June 15, 2024. A quantitative feature that I have used to help identify companies with a durable competitive advantage, is the relatively consistent growth of revenue over many years.  I reason that the persistent climb in revenue is related to the indispensable nature of company products or services, with related durable competitive advantage, and to a large, persistent demand for them, commonly referred to as a “long runway” of persistent total addressable market.  I had avoided cyclical companies, whose stock price rises or falls with the demand cycle.  In order to obtain a superior return, you need to buy at the bottom of the cycle. But in practice it is difficult to know when the company’s fortunes will recover, or when the stock price will stop falling.

Visa and Microsoft are examples of companies with strong competitive advantages and products that are indispensable for large and growing markets.  Since its IPO in 2008, Visa’s  sole decrease in annual revenue occurred in 2020. Government policies enacted during the history making Covid 19 pandemic abruptly curtailed international travel. The fall in purchases by persons travelling internationally slowed cross border payment volumes.  Impressively, Visa total annual revenue did not decrease during the Great recession of 2008-2009.

Microsoft has had minor if any decrease in revenue except in 2009 due to great recession.  In that economic crisis, primarily revenue from Windows software sold to corporations (the Client business segment) decreased, and price cuts for gaming software and hardware slowed gaming revenue.  By 2010 both revenue and earnings exceeded the 2008 levels.  Of note, revenue from the Business Division, including the Office suite of productivity software, was essentially flat. This product was more economically resilient because it has powerful switching costs and generates revenue largely through multiyear contracts.

Nvidia was brought to my attention by the rise of Artificial Intelligence (AI) in public awareness.  Review of its Annual Reports , shows that Nvidia has in the past had prolonged decreases in revenue and earnings, related to adverse macroeconomic conditions. For instance, in 2009 revenue decreased relative to 2008, and did not recover until 2013. Diluted Earnings per Share decreased as well in 2009, showing a loss in 2009 and 2010, and not recovering the level of 2008 until 2017.  In previous periods of its history, rising costs caused earnings to show multiple years of losses or declines without a loss of gross revenue.

Revenue and earnings fell during the Great Recession because Nvidia at that time, derived most of its revenue from products for the PC market. In FY 2009, desktop GPU product sales decreased 29% year over year.  Moreover, cyclical decline can have prolonged effects. PC makers build inventory during periods of anticipated growth. They are left with excess inventory in the event this growth fails.  They can then delay additional purchases of the GPU inputs to PC manufacture, until end customer demand has resumed.

The datacenter GPU business segment, which now contributes the lion’s share of Nvidia revenue, did not yet exist in that era.

And yet, during the period of the Great Recession of 2009-2009, the research engineers at Nvidia were laying the foundation for its history making advances and competitive advantage of the next decade and more.

During 2008 as the global financial crisis accelerated, Nvidia “announced a workforce reduction to allow for continued investment in strategic growth areas… we eliminated … about 6.5% of our global workforce. … expenses associated with the workforce reduction, totaled $8.0 million. We anticipate that the expected decrease in operating expenses from this action will be offset by continued investment in strategic growth areas. ” (Nvidia 10K FY 2009) (Nvidia Fiscal Year ends in January of that year, so it reports on business activity occurring chiefly in the previous calendar year). 

Indeed, R&D expenditures continued to climb during this period.  In fiscal years 2008, 2009, 2010, R&D expenses continued to climb, making up 17%, 25% and 27.3% of revenue for the respective years. (Nvidia 10K FY 2010, p36).

Nvidia GPU chips were originally designed for use in gaming and graphics software applications and by the mid-1990s Nvidia had come to dominate that market. The company IPO’d in 1999. In 2006 Nvidia conceived CUDA, a software platform that enables software to employ the parallel processing and accelerated computing of the GPU, for diverse applications other than solely graphics.  It supports a range of languages and a comprehensive armamentarium of tools allowing it to be used for a wide range of applications. CUDA builds competitive advantage in several ways. The CUDA software platform enables engineers to use accelerated computing driven by Nvidia GPU chips, for a wide variety of other useful and novel applications. This expands the addressable market of use cases for the GPU. Nvidia has fostered an ecosystem of software centered around diverse applications of CUDA, collaborating with myriad companies in diverse industries, from healthcare to pharmacy to automotive, to nurture vertical stacks of software supported by the CUDA platform. Approximately 5 million developers in that ecosystem create a network effect competitive advantage for other GPU manufacturers such as AMD. CUDA is compatible only with Nvidia chips. While it is optimized for upcoming, ever more potent chips, the software ensures backwards compatibility, so developers and end users can often update application software with their current hardware.  There is a strong switching cost competitive advantage versus other chip makers.

Nvidia is one of the rare companies that has consistently done the massive, risky work, anticipating emerging market segments, to  persistently adapt its competitive advantage to continue to dominate the market as it evolves.  During these decades, beginning well before the advent of real AI in 2012, and continuing today, the cultivation of the CUDA centered ecosystem, along with consistent hardware innovation including strategic acquisitions, enabled Nvidia to come to dominate the market  for datacenter GPUs and related high performance computing equipment which is required for AI.

Some general and striking realities about Nvidia’s current competitive position are fairly clear.  There is high demand for AI and accelerated computing capability, and it is not a transient fad.  The use cases are becoming permanent fixtures in the evolving economy. For example, AI is raising productivity of knowledge workers, and widening accessibility to computing applications by making them easier for non-specialists to use.  Accelerated computing makes attainable tasks previously too large to take on. For example, it enables health systems to harness their unstructured clinical or administrative data to yield insights regarding care provision or costs. Virtual digital twin factories can be designed and tested before building the actual plant, avoiding costs of trial and error.

It is clear that the accelerated computing that makes AI possible, largely requires Nvidia products. Specifically, these are the datacenter computer chips needed for accelerated computing, and the technology and software tools needed for the datacenter to efficiently produce (train) and work (inference) with AI models. 

Based on company communications to investors, demand is predicted to persistently outstrips supply.  In view of innumerable essential use cases, the runway and total addressable market is massive.  Nvidia commands at least 80% market share. Most likely revenue and income of the company will climb for some time.

With cyclical companies, there is the concern about avoiding stock purchase at the peak of the cycle. Nvidia stock fell in the macroeconomic perturbations of 2022, among predictions of recession and rising interest rates.  The PE in the quarter ending October 30, 2022 was about 60. It was 50 at the end of the quarter ending in April 2024.  Meanwhile, revenue had climbed more than 4 times, and earnings had grown 20X. 

Therefore it seemed, especially in view of the expectation for continued revenue growth, the stock was not overvalued.  I decided to reallocate some funds from United Health Group (UNH) to Nvidia.  Which I did on February 29th, at a purchase price of $793.16 with 5.4% of my portfolio in Nvidia at the close. The stock has since split 10 to 1.  At some time, it may be that demand for Nvidia data center products will decline. That is not happening soon.  At some point, Nvidia may become involved in a financial mania related to AI. That point has not yet arrived. Should it do so at some point in the future, I might reallocate some funds back to a non-cyclical company, such as United Health Group.