Why Do Fundamentals and Prices Converge?

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Contact: giulianomana@0to1stockmarket.com

Article

I must admit that it was not my intention to write about this topic in today’s article. For the past month, I’ve been going over François Rochon’s shareholder letters, and the plan was to cover his investment philosophy. After writing it for a large part of my Saturday, I decided to stop and postpone the write-up for next Sunday, if possible.

In contrast to the previous articles I wrote in that line (with Terry Smith, Warren and Nicholas Sleep), I’ll try to make this one as comprehensive as possible. I want it to become something we can turn to in 1-2-5-10 years and for it to still be valid. Hence, I need to dedicate time to it. I think it will be a 10-15 pages write-up. Hope you enjoy it.

Turning to what brings us here, as usual, there is a topic that has been bothering me ever since I started reading about investing. When I joined this world in 2020-21, I was mostly a passive reader on Twitter. Within it, there was a chart that people continuously shared with, in hindsight, little to no reasoning behind it.

This was my first encounter with the concept. It was allegedly an absolute truth I should take for granted, and I did, for a while. As reads went by, the phenomenon was recurrently mentioned, by everyone, ranging from the greatest investors of all time to Fintwit contributors. However, it was apparent to me that the sole fact of these things occurring only reveals correlation, not causality. Three years of reading and exposing myself to a wide array of investors and I have yet never found someone to bridge this gap.

Perhaps correlation is all most people need, but after diving into Clayton Christensen’s thinking process, the causality factor has become very relevant for my approach to topics. Ultimately, I don’t have the answer. Claiming such a thing would be under-appreciating the infinite elements involved in the process. Nevertheless, I’ll share below what I suspect.

My questions are not only why fundamentals and prices converge over the long run, but why don’t they follow the same pattern in the short term.

The Wisdom of Crowds

The wisdom of crowds is an interesting phenomenon that was especially researched in the 2000s. Fundamentally, it essentially states that, on average, crowds are much wiser than the individuals that compose the crowd. I lack reading on this vertical to exhaustively expand, but the wisdom of crowds is something that works only when some conditions are met:

• Cognitive diversity

• There must be a mechanism that aggregates individual inputs

• Incentives must be placed so that people try to make the right decision

In a research article Michael Mauboussin published in 2007, he shares some examples that vividly reveal how this works. ‘Who Wants to be a Millionaire’ is the one I’ll reproduce. The latter was a television show in which a person from the public was called to the stage to answer a series of questions (usual TV show). If all answers were correct, the person would be awarded a million dollars.

For each question, the host gave the person the option of calling an expert to help answer, do a poll with the audience or to eliminate 2 out of the 4 potential answers. Interestingly, what recurrently happened is that the audience’ average was right in 90% of the scenarios, while the expert got it right 60-70% of the time.

The Pricing Mechanism

In 1945, Friedrich Hayek published The Use of Knowledge in Society. He dives into the problem societies face when trying to arrange information in such a manner that would, essentially, help make decisions. Knowledge is spread among all agents throughout the economy. Each of these has an informational advantage over the others regarding their particular circumstances, time and place. A rational economic system should be one that conveys all dispersed individual pieces of knowledge and sets ‘things’, prices for instance.

 Similarly to what happened with financial literacy, there was a belief that all of this information could be granted to a particular individual so that he/she makes the ultimate call. Scientific knowledge, praised as the most valuable thing we have, needs to be arranged in this manner. Experts are those who are capable of taking it further and, to do so, they need to be thoroughly instructed about available information.

Being economic decisions those that have consequences to the society as a whole, it results imperative to take this granular information into consideration. To the contrary, scientific discoveries do not have this pre-requisite, only vertical knowledge is needed and consequences are not external. However, it is impossible to convey the scattered information in a way that all is considered by the decision-maker. Therefore, a decentralized system is needed.

“It is in this connection that what I have called the “economic calculus” proper helps us, at least by analogy, to see how this problem can be solved, and in fact is being solved, by the price system. Even the single controlling mind, in possession of all the data for some small, self-contained economic system, would not—every time some small adjustment in the allocation of resources had to be made—go explicitly through all the relations between ends and means which might possibly be affected.”

The pricing mechanism is one in which all agents participate, sending signals to the system. The latter being in the form of buying or selling. Each of these would implicitly include, in prices, individual circumstances that caused the signal to be sent. In this manner, this mechanism effectively manages to aggregate all of this dispersed knowledge and make decisions in accordance with everybody. The stock market is a great representation of this system.

Simulations

This is what puts everything together.

The law of large numbers states that, the more times you run an experiment, the more will the result tend towards the expected value. The stock market is the mechanism by which the signals are sent depending on what people think companies’ value is. Hence, it is, in a strange way, designed for finding intrinsic values.

What I suspect is that, over the short run, not enough signals are sent towards businesses’ prices so that the average tends to this expected value, the intrinsic value. In fact, they might be further amplified by overall changes to agents’ environment. Virtual diseases, or virus, could severely contaminate agents’ decision-making processes.

However, as time goes by, more and more signals are sent. Virus get cured, erased and forgotten. Eventually, the experiment is run enough times so that the prices we see are the intrinsic value companies have.

Personal Commentary

I’ve been with this idea for a couple of months. I explored it in the podcast, but I’m very happy to have articulated in words. I’m not even sure the answer is correct, but the thinking process that got me to it is what I mostly value. Hope you enjoyed today’s article and I will try to have François Rochon’s investment philosophy for next Sunday!

Contact: giulianomana@0to1stockmarket.com