Warren Buffett is a legendary investor, and he’s got a few tips we could all learn from. So what if I were starting (or re-starting) an investment journey from basically nothing? Many of us go through this during life after buying a house or another expensive purchase. What could I learn from Buffett?
Sensible choices
When we’re starting with nothing, it can be tempting to go for broke, put what little money I have in some highly volatile stock and hope for the best.
But that’s exactly the opposite of what Buffett tells us to do. He wants us to make sensible choices. And, here, the first sensible choice would be to set up an automatic contribution for my investment account.
Whether it’s £100 a month or £1,000. I’ve got to go with whatever I can afford.
Moving forward, Buffett tells us to invest in companies that are trading at a discount to their intrinsic value. Whether we’re relying on someone else’s research or doing our own, it’s important to understand what we think a company’s worth.
I say this a lot, but I start my research by looking at the price-to-earnings-to-growth (PEG) ratio. The combination of expected earnings and share value has worked well for me.
The so-called ‘Oracle of Omaha’ also tells us to invest in companies with a competitive advantage. For example, he’s long been an investor in Apple, with $170bn in holdings.
Apple isn’t an investor favourite right now, but there are a host of other companies with attractive valuations and a competitive advantage. Just take AI-enabler Super Micro Computer.
Nvidia
Buffett doesn’t have much exposure to AI, but it doesn’t mean I can’t use his teachings and adapt them. So while I could talk about Super Micro, I want to explain why I think Nvidia (NASDAQ:NVDA) would meet Buffett’s broad criteria and could be a sensible place to start researching an investment journey.
Nvidia is the ultimate AI enabler. The company’s graphics processing units (GPUs), originally designed for things like gaming, possess parallel processing capabilities that are ideally suited for AI workloads.
What does this mean? Essentially, Nvidia provides the computer processing power needed for AI to work. Understandably, AI, machine learning etc, requires vast amounts of processing power, and other companies don’t offer chipsets with anywhere near as much power.
There’s a bit of back and forward between analysts right now. Some warn that other companies will catch Nvidia in terms of their offer. Others say Nvidia is just too far ahead, and the firm now has huge cash reserves to continue developing its products.
I agree with the latter. Nvidia has already built on the H100 — the original in-demand AI chipset — with the H200. It offers 1.4 times more memory bandwidth and 1.8 times more memory capacity than its predecessor. I’m sure more’s coming.
Its PEG ratio is 1.3, which puts it at the lower end of the Magnificent Seven tech stocks, and I’m also aware that analysts have vastly underestimated Nvidia’s earnings in recent quarters. It could outperform once again.
