In a stock market that has so clearly rewarded risk-takers, it can be easy to justify investing in high-flyers or speculating on potential disruptors. However, the potential for great reward always comes with great risk. That raises the question: How should investors go about making high-risk, high-reward bets in a smart way that may put the odds more in their favor? Make no mistake, a leap of faith is going to be required anytime an investment is predicated on what the company will look like five to 10 years in the future. However, we believe that investors should at least consider three characteristics of a company before deciding to take that leap: (1) funding, (2) demand, and (3) behavior shifts. This is by no means an exhaustive list. Additionally, position size will still be key to managing the risk when it comes to justifiable bets and calculated speculation. With these kinds of plays, we are looking for stocks that have the potential to not only double but perhaps even soar 10x over time. First and foremost, we need to determine whether the company has a chance of funding the vision management has laid out for investors. And, not just any kind of funding. This requires us to think quantitatively by looking at hard numbers . We don’t want companies borrowing to high heaven from lenders that may not be all that prudent with their money. Also, backing from the venture capitalists is not, by itself, a green light because the nature of VC investing requires those firms to know that eight or nine out of their 10 investments are doomed to fail. As Jim Cramer called out in a recent Sunday column , this was a key factor contributing to the bursting of the dot-com bubble that emerged in the late 1990s. At the time, much of the fiber infrastructure buildout was being paid for with debt because the companies in question had no pedigree — and more importantly, no money of their own. So, the first box to check when considering a position in a speculative stock is funding. Show me the money Can the company fund its ambitions internally? If not, what does the customer support look like? How much will it need to borrow, and what are the implications for the balance sheet (in the case of debt financing) or equity dilution (in the case of secondary share offerings)? It’s OK if a company needs to raise capital, but investors must have some sense of how much it needs to raise and then consider the projected financial implications. In the buzzy AI race, the largest tech firms — the so-called hyperscaler cloud companies like Amazon , Microsoft , and Alphabet — are examples of companies that can fund their own ambitions. Their businesses generate more than enough cash internally to pay for their aggressive AI infrastructure investments. This means that, even if the plans don’t live up to expectations, we are at least not looking at potential bankruptcy. Sure, their stocks would get slammed if the companies were to take a write-off on the scale of their AI infrastructure investments. But their existing businesses, the parts that actually make money, would survive with relatively little impact in terms of earnings potential. OpenAI, the creator of ChatGPT, and CoreWeave , the AI data center operator, would be examples of money-losing companies that can’t fund their ambitions with internally generated cash but have deep-pocketed customers with a vested interest in their success. In late September, Nvidia committed $100 billion to help OpenAI build out more AI infrastructure, and more recently, we learned that Meta Platforms was committing to spend up to about $14.2 billion with CoreWeave through 2031. As a result, these companies can take on outside money. OpenAI has yet to raise debt, while CoreWeave has. For CoreWeave, which went public earlier this year, debt financing will weigh on the balance sheet, but growing customer demand and order commitments help to alleviate some of the burden in the eyes of investors. OpenAI is not yet public, but the expectation is that eventually, one day, it will happen. So, if we determine that the financial requirements are attainable without putting the business at risk of taking on too much debt, as is certainly the case today for the hyperscale cloud companies that have been able to fund much of the AI buildout thus far with internally generated cash, we can then begin to think a bit more qualitatively about the opportunity — beyond the hard and fast numbers, the intanglibles. To be sure, a “neocloud” provider like CoreWeave is a riskier bet, but given the clear access to capital the name has, one could make the financial case for speculating. An example of a more mature company that made it simply because of its ability to raise capital would be Tesla . Many on Wall Street were betting against Tesla, but ultimately the company — well, more specifically, CEO Elon Musk — proved so effective at raising capital that it managed to survive and disrupt the auto industry along the way, forcing the industry incumbents to get on the electric vehicle bandwagon (more on that later). Tesla was obviously risky in the decade between its 2010 initial public offering and the Covid-19 pandemic in 2020, but if you were able to make the right determination on whether funding would be there to get the company to profitability, you made a killing. To be sure, in Tesla’s case, that was admittedly more of a qualitative call, rather than a quantitative one, that required a highly favorable view of Musk because he proved uniquely capable of selling investors on his vision. It’s not clear that any other CEO would have been up to the task, given how many were betting against the company at the time. Funding is only part of the equation. After all, you can be looking at the most well-financed company in the world, but if there is no demand for what it offers, there will be no upside. Any takers? The second box moves us more qualitatively. A main qualitative