The recent explosion of interest in artificial intelligence (AI) has turned the sector into one of the hottest tickets on Wall Street. From autonomous vehicles to data analytics, the applications of AI are virtually limitless, and so it seems are the investment opportunities.
This atmosphere of excitement and innovation has generated not just hype but also a palpable sense of FOMO—the Fear of Missing Out—among investors. There’s a rush to identify the next big AI stock, a “ten-bagger” that could potentially offer exponential returns.
However, it’s essential to remember that high conviction for a particular stock doesn’t automatically translate into good fundamentals or stellar growth prospects. The market is full of tales of seemingly ‘can’t-miss’ companies that eventually fizzled out, and the rapidly evolving landscape of AI makes it an especially tricky field for predictions.
So, here’s the good news: making decent returns in the world of AI doesn’t necessarily hinge on picking that one golden stock. Diversification can still work to your advantage. Here’s why putting all your AI eggs in one basket might not be the wisest strategy.
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Ever hear of idiosyncratic risk?
In the world of finance, “idiosyncratic risk” refers to the risk inherent to a specific asset, like an individual stock. In simpler terms, it’s the risk you take when you put all your eggs in one basket – like betting heavily on a single AI stock, for example.
Here’s the kicker: investors are not compensated for idiosyncratic risk. Why? Because it’s a risk that can be easily diversified away. You stand to gain nothing for taking it on, but stand to lose everything. It’s a terrible bet to take in terms of risk/reward.
Let’s say you invest heavily in a hypothetical company called “FutureMind AI,” which specializes in AI-powered healthcare solutions. A regulatory hurdle suddenly emerges, delaying one of FutureMind’s most anticipated products. The stock plummets, and because you were so heavily invested in this single company, your portfolio takes a massive hit.
So, in AI investing, instead of putting a disproportionate amount of your capital into one “can’t-miss” stock, you can reduce idiosyncratic risk by diversifying across several AI companies. That way, you’re not leaving your portfolio exposed to the unique risks that any one company might face.
It’s probably priced in anyways
The stock market is perhaps the closest thing we have to a financial “hive mind,” reflecting the judgments, expectations, and actions of millions of investors worldwide. Among these market participants are some of the most brilliant minds, such as MIT quants who have decided to forgo a career in theoretical physics just to arbitrage a single cent of profit on something as mundane as soybean futures.
This collective intelligence ensures that the market is efficient at incorporating information. When we say that something is “priced in,” we mean that all known information – whether it’s a forthcoming product launch or an anticipated earnings report – is already reflected in the stock’s current price.
In other words, you’re not really getting a “deal” based on your own research or intuition. If the company does roll out a game-changing AI technology, the stock might not soar as you expect, simply because the market had already anticipated this success.
For instance, if you’re banking on a particular AI stock to skyrocket after an eagerly awaited product launch, you may find that the stock barely moves, or worse, falls. This drop can happen because the market had already accounted for the success of the product; what it didn’t account for was any number of unforeseen factors – a software glitch or a lukewarm user reception – that could affect the stock’s value.
What I would do instead
Staking your financial future on a single AI stock is akin to buying a lottery ticket. While it’s tempting to chase the allure of exponential gains, the reality is that this approach offers a poor risk-adjusted return. The chances of disappointment far outweigh the likelihood of striking it rich, especially when you consider the market’s efficiency in pricing in information and the idiosyncratic risks involved.
Instead of trying to pick the lone AI superstar, a smarter strategy would be to invest in industries that are closely linked to the AI ecosystem. These are the sectors providing the essential hardware and software that AI companies rely on to function and innovate.
Two ETFs I like here are Horizons Big Data & Hardware Index ETF (TSX:HBGD) and Horizons Global Semiconductor Index ETF (TSX:CHPS). They can be a great way to add an AI-themed tilt to an already diversified portfolio of Canadian stocks (and if you need some ideas for those, the Fool has some suggestions below!)
