Original Value vs Expected Mean Reversion

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In this week’s episode of the VALUE: After Hours Podcast, Taylor, Brewster, and Carlisle discussed Original Value vs Expected Mean Reversion. Here’s an excerpt from the episode:

Jake: One approach is what we might call original value, which is really like, I’m understanding the company’s history looking backwards, I know everything about it, I have to assume that the future will look something similar to what the past looked like, and that there’s then an expectation of reversion to the mean of, what the business is going to do, what the multiples that the market was willing to pay for the business, all these things are going to revert back to the mean. That’s really the bet that old school value has been making for 100 years. You think about Buffett with Amex, and the salad oil scandal. That was a temporary problem, the reversion of the mean of a good business he was expecting, and he did really well with that.

The other approach, potentially, that you might call newer value, would be taking advantage of rapid and widespread disruption and changes, and focusing then more potentially on TAMs, focusing more on network effects, growth rates, and really more ignoring the past, because you don’t think it’s a good prologue for what the future is going to look like, really ignoring the base rates and reversion to the mean and really focusing more than on the future and optionality that these businesses might create.

I think both of them have their season, and understanding what is maybe the next to come, might tell you which way to lean, whether more towards old reversion of the mean, or more towards traditional value– towards the newer value, optionality. One way to reframe this conversation is to talk about explore versus exploit. I think we’ve talked about this on the show before, but it’s really interesting to see actually, ants, through the use of their little simple minds, the way that they’re programmed their brains and pheromones, they’re able to mathematically solve problems to do this explore versus exploit trade off. What researchers have found is that they actually will tune the amount of exploration versus exploitation based on the rate of change within the environment. The more change there is in the environment, the more the ants evolve towards more exploration, because that is what is rewarded. But the more static the environment, the more the ants fall back towards exploitation.

Toby: How are they making that determination?

Jake: It evolves from the very simple, just machinery inside of the little algorithm in their little ant brains that has just a few yes, no, on or off type of synapses that will then emerge into this very intelligent behavior.

Toby: What are the criteria on which they’re making those decisions? Maybe I could use them in my investment strategy.

Bill: I like to see IPO valuation.


Jake: Right. I don’t know if I have a good answer for that. I’m going to punt on that one. But I’m going to keep going instead and following my own agenda.


Jake: The more the change there is, the more that they do exploration. The more static, the more exploitation. Well, I think what’s really interesting about this is that if we have to remember that in markets, it’s horse race betting. What is the mispriced bet? It’s not just what is likely to happen, but if everybody knows that’s what’s likely to happen, the pricing can get messed up there. I think it’s probably reasonable to say that 10 years ago, people sort of assumed too much reversion to the mean, especially if you were a value investor. These businesses grew in ways that we never really would have predicted. There were lots of places where reversion in the mean was just dead for the last 10 years.

Toby: Would you say it’s as long as 10, I’d say just even 6?

Jake: All right. I mean, perhaps that’s–[crosstalk]

Toby: 2015. Let’s come back to this in a moment, but I think 2015 is the date.

Jake: When it sort of changed?

Toby: Yeah, when it split.

Jake: We have the actual rate of change, that ended up occurring versus what was sort of, we expected. I think that there was an error made often by a lot of value investors, probably me included. The other part of that too is the skewness of the distribution. If you have a very fat tail, especially on the right tail, a right tail skew, the outcomes can be so big that you can underappreciate what they would look like. It’s not even just the probability, but also times the magnitude, which is captured by the skewness of the tails. With that said then, today now, let us try to think about… what optionality for the next 10 years appropriately priced, or have we all sniff this out now, and people are potentially overpaying for that optionality. Perhaps if the next 10 years are not as different, then the right bet to make is the back to the reversion of the mean, the old school expectations, looking backwards more, and not so much looking forward as where to focus your efforts.

That then brings us to looking at things like Carlota Perez’s innovation and diffusion, and technological revolutions. They have this explosion phase, and then typically an installation, and then it becomes a utility, and then there’s something else that comes along and disrupts it. Where are we on that? This also gets into arguments about, take Ray Kurzweil’s asymptotic approaching of just this runaway–

Toby: The singularity.

Jake: Yeah, the singularity and these nonlinear exponential technologies, versus Peter Thiel holding up an iPhone and saying, “This is not the equivalent of putting a man on the moon, and maybe that we’re not as advanced as far as maybe some of us think in certain realms.” I don’t have a ton of answers.

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