factor to consider is demand — does the company sell a product or service that customers are buying? Put another way, we’re looking for companies that generate revenue. Not all sales are equal, though. We’re in search of high-quality sales, meaning they are growing organically and the company is rushing to meet demand. On the lower-quality side is where we find sales driven by acquisitions, which is considered inorganic growth, and by promotional activity, which can be an effective way to increase consumer adoption but may also cloud the true nature of demand. When it comes to investing in speculative stocks, it’s one thing to speculate on a totally new concept that we don’t even know if people want, in hopes that it will disrupt some existing standard. Examples might include Netflix jumpstarting the premium content on-demand streaming space after its roots in mailing DVDs to customers, or Amazon bringing the concept of cloud computing to the enterprise world. Of course, the payoff can be huge if correct, but the stakes are high and the odds are long. That’s why the success rate of VCs is generally lower than a baseball superstar’s batting average. It’s another thing entirely, however, to take a chance on a company that is already seeing immense demand for its offerings . CoreWeave once again fits the bill, given the shortage of AI compute capacity. Another example would be data analytics software maker Palantir , which was around for roughly 17 years before going public and was already very highly regarded for its work with the U.S. government. The Club has found success in picking a stock that was already seeing strong demand when we first entered the name, but nowhere near what we believed it would be over time. That home run is Nvidia . When we initiated our stake in Nvidia years ago, before Jim’s Charitable Trust came over to CNBC, gaming chips were its top product. However, what really got us excited was the notion that these chips were about more than gaming; they were about accelerated computing for applications such as AI, and we rightly believed that we were only just scratching the surface of demand for accelerated computing. In other words, we took a chance on what at the time was believed to be a high-flyer because it not only checked off box No. 1 — it could fund its ambitions — but because it also already had a strong demand profile, just not to the level we believed it could be over time. Indeed, it’s important to have a view on demand, not only where it stands in the moment but where it can go over time. Nvidia is perhaps the best example of where this thinking paid off, given the applications for accelerated computing go so far beyond the realm of gaming. If you’re a big believer that we’re just scratching the surface on the need for AI computing, companies that provide it would check this second box. Again, Meta Platforms just committed roughly $14 billion to CoreWeave, and that comes after we’ve already seen the social media giant spend aggressively on internal AI development to result in better ad targeting and a more efficient operation overall. In other words, for all the money Meta has already spent, the company still sees a need to send significant additional sums on AI compute capacity. We’ve also heard from more than a few companies that AI agent implementation is leading to increased efficiency gains. It’s not obsoleting the human workforce yet, but we are seeing examples where companies are getting more done with fewer people or not feeling the need to hire as aggressively to support growth. Those kind of demand signals would support the idea that we’re still early innings on AI. Of course, there are still differences when it comes to signs of future demand. Oklo , for example, is a nuclear energy company that has caught the attention of investors, and why wouldn’t it? It’s backed by OpenAI’s Sam Altman. While that, along with interest from the U.S. government, understandably has investors excited about it being a potential key supplier of energy needed to fulfill the demand created from the AI infrastructure buildout, the company doesn’t actually have any current commercial operations. That means it has no sales to speak of, despite sporting a market cap of nearly $21 billion. Investing in a company that still needs to build out facilities and prove itself and its technology is a far different proposition than investing in a company that already has a proven product, generating sales, and now “simply” needs to make continuous improvements and scale. In both cases, success is far from a forgone conclusion. But the differences in their starting place does matter. To be sure, early demand on its own is not enough to speculate on. The reason is that early adopters can result in a head fake. We saw that dynamic take place when the traditional automakers — especially Ford and General Motors — made a strong push into the electric vehicles market to catch up to Tesla, only to see demand lag initial high expectations. The growth rate resulting from early adopters in the U.S. was robust, but we soon learned that the majority of automobile drivers were going to need a bit more convincing before giving up their traditional gas-powered cars, which is also why we saw Ford quickly shift its focus from EVs to plug-in hybrids as demand began to wane following the initial adoption phase. Behavior shifts That brings us to the third box: How much of a shift in consumer/business behavior is really needed for the visions promised to investors to be realized? We have to be careful when extrapolating early demand to future years. We know that new technology brings with it early adopters, and those early adopters, by their nature, are more likely to spend money to try new things than the rest of the total addressable market. So, we need to consider the merits of the technology to determine if demand growth will sustain beyond the early