Enrich Your Future 11: Long-Term Outperformance Is Not Always Evidence of Skill

Andrew Stotz 00:01
Andrew, fellow risk takers, this is your worst podcast host, Andrew Stotz from a Stotz Academy, continuing my discussion with Larry swedroe, who for three decades was the head of Research at Buckingham wealth partners. You can learn more about his story in episode 645, Larry's unique because he understands the academic world as well as the practical world of investing. And today we're going to discuss chapter 11 from this recent book, which is called enrich your future. This keys to successful investing. And the chapter title is the demon of chance. And I want to just highlight the quote that you mentioned right at the beginning of it. And this is by Miriam Ben benzman from institutional investor in january 1997 and that is funny that you mentioned this, because I was thinking, how do you find these quotes? But it says people often see order where it doesn't exist, and interpret accidental success to be the result of skill. Larry. Take it away.

Larry Swedroe 01:03
Yeah. So if you could put up this chart from the book Andrew, I'll get started. As you know, we like to use stories and an app that help people understand a complex subject by creating an analogy. And this story is that it's 19, sorry, 2003 January, the start of the year, and an investment committee of a big pension plan of a corporation. They're there to discuss the performance of their plan, choose the managers again, every review performance every year, and they go through a long due diligence process, including looking over a long history. In their case, it's 15 years, and it's come down to these six funds. And here are the returns. And after their discussion, they decide, well, the Larry swedroe Investment Trust has the best returns. You know, we should choose it.

Andrew Stotz 02:10
So maybe, maybe I'll review the returns just for the audience who's can't see it if you're listening, Larry has a list of returns by the ranked by the highest return to the lowest. The highest return, of course, is the Larry swedro Investment Trust at 14.3% average annual returns from 1988 to 2002 the second best is leg Mason value, which is very close at 14.2 then you got Washington Mutual at 12.4 for that same period, fidelity, Magellan at 12.3 for the same period, S, p5, 100 index. Well, you could just put your money in an index and you're going to earn 11.5 and then there's the Janus fund at 11.3 so we've got a ranking. And lo and behold, the Larry swedroe Investment Trust is at the top. Continue. Larry, yeah.

Larry Swedroe 03:00
And what's really interesting here, of course, is leg Mason Valley trust was run by a fellow named Bill Miller, who had set a record. He had done something that had never been done before. He had, although he didn't know it at the time, because the period went through 2005 he beat the S p5 115 years in a row, not cumulative over the period, but every year. And his streak at that time was 11 or 12 years. And yet, the Larry swedro Investment Trust outperformed even legendary investor, Bill Miller. Now the committee says we should do one final review. Let's bring Larry in. Let's say we've checked the returns. They're consistent. Volatility is low. We've looked at all kinds of sharp ratios and volatility measures and looks great, but let's do a final due diligence, and we'll grill him on his investment strategy. And so I walk in and I said, Explain. Well, my strategy is very simple. My wife's name is Mona, and so M is my favorite letter, and I just built a portfolio of all the stocks that began with the letter M, and I value weighted them. Market cap weighted them, and each year I would rebalance the portfolio. So now the question is, do they hire me, Andrew, or not? What do you think?

Andrew Stotz 04:39
I think they may have gotten a little bit startled by your methodology. Yeah,

Larry Swedroe 04:44
this is meant to show the example that you're of that quote that you cited that we often get confused or make the mistake of attributing skill to what could be a purely. Random outcome and just lucky, right? The result of this example is a data mining exercise. It was actually created by dimensional fund advisors at a for a conference I attended, and they just ran all the letters and found that M had the best returns. And so they, you know, created a fund. And I just use that same example. And you know, we have used in our previous calls, an example to show the same thing. It's the coin tossing example we've gone through. So you start out with 10,000 participants in a coin, sorry, 5000 participants in a coin flipping contest, and you say heads wins, and we'll see how many in a row you can get. Well, half of them randomly. You'll get one heads around. Now you got 2500 then 1250, etc. And after 10 rounds, randomly, we should expect 10 to win. Now, would you put any money on those 10 winning the next coin flipping contest? You

