Ken Fisher Talks Recession Probability, Stock Fundamentals, AI Research and More.

Transcript

Ken Fisher:

Let me just say to you that stocks tend to rise. Three out of four time periods. So, if you spend more of your time looking for when stocks are going to fall than you do for when stocks are going to rise, you're betting on the wrong side of the odds. So, every month I get these questions that somebody sends me in from here, there and wherever. And I type them up on a little card so the print is big enough that I can read them in front of you, and I rattle off short answers to them. Sometimes. It's hard for me to give you short answers, I'm pretty windy.

So, does the strong Q3 US GDP report mean tariffs' economic impact is less than feared? Should investors be bullish on the US economy in 2026?

Now, those are a couple of two questions, not one, and they're interestingly phrased. Let's take the first of the two and treat it separately than the second one: "Does the strong Q3 US GDP report mean tariffs' economic impact is less than feared?" Well, the first question you say is feared by who. What I've said from the beginning, and remain hewn to, is that tariffs are bad, they're always bad. And they're worse for the country that imposes them than for countries that are imposed upon. And the reason for that is because the imposition is a two-party system, whereas the ones that are imposed upon have the whole rest of the world they can trade with. And that world is three times as big as the imposer, or more, if you have the biggest imposer in the world, the United States of America, which is the case in this instance. Now, as I also have said and wrote about in early 2025, that US capability to collect the tariffs successfully in a world where there's many ways to dodge or eliminate the tariffs, the collection capability is less than most people believe it to be. It's not as easy as, a tariff rate is announced, and that's what you will get based on the amount of stuff that comes into the country. Approximately, since Liberation Day—and of course, tariff rates have jockeyed around, bouncing around like ping pong balls a little bit since then— tariffs have been collected at about half the sticker rate. The tariff collection is about half of what it was that originally President Trump said we would be collecting from these tariffs where he was assuming a straight line, mostly of, this is what's coming into America, and this is the rate, so this is what we'll get. That's actually a higher collection rate than I would have expected by about a factor of two. I would have expected it to be about 25%, not 50%. But be that as it may, it's also important to remember that this is on manufactured goods, and the service economy is three times the size of the of that. And so therefore, it's not the biggest factor in the world. It's one of the reasons why the economy can do okay, even though it might do better if the tariffs weren't there— because it's a bad, but it's not a bad enough bad to throw the economy into a cocked hat. And then, the way you frame the question, there's this other wild card, because Q3 GDP report runs into the period of government shutdown. Now, first I'm going to say to you, as I always say, GDP numbers aren't that precisely accurate, even though they're presented as precise numbers. It's just not a very accurate measuring system. Secondarily, the government shutdowns skewed things, so you don't really know what that number really reflects. It'll get revised several more times, as they all do, and we don't know how big those revisions will be. And then, when you get through with the final revision, it's still, as I said a few moments ago, not a perfectly accurate reflection of what happened. GDP is a government calculation about a thing that it can't measure precisely, even though it's presented as precise numbers. So, that covers the first of the two questions. See, I didn't answer that quickly. I'm supposed to do these fast. I can't do that. These are questions that deserve actually more than a fast answer. So then, the next one has a similar conundrum to it.

Should investors be bullish on the US economy in 2026?

Generally, yes. But relative to what? What I would say about the US economy is we're doing just fine. On the other hand, compared to expectations in 2026, it probably will not do as well compared to current expectations as Europe will do—where expectations are very low and it will, and Europe will do, better than those very low expectations, or emerging markets. So the answer is, yeah, the US economy will be okay, it'll do fine. But compared to expectations, it will not do so terribly well.

What is the probability of serious recession in 2026?

Low. Why? Well, first, you will always get the stock market falling for months before you get a recession start. The stock market is the best leading indicator of recession. And since we just hit in early 2026 new all-time highs in the market, you know that you're not getting recession starting at all until, at the earliest, of spring. Secondarily, and I've written about this a lot in 2025, globally—in America, outside of America—globally, lending has been increasing at an increasing rate and robust from about 18 months ago when it was lower. Loan growth is fuel for economic growth because there's almost nobody that's borrowing money that doesn't intend to use it. You don't borrow money that you don't intend to use. You borrow money shortly before you're going to use it. So that loan growth is a reflection of supply availability, but also demand for that money that will get utilized. Now, let me say that, is it possible to have a recession? Yes, but you said what's the probability of serious recession? That's the question. Probability is low because the lending environment is good. Lending is going strongly. It's one of the most important indicators to watch for looking ahead. Economists are too dour. Economists expectations are all focused on global trade, and they miss the point that the global world outside of America can actually trade pretty freely among themselves. And they, the economists, tend to be too much fixated on global trade between us and the non-US world.

Regarding your recent video on corporate earnings, if we don't look at earnings reports, what should we focus on?

