Charlie Munger is not only insightful, but he’s an entertaining guy to listen to. These Munger comments below were compiled by Aznaur Midov from the annual meeting for Daily Journal Corporation, a company that Munger chairs.
I just thought I’d highlight a few comments that I thought were interesting.
Charlie Munger talked about moats a couple times during the meeting. The first time he recited a few examples of formerly great companies that had significant competitive advantages, but due to the nature of capitalism, eventually wound up bankrupt:
“The perfect example of Darwinism is what technology has done to businesses. When someone takes their existing business and tries to transform it into something else—they fail. In technology that is often the case. Look at Kodak: it was the dominant imaging company in the world. They did fabulously during the great depression, but then wiped out the shareholders because of technological change. Look at General Motors, which was the most important company in the world when I was young. It wiped out its shareholders. How do you start as a dominant auto company in the world with the other two competitors not even close, and end up wiping out your shareholders? It’s very Darwinian—it’s tough out there. Technological change is one of the toughest things.”
Charlie Munger had this story when asked to identify a moat:
Question: What is the least talked about or most misunderstood moat?
Charlie Munger: You basically want me to explain to you a difficult subject of identifying moats. It reminds me of a story. One man came to Mozart and asked him how to write a symphony. Mozart replied, “You are too young to write a symphony.” The man said, “You were writing symphonies when you were 10 years of age, and I am 21.” Mozart said, “Yes, but I didn’t run around asking people how to do it”.
This was an interesting response. Moats are all the rage these days among value investors—especially Munger and Buffett disciples (a group of which I consider myself a part of as well). This is for good reason—all things equal, we’d ideally prefer to own a company with a competitive advantage (a “moat”). The problem is that it’s relatively easy to identify a company that is doing well. It’s much harder to look into the future and determine if said company will continue to do well. The durability of moats is much harder to identify than the moat itself. And the durability is really what is most important, since most of the time the company that is doing well currently is often priced to reflect that.
Thus, the other problem is valuation. Charlie Munger again:
“Everyone has the idea of owning good companies. The problem is that they have high prices in relations to assets and earnings, and that takes all of the fun out of the game. If all you needed to do is to figure out what company is better than others, everyone would make a lot of money. But that is not the case. They keep raising the prices to the point when the odds change. I always knew that, but they were teaching my colleagues that the market is so efficient that no one can beat it. I knew people in Omaha who beat the pari-mutuel system. I never went near a business school, so my mind wasn’t polluted by this craziness. People are trying to be smart—all I am trying to do is not to be idiotic, but it’s harder than most people think.”
Charlie Munger’s comment above reminded me of the comment that he made years ago in a speech in California. In this lecture, Munger points out how important it is to think in decision trees and simple probability. He references the concepts of two 17th century mathematicians: Pierre de Fermat and Blaise Pascal.
In the summer of 1654, one of Pascal’s friends—a gambler who was smart, but consistently lost money—came to Pascal asking for help with why he consistently lost money. This problem was interesting for Pascal, and a series of letters ensued that summer between Pascal and another mathematician, Fermat. By the end of the summer, these casual letters ended up proving to be a linchpin in the fundamentals of modern day probability.
Charlie Munger didn’t get into detail of this in his talk, but he did state how important the concept of thinking probabilistically is. And he even attributed this skill as one of the reasons for Buffett’s success:
“One of the advantages of a fellow like Buffett, whom I’ve worked with all these years, is that he automatically thinks in terms of decision trees and the elementary math of permutations and combinations…”
But the main point of bringing up a couple of 400 year old mathematicians was to describe how the pari-mutuel system works:
“Any damn fool can see that a horse carrying a light weight with a wonderful win rate and a good post position, etc., etc. is way more likely to win than a horse with a terrible record and extra weight and so on and so on. But if you look at the odds, the bad horse pays 100 to 1, whereas the good horse pays 3 to 2. Then it’s not clear which is statistically the best bet using the mathematics of Fermat and Pascal.”
So the pari-mutuel system that is the stock market is fairly good at leveling the playing field between the high quality stallions and the broken down nags. Charlie Munger says a railroad company at 1/3rd of book value might not necessarily be as attractive a value as IBM at 6 times book value. Of course, it’s not perfectly efficient, and sometimes the nags provide more value relative to the price you can buy them for, other times the stallions do.
Reducing the Probability for Error
I think the stallions (the good businesses) often prove to be the lowest risk, highest probability outcomes, but this is not always the case. I’ve always thought generally speaking—most investment mistakes are made because an error was made evaluating the business as opposed to an error based on the valuation given the current state of the business. Of course, you could argue that a bad business (or one that gets progressively bad) turned out to be overvalued. But I’m just referring to the idea that very few serious investment mistakes come from buying great businesses at too high prices. Sometimes this happens—like buying Coke in 1998 or Microsoft in 2000. Business results at both of those companies continued to be good, but the stocks performed poorly. But usually, this type of mistake (while still a mistake) means mediocre results going forward, and not necessarily significant loss of capital. The big losses tend to come from being wrong about the business.
So I find I spend a lot of time trying to reduce errors, and this leads me to preferring high quality businesses. And Munger and Buffett have obviously proved the merit of this idea over time. As Charlie Munger said in that same lecture:
“And so having started out as Grahamites—which, by the way, worked fine—we gradually got what I would call better insights. And we realized that some company that was selling at 2 or 3 times book value could still be a hell of a bargain because of momentums implicit in its position, sometimes combined with an unusual managerial skill plainly present in some individual…”
So moats are important, valuation is crucial, but thinking in terms of probability is also very important. Evaluating what Wal-Mart will look like in 10 years will probably lead to a more predictable outcome than evaluating Facebook (note: more predictable, not necessarily better). There are no sure things, but there are probabilities, and the probabilities—unlike card games or dice—are dynamic and ever changing. It’s not an exact science.
What you’re trying to do is locate what Munger calls the “easy decisions”. The low risk, high probability bets. Sometimes those come from the best companies in the world with significant advantages, other times they come from off the beaten path—companies that are involved with some sort of special situation that might not have these sought after moats, but nonetheless offer significant value and low risk of permanent capital impairment.
I think what Charlie Munger is really saying—if I can be so bold to put words in his mouth—is that identifying moats is not a science, and it’s not easy to describe to someone who is asking about them. (After all, the quote above is from a speech called “The Art of Stock Picking”). Each situation is different and each company has its own set of circumstances. Despite how much we’d like to boil this down into a checklist and a simple box checking exercise, investing just doesn’t work that way. It takes a lot of preparation to put yourself in the position to identify these low risk, high probability investments, and it also takes a lot of patience and discipline to wait for them in the meantime when they aren’t available.
Charlie Munger succinctly summarizes this point when he was asked at the meeting “what system do you use to identify great investments?”
“We tend to look for the easy decisions, but we find it very hard to find “easy decisions”. We found just barely enough and they had their own problems. So, I don’t have a system.”
It is certainly a lot harder for Munger than the rest of us. He is 91, he’s a billionaire, and he unfortunately has far fewer investment opportunities than most of us.
But his experience is relevant, and we can take away certain aspects of his investment philosophy as we hunt for our own bargains.