What Do You Believe That is Actually False? | The Only Three Questions That Still Count

Transcript

Ken Fisher:

So used to, I would every month take a chapter out of my book Debunkery and explain how some myth was actually false. They believed it so, about investing, but it isn't. Now, that leads to a perfectly obvious phenomenon, which is that if you already knew it wasn't true, you wouldn't believe in the first darn place, right? I mean, it's not like you're an idiot or something. But, if you think about having written a book predicated on common beliefs, that Debunkery book that I've done chapters out of for a couple of years, once a month, maybe longer. There got to be a lot of things that people believe are true, that you can demonstrably prove are false, which is what that book was all predicated on. And going back to my prior point, if you already had known it was false, you wouldn't believe it. Why do people believe things are true that are demonstrably false? And the answer to that is that an awful lot of investing in conventional wisdom was created over time periods where data was very scarce, hard to put together. If you go back to the time that I'm young and first coming into the business, you're just starting to get the world where many computers are becoming prevalent on a wide basis. Microcomputers, not yet. And in that world, and this is what I do in college, you know, you worked with a slide rule because we didn't yet have electronic calculators. I'm an adult working in the world when we first have electronic calculators. Where you had to get anything done on a computer, where you took your things to somebody, and they were in punch cards, and the punch cards were put into a mainframe computer. It was a lot of work to do any kind of statistical work.

Fact of the matter is, nowadays statistical work is easy. You can do statistical work today without even understanding statistics at all. Although, I encourage anybody to take a class in statistics. It's you know,  those statistics class for non-statistics majors in college are actually very very good for getting you to see the world better. But that's not my point in this talk. My point in this talk is that when I was young, I would hear somebody say something and I would say, that's not right. And then I would go and put my effort into trying to prove that I was right and they were wrong. And that's a normal human thing to do. And it took me a good long time to realize that I was wrong in doing that. What I should really do is try to focus on what I think is true, and see if it's actually false. Things that I believe are true and that you believe are true, and that we mostly all believe are true, that are actually false, you can bet against. If everybody believes X causes Y, but it doesn't, and then you see X happening, you can rely on the fact they'll be betting on Y and you can bet against Y. Now, some of the time when that happens, X happens and Y will occur, but X doesn't cause Y. We prove that. I'll come back to that in a moment. But if X doesn't cause Y and most of the time you don't get Y from X happening and you bet against it, most of the time you win. The fact is, people are so used to not checking as to what their beliefs are being wrong, that common and widely held beliefs are commonly wrong. That's what that Debunkery book was about. A whole long list of them. Now, in my only three questions book, The Only Three Questions That Count. The first one.

The first question is what do you believe that's actually false? And what do you believe It's actually false is about the most important question you can possibly ask, because it gives you self-improvement over time. And you say to yourself, "Well, I believe this is true, but can I actually prove that it's wrong?" And if you take things that most people believe and you challenge them statistically, you say to yourself things like, well, so take a concept like correlations. You may not know what correlations are, but what correlations measure is just simply how commonly do things wiggle together. This happens and that happens with it. How tightly do they move together? Now, wiggling together doesn't necessarily mean that X causes Y. The two things. But if they don't wiggle together, it means X does not cause Y, and Y does not cause X. So, if everyone believes X causes Y and you can actually demonstrate they don't wiggle together, then you got something. Going back to my point that you can bet against the common belief and most of the time you'll win. So, you don't have to actually know the math that I learned when I was a kid to do correlations today, because if you go to some place like Yahoo Finance, you know, they got the ability to enter on a spreadsheet and it'll do the math for you. All you got to do is tell it what you want it to do. And I encourage you, for something as simple as correlations, to test every darn thing you know. And increasingly, what I know is that I keep having things I believe that I haven't tested, but the more you test, the more you find. Because if you believe it, then the next thing you want to do is say, do other people believe it too? And if you believe it and other people believe it, and you can prove it false, you got something? This is such a simple concept that most people won't do it. And most of you that see this video won't do it. So, for example, and in the beginning of the book, I go into showing you the history.

It shows that the common belief that's overwhelming in investors that high price-earnings ratios are riskier than low price-earnings ratios, is measurably false, because we have a very long history of good stock data that you can run a test on. And when you run the test on it over one, three and five year periods, you see that price-earnings ratios are not predictive of anything any way you calculate them. And then people will come back to me and say, "But what about the Cape-Shiller PE that shows that ten-year returns after high PE markets are below average? And my point would be, it is a perfect example of trying to maintain a myth. It is an example of coming up with a convoluted formula over an extended time period, to show something that doesn't hold up if you don't have the convoluted time period. And doesn't hold up if instead of ten years, you look at one, three, and five years. And that math is all doable. And the fact is that people won't check and work so hard to prove that their belief, because it feels right, that high PE should be riskier than low PE. People don't get that PE is one of the most known things in the world and PEs are priced. The market's already figured the risk out when it categorizes the PE. So, you can go through so many things that are like that. Like my party's good for the— my political party is good for the stock market. Your political party is bad for the stock market. Or long-term interest rates tell you what will happen to stocks or the reverse. Stocks will tell you what's going to happen to long-term interest rates. Or short-term rates will tell you what will happen to long-term rates. Or and again, I'm not going to belabor your time with it, because that's what that whole book that I was doing month after month after month, Debunkery, was full of. As goes the first month, so goes the year, etc. I mean, I can't even rattle off all of those in that book. But in my only three questions book, one third of the book is about taking you through processes of showing you how to discern and the importance of discerning that what you believe and other people believe that's actually false, which is much more common than you think, is something you can bet against. Now, you know the second question is important is what can you fathom others can't fathom? It is a much tougher one to do, and I'm not going to go into this today. It's the second part of the book, and it's really about how do you see not whether X causes Y or not, but that P causes Q when nobody has a clue what causes Q. Now that one is much more valuable, because when you can do that now, you actually can bet on something with consistency. The what do I believe that's actually false, that wins kind of two-thirds of the time.

The other one wins like 90% of the time. And then the third one that feeds back to the first two is what is my brain doing right now to blindside me. And humans are actually inherently blindsided by prior bias and by our inability to correctly recognize information when it's presented to us in certain frameworks. So, I'm just telling you all this because the most important thing that you can actually do, in doing well in investing, is to better understand who you are, to better understand what you know that's false, to better understand who you are that can figure out something that other people haven't figured. And to better understand how to not let your brain screw you over. And your brain is your biggest enemy when it comes to making investing mistakes. So, thank you very much for listening to me.