Andrew Stotz 06:12
know, it's funny. When I read that in the book, I was just laughing because I never thought about it that way. I always looked at it from the perspective of the past. And asked, Did those people have some sort of skill to get where they were? But to think about, okay, so ready, ladies and gentlemen, it's time to put your money down. Which ones are you going to put it down on? And I think that behavioral bias tells us that people are going to say, Oh, I have to put my money down on those guys that won. But we know there's, there's no, there's no, it's purely random. Well,

Larry Swedroe 06:44
I'll give you another example. It's not in this book, but there's a statistics professor, and he's teaching this class, and he asks everyone to, he's going to leave the room, and he's going to ask everyone to pull out a coin and flip it, and then mark down whether it was heads or tails. Okay, alright. And then he says, I'll come back. You hand it in, and I'm willing to bet. And they're going to have to do this 100 times. And then he is willing to bet he can predict which one is the real coin, because everyone, one person, has a real coin, and the others all have an imaginary coin. So I forgot the setup. So everyone's got an imaginary coin, they're flipping it in their heads, marking it down, and one person has a real coin. How is he able to predict with almost 100% accuracy every year which person had the real coin? Well, what does he look for?

Andrew Stotz 08:01
One, one thing is, you know, you know that there's, there are streaks at times that are random, but, but with a traditional coin, you're going to have very close to, you know, a random outcome that's going to be not contingent upon the prior ones, where, I think the the individuals who are imagining it may be coming up with some patterns and things that would be strange patterns compared to a random coin.

Larry Swedroe 08:28
You're in the right direction. But the answer is, when we flip the imaginary coin, we tend to put t h h t, t, t h o, you know, etc. All he did was look for the longest streak of the same letter. Because, as you noted at the beginning of your comments, there is going to be a streak somewhere. Yep. But when we flip the imaginary coin, we don't come up with a streak of five or six heads or tails in a row. Well,

Andrew Stotz 08:57
it's a good illustration of the difference between statistics and actual outcomes that some people miss. The fact that statistics are to describe the general, you know, behavior of what to expect, but statistics can't tell you the actual outcome is what we get, which will fit in that statistical framework. So it's an important point.

Larry Swedroe 09:22
So the point of this story is we want to avoid data mining, first of all, which is how dimensional came up with that letter M. They just told the computer to find it. We've mentioned, I think, in previous discussions, the David Lean Weber's analysis found the best predictor the S, p5 100 was butter production in Bangladesh, right? But people attribute skill to almost every out coming the champions of the Olympics, the best soccer team is. Likely to win, not necessarily right, the fastest runner is going to win that skill in any sport where we have almost like one on one or a team competition, but as we discuss in investing, the nature of the competition is very different. You're competing against the collective wisdom of the market, and that changes the game. So what we have to think about is, can we look at other examples of winning streaks, and did it tell us anything? Well, I mentioned Bill Miller, that was that famous, like Mason fund. He did something that even what most people consider the greatest mutual fund investor of all time was Peter Lynch, and he did something Lynch never did. He won 15 years in a row, and after that, he did so poorly, he was fired, never I

Andrew Stotz 10:56
remember that going on, and it was just like horrifying seeing him collapse, you know? Yeah,

Larry Swedroe 11:03
and what happened is exactly what you would expect, investors skeptical early. So the Fund had very little money when he had his best returns, then it had massive amount of assets, and then he did poorly. And so most people missed the great at returns and got the lousy returns, and then they dumped them, right? But that's not the only example. My favorite one is a fellow you know, we think of Peter Lynch as the greatest fund investor of all time, and his era was the 70s, but Peter Lynch was not, this is something most people don't know. Was not the number one fund manager in the 70s, his best decade by far, it was a fellow named David Baker who ran a company called or a fund called 44 Wall Street. Have you ever heard of David Baker? Nope. Well, he outlinched Lynch, and yet, in the next decade, the S P went up. Let's see if I could find that number went up almost 18% a year, and David Baker's fund lost 73% of his money, the investor money. How do you do you couldn't do that if you try to be that bad. So there's two great examples, and we have one other in the book that had beat the S P 11 years in a row, from 74 through 84 was the Linda large cap value fund, and over the next 18 years, it underperformed by eight and a half percent a year. You know, we have to be very careful to not attribute skill when we have such huge numbers of professionals trying to outperform just randomly, some are going to succeed, just like randomly the letter M, you have to really be careful.