adoption phase. Electric vehicles are a good example of a product where a decent change in consumer behavior is needed for widespread success to be realized. In switching over to an EV, you can’t swing by the gas station you always went to or decide to hit the highway with a quarter tank, knowing that at some point in the next 80 miles or so you’ll likely see a gas station. You now need to plan ahead and figure out not only where the EV charging station is, but also what kind of charger it has because that will dictate how long it will take to charge. At one point, you even had to be sure the chargers would be compatible with your vehicle, though the agreements between companies and charging port adapters have largely addressed that nightmare. Tesla had a first-mover advantage, so it didn’t really need more than the early EV adopters to realize significant expansion — growth is always easier off a small base. However, more recently, as the early adopter market began to saturate and more players came into the space, especially the legacy automakers with significant production capacity, it became more clear that getting consumers to change their behavior and swap out gas-powered vehicles for EVs in mass was no small task. While an investment in Ford or GM for their EV potential may not be that speculative given their legacy gas-powered businesses, the same can not be said for a lot of the EV startups that hit the market during the early years of the Covid pandemic. In the 2020-21 period, we saw investors make somewhat reckless bets chasing the next Tesla, bidding up names like Rivian and Lucid Motors , as well as the stocks of now-bankrupt Fisker and Nikola, to nosebleed levels. Those investors, knowingly or not, misjudged the adoption curve for electric vehicles and opted to bet on companies that had either just released a first product or had yet to release anything at all. On the other hand, the idea that accelerated computing demand would take off didn’t require much of a bet on consumer or enterprise habits changing. The need for more computing power is not new. Generation after generation, we’ve seen more advanced software drive the need for more advanced hardware. So, betting that Nvidia’s accelerated computing hardware would start to see increased demand as existing, non-accelerated solutions started to reach their peak — basically, the end of Moore’s Law, an observation that the number of transistors on a chip doubles roughly every two years — was less about betting on a behavior change. Instead, it was more about betting that the same trend we’ve seen continue for decades would do just that. Here, we might also highlight Club names CrowdStrike and Palo Alto Networks . CrowdStrike, in particular, can certainly be considered a high-flyer because it trades at more than 100 times forward earnings estimates (Palo Alto has a forward multiple just north of 50. Still rich, but not as rich as its cybersecurity rival). CrowdStrike’s valuation may be high, but it certainly meets the criteria we’ve laid out for justifiable high-risk investing as opposed to reckless speculation. First, it is a profitable company with positive cash flow — funding secured. Second, it clearly has demand, as sales have been growing at a rapid clip for years. Finally, when we step back and consider the longer-term demand profile, cybersecurity is always a top priority, especially in a world where data is the new gold and a breach can cost a company everything. That’s only becoming more true as AI agents begin to proliferate throughout the world . These AI tools are being adopted by bad actors who leverage them to conduct more advanced cyber attacks, more often, on an ever-increasing number of attack surfaces, thanks to the more decentralized workforce we have in a post-Covid world. Bottom line In the end, while this is not an end-all, be-all list of things to consider before taking a position in a high-risk/high-reward type of investment, a company that checks off all three boxes, like a CrowdStrike, falls into the justifiable bet category, which we define as a company that makes money but trades at a rich valuation, meaning a high price-to-earnings multiple. These are the kinds of investments we make for the Club portfolio. A stock that checks only two boxes, or maybe just one, might be what we consider calculated speculation, where you’re betting on a profitless company that you expect to eventually make money, based on an optimistic longer-term view of its fundamentals. As those improve, the stock price should follow upward. We typically don’t invest in these types of stocks for the Club, but we would not fault members for taking a chance with money they can afford to lose. Palantir could be considered this type of stock. How about a stock that checks one, or even none, of the boxes? We call that reckless speculation, which we do not condone, and more or less amounts to gambling because you’re effectively betting you can flip the stock at a higher price regardless of any improvement in the underlying fundamentals and profits. That’s where you might find Oklo at this stage of its life. (See here for a full list of the stocks in Jim Cramer’s Charitable Trust, including AMZN, MSFT, META, NVDA, CRWD, PANW.) As a subscriber to the CNBC Investing Club with Jim Cramer, you will receive a trade alert before Jim makes a trade. Jim waits 45 minutes after sending a trade alert before buying or selling a stock in his charitable trust’s portfolio. If Jim has talked about a stock on CNBC TV, he waits 72 hours after issuing the trade alert before executing the trade. THE ABOVE INVESTING CLUB INFORMATION IS SUBJECT TO OUR TERMS AND CONDITIONS AND PRIVACY POLICY , TOGETHER WITH OUR DISCLAIMER . NO FIDUCIARY OBLIGATION OR DUTY EXISTS, OR IS CREATED, BY VIRTUE OF YOUR RECEIPT OF ANY INFORMATION PROVIDED IN CONNECTION WITH THE INVESTING CLUB. NO SPECIFIC OUTCOME OR PROFIT IS GUARANTEED.
