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Technology Stocks : Investing in Exponential Growth

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From: Frank Sully12/18/2020 11:13:56 AM
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NVIDIA: FWIW, I am planning a modest investment of 40 shares into NVIDIA next week. I like it's exponential growth and AI potential, particularly with the purchase of ARM. Any comments? Here is a SA article on valuing NVIDIA.

Nvidia: Deep Dive And Cash Flow Analysis
Dec. 14, 2020 5:56 AM ET
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15 comments
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About: NVIDIA Corporation (NVDA)



Trevor Jennewine
Long Only, Value, Growth, long-term horizon



(962 followers)



Summary
Nvidia is a leading provider of GPUs and AI solutions, with products that address a wide range of use cases.

Management estimates Nvidia's addressable market will reach $250 billion by 2023 - nearly 17 times Nvidia's trailing 12-month revenue.

Based on my DCF model, I estimate Nvidia's fair value at $517 per share.

Nvidia is a buy for long-term investors.

Investment Thesis In the age of big data and AI, Nvidia's ( NVDA) GPU-accelerated computing platforms and AI solutions address critical needs for developers, researchers, and scientists across various markets, from high performance computing and data analytics to autonomous vehicles and robotics.

My investment thesis is summarized in the following points:

1. Nvidia's intellectual property gives it an advantage over competitors in several quickly growing markets.

2. Nvidia has an enormous market opportunity, at $250 billion by 2023.

3. Nvidia's financial performance has been stellar in recent years. Since 2015, Nvidia has grown revenue at 26% per year and profits at 44% per year.

Nvidia's Market Opportunity Nvidia is a leading provider of GPU-accelerated computing platforms and AI solutions. Nvidia's products have applications in a variety of industries and markets, including gaming, professional visualization, data centers, and edge computing.

The GPU is the foundation of Nvidia's computing platforms. While GPUs were originally designed to carry out the complex calculations necessary for graphics processing, Nvidia's parallel computing platform, CUDA, allows GPUs to be used as general purpose processors, too.

Gaming: For PC gamers, Nvidia's hardware solutions include several generations of GeForce Graphics Cards, including the most recent RTX 30 series, which are powered by Nvidia's latest GPU architecture: Ampere. The RTX series graphics cards combine ray-tracing and AI to deliver more realistic visual effects.

Professional Visualization: For animators and design professionals, Nvidia's hardware solutions include several generations of Quadro GPUs. However, Nvidia is dropping the name Quadro from the upcoming RTX A6000. The RTX A6000 will incorporate Ampere architecture GPUs, ray-tracing, and AI tools to deliver enhanced graphics to a wide range of users, from animators using Pixar RenderMan, to design engineers using Autodesk ( ADSK) AutoCAD, to marketers using Adobe ( ADBE) Premiere Pro.

Data Centers: Nvidia's data center products are used by data scientists, researchers, and developers to accelerating workloads in high performance computing (HPC), data science, artificial intelligence, machine learning, and deep learning.

Nvidia's data center hardware products include the HGX platform, built with Nvidia GPUs, NVLink-powered NVSwitches, and Mellanox InfiniBand networking. HGX servers are used to accelerate AI and HPC workloads. The HGX platform is also the building block for another Nvidia product: the DGX platform. This server includes the previously mentioned HGX components, but also incorporates CPUs. The DGX server is targeted at AI applications, such as training deep neural networks for deployment in edge servers, autonomous robots, or autonomous vehicles.

Source: Nvidia Investor Presentation ( May 2020)

Complementing its hardware, Nvidia's GPU Cloud (NGC) provides access to GPU-optimized software designed to accelerate deep learning, machine learning, and high performance computing applications. This provides access to deep learning frameworks, like TensorFlow and PyTorch, which enable the designing, training, and validation of deep neural networks. It also includes TensorRT, an inference engine that runs trained neural networks on GPUs to generate real-time AI inferencing.

