strong Tailwinds

 The consensus optimism of Wall Street analysts over Nvidia will eventually lead to more hedge fund managers and institutional investors to raise their bets on Nvidia. Nvidia’s resilience against the rejuvenated GPU (Graphics Processing Unit) products of Advanced Micro Devices (AMD) is best illustrated in the 68% year-over-year growth in its Gaming segment’s quarterly revenue of $1.72 billion.

Even without releasing a consumer version of its Volta GPU product, Nvidia is still super-dominant in gaming and workstation GPUs. I also expect that the anti-ASIC forks of Ethereum and Monero will keep cryptocurrency miners addicted to GeForce video cards for many quarters to come.

In spite of the hype over Bitmain’s upcoming Ether-friendly ASIC mining hardware, the price of Ethereum is still above $680. Mining Ethereum via GeForce GTX 1070 and GTX 1070 Ti is still very profitable. Further, there will be other blockchain currencies that will come out after Ethereum mining gets dominated by highly-efficient ASIC hardware.

Discrete GPU products will therefore have a persistent tailwind from cryptocurrency mining. Any future  weakness in Ethereum mining can be offset by the millions of gamers who have been waiting for so long to get their hands on Nvidia’s latest discrete video cards.


Why You Should Really Raise Your Bet On Nvidia

The 71% year-over-year growth in Datacenter segment’s quarterly revenue ($701 million) confirmed  that Nvidia has zero competition in datacenter GPU acceleration or deep learning processors. Intel has no answer to Nvidia’s Tesla and Volta super GPU products.

AMD unveiled its deep learning Radeon Instinct GPU product last year. However, Nvidia’s growing quarterly revenue from its Datacenter segment is a hint that few customers are buying Radeon Instinct GPUs. I believe it will take several years before AMD can even match the compute performance of the old Tesla P100. I don’t think AMD can catch up with the new Volta-based Tesla V100.

(Source: Nvidia)

The total addressable market for datacenter-centric GPUs will reach $50 billion by 2023. For 2018, Nvidia will likely earn $2.8 billion from its Tesla/Volta GPUs. Nvidia, therefore, has more upside potential in datacenter sales for the next four years.

The inability of AMD to compete in deep learning GPUs is a blessing for Nvidia. Big datacenter operators like Google (GOOG) have no choice but to keep on buying pricey Volta GPUs from Nvidia. Google recently purchased a bunch of Nvidia Volta GPUs for its Google Cloud platform. Google will rent out these Volta GPUs to its artificial intelligence/deep learning customers for at least $2.48/hour.

Sad but true, companies like Google already have their own custom datacenter processors. The problem is their cloud computing customers still prefer to rent Nvidia’s Tesla/Volta GPUs for their enterprise applications/deep learning experiments.


Long-term growth investors who want to be among the early-bird winners in the growing artificial intelligence and self-driving car industries should go long NVDA. As the pioneer in GPU-powered deep learning and datacenter workload acceleration, Nvidia is winning the trust of more enterprise customers.

As more enterprise customers sign-up, Nvidia is gradually establishing as the industry-standard for deep learning and datacenter processors. You know Nvidia is a great long-term investment when cloud infrastructure leaders like Amazon (AMZN), Microsoft (MSFT), and Google keep buying Tesla/Volta GPUs. Microsoft and Google can keep making their own custom x86/FPGA and ARM-based datacenter processors. However, their customers will still prefer the proven/tested reliability of an Nvidia Tesla V100 GPU.

My buy rating for NVDA is supported by its very bullish one-year algorithmic market trend forecast score of 416.19. The predictability score of 0.72 also told me that I Know First’s artificial intelligence-powered stock picking algorithm has an excellent history of correctly predicting NVDA’s one-year market trend performance.

Past I Know First Forecast Success With Nvidia

On August 15, 2017 I Know First  published a bullish article about Nvidia.

NVDA is with about 57% gain since this bullish forecast.

This bullish forecast for NVDA sent to the current I Know First subscribers on  August 15, 2017.

I Know First Algorithm Heatmap Explanation

The sign of the signal tells in which direction the asset price is expected to go (positive = to go up = Long, negative = to drop = Short position), the signal strength is related to the magnitude of the expected return and is used for ranking purposes of the investment opportunities.

Predictability is the actual fitness function being optimized every day, and can be simplified explained as the correlation based quality measure of the signal. This is a unique indicator of the I Know First algorithm. This allows users to separate and focus on the most predictable assets according to the algorithm. Ranging between -1 and 1, one should focus on predictability levels significantly above 0 in order to fill confident about/trust the signal.