Andrew Stotz 13:08
So I think you need to help people think this through, because it's a bit of a different, difficult one. I mean, because we're brought up, all of us probably are brought up to tell, be told by our parents, for instance, that the outcomes that you achieve are due to the efforts that you put in. And there is a whole indoctrination that you know has has helped a lot of people to think that that success is not due to luck. Imagine if we went to a young person and we said, Sorry, kid, your outcomes are going to be completely due to luck. It's going to demoralize them. So there's a, there's a moral aspect to it. Why we tell people that you know, your efforts are important? So we come into this world with this frame framework, and you've already explained that, you know, we're competing against an incredible force that is way beyond what we imagine it is, as far as the efficiency of it. But I want to talk about the other side of it. How do we identify skill? And I'm thinking also, we've also talked about how, you know, stock market is one thing, but you know, baseball or other things are not the exact same thing as you're competing against everybody, against this collective but how do we put skill into this whole context?

Larry Swedroe 14:30
Yeah, so again, I think what you have to think about, of course, skill matters in almost everything, but you have to understand the nature of the competition is very different, right? We can watch two tennis players like jokovic and Nadal, they go after us the other day, and you knew with a high degree of certainty that yokovic was going to beat Nadal, where 10 years ago, you could not have made that prediction. They were fair. Are equal, but today, their skill sets are different. The dolls body, you know, he's 38 and it's, you know, no longer able to stand up to that rigors and every sport you don't get to be, for example, a great pianist without practicing 1000s of hours a day, right? The difference here is you're not competing in a game of one on one, like you are against another pianist to see who's the greatest pianist in the world. And statistics here can help, because what we can do is to see what would should we randomly expect with a large database of people trying something called the t statistic, tells us if there's at least a likelihood that this was skill, right? So if you run 20 experiments, one of them will have a 5% chance, just randomly, of being a success, right? So if that tells you, if you run 100 tests and you have a T stat of two, you're meaningless. If you don't have a theory to support why that should work. You come up with this theory first, and then just run one test, and you find the T stat was two. Now you could say, Ah, there's a 95% we're not certain. Okay, that it's skill. If the t stat was three, there's a 99% chance this skill. So the problem today we face is we have such high speed computers and massive databases we didn't have 4050, years ago, that anyone could take the data and come up with the Larry swedroe Investment Trust and whatever the data says is that, but just because you have a correlation doesn't mean this causation. You have to be really careful here to attribute skill and with 10,000 mutual funds out there, randomly, we're going to expect some to outperform for very long periods after. Therefore be very careful before you assume it's skill, and even if it is skill, we've talked about a book I've written called The Incredible Shrinking Alpha. It's getting harder and harder, and this even if you are skillful, like Peter Lynch, we could probably attribute some of his early success to skill, but he was running a very small amount of money when he had the best returns. By the time he retired, he his Alpha was very close to zero. The last few years the market, one had caught up and discovered his secret sources to some degree, like he was a value investor early, and then he got this huge infos, and now he's got big market impact costs and how to diversify to avoid that. Now you can't generate alpha, or it became much harder.

Andrew Stotz 18:15
So it's one of the lessons of this is when you see outperformance, the first thing you should do is attribute it to randomness.