Edge Computing: In 2019, Nvidia launched the EGX platform, a family of GPU accelerated computing systems designed to handle AI workloads at the edge - it includes both EGX servers for edge data centers and embedded Jetson systems for edge devices.

Using trained AI models, the EGX servers generate inferences based on data streamed from edge devices (such as an IoT sensor). The EGX server then makes a decision, and sends the data back to the edge device. This technology, known as edge AI, has applications across a range of industries: retail, manufacturing, telecom, smart cities, healthcare, etc. For instance, by analyzing traffic patterns, EGX servers could coordinate traffic lights throughout a city to minimize roadway congestion.

In the event of a low confidence decision, the EGX server can send the information back to a central data center, where the AI model can be retrained with new data, then redeployed at the edge. This dynamic is shown in the graphic below.

Source: Nvidia EGX Platform.

Depending on the edge use case, Nvidia offers various software solutions that complement its hardware and help developers build the applications they need: Metropolis for smart cities and retail, Isaac for robotics and manufacturing, Clara for healthcare, Aerial for 5G, Merlin for recommendation systems, and Jarvis for conversational AI.

Market Opportunity If the acquisition of ARM is approved, Nvidia's management estimates the company's market opportunity will reach $250 billion by 2023:

  • Devices: $95 billion
  • Data Center: $80 billion
  • Auto/Edge AI: $75 billion
  • The total figure, $250 billion, represents nearly 17 times Nvidia's revenue over the last 12 months - that's a big opportunity. And by combining Mellanox's high performance interconnect solutions, ARM's energy-efficient processors, and Nvidia's world class GPU-accelerated computing platforms, the company would be well positioned to capture growth across all three markets listed above.

    Financial Analysis Nvidia has posted strong revenue growth in recent years, increasing sales from $5.0 billion in fiscal 2016 to $14.8 billion over the trailing 12 months, which clocks in at 25.6% per year. The charts below shows Nvidia's revenue growth in each of its four business segments: Gaming, Professional Visualization, Data Center, and Autonomous Vehicles.

    Source: Nvidia Investor Presentation ( November 2020)

    So far in fiscal 2021, Nvidia's revenue growth has accelerated substantially, up nearly 57% in the most recent quarter. Despite some margin compression, growth in revenue has accelerated earnings growth as well, with profits up 46% in Q3 2021.

    Like the income statement, Nvidia's balance sheet looks strong, with $10.1 billion in cash and marketable securities compared to $7.6 billion in debt and lease liabilities.

    Valuation In my DCF model, I have made the following assumptions:

  • Growth Rate: 20%
  • Terminal Rate: 2.9%
  • Discount Rate: 8.0%
  • Since 2015, Nvidia's FCF-per-share has grown at an annualized 30%. I have selected a much more conservative 20% to introduce a margin of safety. I selected 2.9% as the terminal growth as this figure corresponds with worldwide GDP growth over the last decade. Finally, I have selected 8.0% as my discount rate as this figure corresponds with the average return of the S&P 500 since 1957.

    Source: Created by the author.

    Based on my DCF model, I estimate Nvidia's fair value at $517. This number is roughly equivalent to the stock price at the time this article was written.

    I have also used FCF-per-share to model potential returns over the next five years. Again, I assume 20% annualized growth in FCF per share. But because Nvidia's current price-to-FCF multiple is near its historical high, I have selected three more conservative multiples: 70, 50, and 30.

    In the most bullish scenario, Nvidia returns roughly 18% per year over the next five years. And in the most bearish scenario, Nvidia returns -0.5% per year over that time period.

    Conclusion Nvidia is a market-leading provider of the GPU-accelerated computing platforms and AI solutions needed for high performance computing, machine learning, and deep learning. Given the company's strong competitive presence in these high growth markets, Nvidia looks well positioned to capture value in the years ahead.

    For long-term investors, I rate Nvidia a buy at $517.

    Disclosure: I am/we are long ADBE, NVDA. 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.
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