So let me just say one word and then let me make 15 points. One word is you should focus on the fundamentals. How might you do that. The 15 points now. Now, giving a tip of the hat, despite the fact I'm not wearing a hat, to my father. In 1958, my father wrote a legendary book called Common Stocks and Uncommon Profits, which is outdated in its writing style. But the fundamental points that it makes are as valid today as the day that my father wrote that book. In Common Stocks and Uncommon Profits, he—and I'm not hawking the book at you here, I got an easy way for you to do this— but in Common Stocks and Uncommon Profits, he made 15 points of what to look for in a stock in fundamentals. And you don't have to buy the book, you don't have to go to the library— all you got to do is go and look up the internet. And go to some standard AI source, like Grok or Perplexity or something, and put in, "what were the 15 points Philip Fisher wrote about in his book, Common Stocks and Uncommon Profits?" You don't have to do anything more than that, and it'll take you right to them. And when you do that, they'll cover the waterfront, from the gross profitability of the company, market size potential for the company, research expenditures, whether the management is open and willing to discuss its shortcomings as well as its strengths—there's 15 of them. Just look it up on AI. That's what you look for.

Why have I heard you called "a perma-bull"? Is that accurate?

Well, there's lots of reasons that I'm called a perma-bull. Perma-bull is implied in a negative context. Perma-bull is stated by people who think the key to life is figuring out when the market's going to fall. Let me just say to you that stocks tend to rise three out of four time periods. So, if you spend more of your time looking for when stocks are going to fall than you do for when stocks are going to rise, you're betting on the wrong side of the odds. People have a hard time with that. They treat it like it's a 50/50 proposition. Tomorrow, it's not 50/50. Tomorrow, I don't know what will happen, but when we look out over periods, most of the time stock drives. The only time, and I've said this routinely, that's worth getting out of the market for, is if you have an ability to foresee or see early in a bear market that it is a bear market, and then it's worth sidestepping the bear market. It is hard to do that. I've done that a few times in my life. I'm not actually a perma-bull, but I have not done that, now, for a long darn time. I missed the last big bear market, which was 2007, 08', 09', and I don't really consider 2020 and 2022 bear markets worthy of focusing on very much because they're both so short and didn't do very much. 22' didn't have a recession with it, and it wasn't very long, and 2020's bear market, associated with the outbreak of Covid, was exceptionally short. So, is it accurate that I'm a perma-bull? Not really. But mostly, I'm biased. You got to have a good reason to be bearish; you don't have to have a good reason to be bullish. The thing that makes a good reason to be bearish, is seeing something that's big and bad, and able to create recession, that others haven't already been talking about, and therefore, isn't priced into stocks. And that's hard to do. I'm always looking for it, but I'm human and I'm not all that great at doing it. And if you can't do that, then tried to call a bear market or a correction, or anything else based on other stuff, is foolish.

Isn't the talk of AI today very similar to the dot-com bubble in the 1990s?

No, they are very dissimilar. I've written a fair amount about this. I understand why a lot of people who are wrong think they're similar. Why? Two basic reasons. Valuations are high, one. And two, it's Tech led. AI is Tech and valuations are high. Those are the two. Oh I guess there's a third. They both have expectations about good things that this technology will deliver ahead, as the 1990s did for the Internet and as AI does today. So, you know, we could go one, two, three, if you want. Why are they very different? Well, the dot-com bubble was a bubble. And I wrote about that bubble. the dot-com bubble had hundreds of companies that were losing money, that had no gross operating profit margin, that were dependent entirely on their survival being based on future cash raises through stock offerings. The companies—not all, but most of what goes on in AI today are huge companies with huge gross operating profit margins that are funding their AI efforts out of their huge growing profitability, profits in hand, their own cash flow, not based on selling stock. That, in the late 90s, was a bubble because it was all 100% fundamentally dependent on the companies that were doing it being able to continue raising money through stock sales. This one is not a bubble because there's no financial market requirement for the companies to be able to continue doing the activity in which they're engaged. Now, let me say differently, just to go off to a different direction briefly. That is not to say that the AI stocks can't fall, that the stocks that are involved in AI can't fall. Yes, they can. Rising and falling, normal bear markets, stocks sometimes being overpriced. None of that's about a bubble. That's just normal stuff. We've had bear markets forever without having had bubbles. We've had categories of stocks fall forever without having had bubbles. It is a mistake to confuse the normal process that Sir John Templeton famously called the evolution of a bull market of bull markets being born on pessimism, grow on skepticism, mature on optimism, and die on euphoria. It's a mistake to confuse optimism and euphoria. Or the euphoria of the peak of a normal bull market with the different form of euphoria. That's a bubble, which is a dependency on stocks going higher to finance fundamental business activities.

Can investors gain an edge by leveraging AI for research?

Well, it depends how you want to view that. If you say, can you do better by doing research via AI? Standard AI sources. Asking questions and getting answers, then by going and doing it otherwise, the answer is absolutely yes. If you're looking for what would be the consensus answer you would get if you went into a kind of a library and studied it for a long time, instead of using AI to come to the same conclusion, because AI can just do that so much faster. AI, however, cannot give you something. I mean, it's a phenomenal timesaver for that kind of answer to that kind of question. What AI does not do is gives you any creativity. Truly. It does not allow you to create new stuff because it's all a pre-programmed algorithm and because it's all a pre-programmed algorithm, it can't do the kind of creativity that does never yet done greatnesses for humanity, which is where most of the great world changing things come from. So, the answer is yes, it's a great efficiency enhancer, and if you use it and others aren't using it, you gain relative efficiency to them. That's good. But in terms of game changing stuff, it's not so good.

Thank you much, hope you found this grab bag month useful. Send in more questions for next month and I'll do my best to answer them. Although, even though I'm supposed to answer them quickly, I never seem to be able to.

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