In their recent episode of the VALUE: After Hours Podcast, Taylor, Brewster, and Carlisle discussed Popular Factors Underperform. Here’s an excerpt from the episode:
Jake: The forward PE has been the number one model for 14 years in a row as of 2019. By the way, it’s underperformed by 46% over the last nine years. So, everyone’s using the same model, and then, therefore negating themselves out, and it’s not working.
Tobias: Say that again. The forward PE has been the most popular model, but it’s also been– or it hasn’t performed very well?
Jake: Right. Exactly. Perhaps, probably because everyone has been using it as their number one factor. They have tons of different factors in here like earnings surprise, dividend yield, beta, size, return on equity, PEG ratio, relative strength, all these different– machine learning all this other stuff. Since 1991, earnings revision as one of the factors has been underperforming by 1.4% per annum, when years, it’s in heavy usage by everybody.
Jake: But the time when it’s not in heavy usage, it’s plus 4% per annum. The average model in 2019, they used 18 factors, whereas in the early 90s, it was 7 or 8. John Maynard Keynes actually described this problem a hundred years ago, when he talked about this beauty contest, where you are trying to come up with what you think the average person is going to guess is what they would say is, what they would pick for the for a beauty contest. Then, you start to think like, it becomes recursive where each layer down, you’re thinking, “Well, what’s the average person thinking that the average person is going to think that they’re going to pick for the beauty contest?” It becomes a total mind scrambler to try to–
Really, all they’re trying to figure out is, it’s really a very complicated form of greater full theory, like, is someone going to pay me more later compared to– am I using the factor that’s going to be the one that’s the winner who’s going to allow me to pick over this time period the thing that someone’s going to pay me more for? What do you guys think of the El Farol problem to start?
Tobias: Yes, that’s a good summation of it. You’re not trying to come up with a valuation. You’re trying to pick which ratio best predicts the next 12 months.
Jake: That’s probably accurate, I would say. It might be generous to say 12 months, but [laughs] are we measuring quarters or days?
Tobias: Quarterly, yeah.
Jake: I don’t know. [crosstalk]
Tobias: It’s going to be noisy, because– I don’t want to say confounding factor, but the thing that influences what other people are doing like, did cheap stocks on a PE basis all of a sudden become popular in which case there are fewer of those, because everybody’s trying to buy the cheap stocks. If your approach was to try and figure out which one best predicts where the underlying business will be in x period of time, do you still run into the same problem? Probably, possibly. You still get booms and busts in that scenario, right?
Jake: Well, it always goes back to what is everyone else imagining, and are they bidding that factor up to a level where there’s nothing left for you except maybe even under performance? You don’t know what everyone else is doing a priori. It’s almost as if this would be telling you that all of the [chuckles] machinations of trying to figure out where the hell this thing is going, and what’s going to work is perhaps wasted CPU cycles.
Tobias: Yeah, so what’s the solution? What’s the answer?
Bill: Wait, I’ve got two quick thoughts. Ken Fisher, even though you’re not allowed to speak his name, he who shall not be named, he used to do this when he would do his market predictions. He always would admit that he’s cheating but what he would do in order to come up with it is, he would look at what everybody else has predicted after the big money poll has closed, and he was like, “All right, that’s what’s priced in. So, that’s what’s not going to happen.”
Then, he picks the slices outside of that, which I thought was interesting. Then, the other thought that I had was, I just think forward PEs hasn’t worked, because there’s a very real possibility that we are in the middle of a huge global asset grab for the next layer of basically internet infrastructure.
There’s really rational reasons to reward people that are spending a ton of money if that thesis is correct and their businesses are sticky. They would have more losses right now, because gap requires it. It makes sense to me. Now, whether or not that assumption is correct is debatable, but I can at least understand it.
Tobias: Ken’s dad, Phil, who wrote the book, Common Stocks and Uncommon Profits. There’s a similar story in the start of one of his books, but it’s not looking at where the big money goes. It’s just one of those competitions, and I think the prize was a color TV or something. Back when, that was a big deal.
Tobias: [chuckles] They just got everybody’s prediction for where the stock market would close the next day, and everybody predicted plus 0.5%, plus 1%, minus 0.5%, minus 1%, and then, he just picked plus 3%. Of course, that turned out to be the right thing, and he won the TV. The prediction was not on the basis of that’s what he thought was going to happen.
He just knew that he’d be the only one out there predicting that it was just a wild move one side or the other, and everybody would forget the correct answer in the years to come unless it was of a wildly divergent answer. So, that was why he picked it. He was pretty smart. So, he is playing the game more than he’s trying to figure out what’s happening.
Jake: Yeah. I think that Bill gave us probably the correct answer earlier, when he named an individual security and situation that he thought made sense to him, and-
Bill: Just makes me happy. [laughs]
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