Larry Swedroe 18:25
It depends on the activity. If I'm watching this match, I would if we're

Andrew Stotz 18:31
just talking about the stock market and the performance of fund managers, and we're looking at performance, and we see a list that someone shows us. Hey, these are the guys that outperform. These are the men or women or whatever, that outperform. Should we immediately think, you know, would we be safe to say, Yes, I agree that they outperform, but I'm going to assume that that was from luck.

Larry Swedroe 18:54
Yeah, I wouldn't say it exactly that way, but the first thing you should do is look at what the historical empirical research on the subject is found, and all the empirical research says there's no evidence of persistence of performance by fund managers beyond what we should randomly expect in a normal distribution, you're going to Find some in the left tail that performed very poorly, and maybe that was either high expenses or maybe it was just bad luck. On the other hand, you could have some and you're going to have some in that right tail. Now it might be skill or it might be luck. And if the empirical evidence found bigger fat tails than we should expect randomly, then you could say maybe there's a reasonable chance at skill. And now I have to do more diligence to make sure I can find you know, what is the distinguishing characteristics that is? What's in their secret sauce? Okay, the problem is, there's no evidence in all the studies that I've seen of anything beyond, you know, random outperform, yeah. So

Andrew Stotz 20:12
that was my next question is, after all this years of work, have you it? Can you definitively say that one person or one situation showed a persistence due to skill. Or can you say that there is think

Larry Swedroe 20:27
I think we could say it very clearly, Warren Buffett hats and Charlie Munger had a lot of skill, but they hold the world their secret sauce. And academics did what we could call reverse engineering, fed their computers and say, Hey, can we identify traits of stocks so we could buy an index of stocks that have those same traits, and can we match their performance? And that's what's happened. And Buffett has not been able to outperform for the last 18 years or so.

Andrew Stotz 21:02
Yeah, and you don't even have to telegraph what you're doing. The market will perceive it by reading what your disclosures are, watching market movements, and that's where the efficiency becomes, you know, enormous.

Larry Swedroe 21:15
Yeah, here, you know, we see these great high frequency trading funds. Or let's say, Renaissance technology, and they hire world class scientists, and they pay 10s of millions of dollars to buy the most sophisticated computers and park them, you know, slightly closer to the exchange, so they could get the trading information a millisecond before everybody else. And so now these people go on and they outperform. And then some they say, Well, why should I let the owner of their fund? He's paying me pretty well, but I can leave, I know the secret sauce. And they leave and go start their own fun. And then the secret sauce has a problem, because they're competing in that small, little space to try to extract alpha. So success does breed its own seeds of destruction.

Andrew Stotz 22:10
So one other thing that I wanted to address was that I think there's a lot of people that be pretty upset with what you've said. There's a lot of people out there that are working very hard to build skills, and they see the performance that they've done so far, and they're attributing it to their hard work. And we're not talking about a small number now. Larry, so I want to address the huge volume of participants that believe that their development of their knowledge and their skill and their experiences all coming together to produce something beyond luck. What's going on there? How could they all think that when you've described that, it's a very different situation? Well,

Larry Swedroe 22:55
we know, and we've discussed before, that probably the most common human trait is overconfidence. Tests on that including if you ask people if they're better than average driver, 80 to 90% of them will say, yes. Well, that's impossible. It doesn't matter whether you ask them, Are you a better than average stock picker? They'll say they're, of course, better than it can't be that more than half are better. And you not only have to be better, you have to be a lot better, because you have costs, right? If you're going to play that game. And your competition isn't you or me, even, maybe they're smarter than we are. The competition is Renaissance technology today, that's who they're competing against, world class mathematicians, scientists with a lot more resources than they likely have. What's their advantage that they can identify? So I tell unless you look in the mirror and see Warren Buffett and then even acknowledge that buffet hasn't been able to do it for the last 18 years. The odds are good that your out performance is probably attributed to luck. Doesn't mean you're not smart. We don't want to confuse that issue. You could be highly intelligent, as almost all these mutual fund managers who lose almost certainly are the problem is the competition's too tough and they have expenses.

Andrew Stotz 24:28
I guess. The way I'm thinking about it is like, we've created a monster, you know, like, if you go to a weightlifting competition and all the humans are there and they're hitting some, you know, peak, and then some huge monster comes in and pushes away beyond what any human could ever do, and that's kind of the way I think about it, from the market. So

Larry Swedroe 24:48
let me this point there. The market is a machine that is moving to become more efficient over time. We learn that. That there may be pockets of inefficiency, and the very act of exploiting them moves the prices towards where they should be. So let's say that Andrew Stotz, you know, brilliant mathematician in Thailand, he discovers some anomaly in the Thai mortgage market. So he raises a fund of 100 million bucks, or, you know, a billion dollar whatever, and now he exploits it, and now money comes rushing in, and other people try to reverse engineer, and the Thai mortgage market is very little, and there's just not a lot of alpha there, if everyone's do so what, the way these you know you only way you can keep generate is finding these new sources. So it gets harder and harder, because every day, really smart people are trying to uncover these niches, and just getting harder and harder to outperform.

Andrew Stotz 26:02
Okay, so let's wrap this up by thinking about a young person that wants to apply their brain and their knowledge, and, you know, their understanding and their hard working, and they want to maximize their wealth, and they now understand that, okay, what I'm going to do with the stock market is take the wealth that I'm creating and put it in maybe some sort of index fund type of thing, some factor based exposure, and I'm just going to let that grow, but now I'm going to turn my direction towards creating the wealth that I want to create for my family and my legacy. Where would you say is the best place that they should be competing? Where the odds are. I mean, we've identified where not to compete based upon this discussion, but do you see any places where they should be competing to maximize the value they get for the time and knowledge that they have? Well,

Larry Swedroe 26:52
that's an interesting question. The way I personally would answer it, the objective is not to create the most wealth, but to live a meaningful life. And the answer about what you should pursue, if I told you wanted to get rich, one you've got to be, you know, super, super smart, you know, in the Mensa kind of IQ go to work for some hedge fund Renaissance technology or maybe some biotech firm and invent a cure for cancer or something like that. And you can get rich that way, but there's only a small percentage of the people on the planet who are in that top one or 2% the rest of us should find something that you know, we enjoy, we love. I tell people, oh, we're tired when it feels like I'm going to work. I love what I do, and you should find something that enables you to live a meaningful life and get and enjoy that hopefully it puts enough food on the table for you to live reasonably well as well. Great

Andrew Stotz 28:02
advice. I think part of what can help you to live a meaningful life is to not get caught up in the excitement of the market and understand through our discussions that, you know, there are ways to benefit from the stock market, you know, but you gotta understand these core principles. So I think that's a great thing, and I totally agree about living a meaningful life. I think one of the things that I love is that, you know, every day I get up and do what, what I like to do. And I know I remember the advice that you gave me when I was talking about, you know, what to do with my podcast and other things. And you said, the question is, do you like doing it? And if you like doing it, keep doing it. And so I think that's great advice for all the listeners out there. Find what you love to do, do it. Use the stock market for the benefit that it has, but don't get caught up in thinking that you're going to beat it.

Larry Swedroe 28:53
I think you're much better off spending your time on your passions. And you can't do that if you're spending your time trying to find the next great stock, right? Unless that is your passion. That's your passion, you know, God bless you and good luck. And

Andrew Stotz 29:12
there's still, there's so plenty of careers to build in the world of finance and helping people to be overcome their behavioral biases and understand these core principles and build their wealth, you know, over time. So, yep. Well, exactly, exciting. Well, Larry, I want to thank you for another great discussion. I think that one ended with some meaningful discussion about life. So I'm looking forward to the next chapter, which is chapter 12 out foxing the box. Oh, my goodness, can't wait for that one. For listeners out there who want to keep up with what Larry's doing, it's just relentless. The man is relentless. Find follow on Twitter at Larry swedroe and follow him on LinkedIn. And this is your worst podcast host, Andrew Stotz saying, I'll see you. On the upside and.