We’re now at the fifth video in the Munger’s Mental Model series.
Thank you for staying on this long, you know what they say:
We never say anything unless it is worth taking a long time to say.
You are truly dedicated Charlie Munger fans.
In the last video, we learned the following:
- By using filters, you can quickly narrow down
thousands of potential investment candidates to a short-list of better than average opportunities
- Patience is key in investing.
Munger didn’t get rich by going after mediocre opportunities
- The best way to get what you want from life is to deserve what you want
- Probability trees and conditional probabilities are terribly important to understand
if you want to be a rational decision-maker, both in the stock market and otherwise
- Lots of things are distributed like a Bell Curve but not all things,
so be careful when applying the elegant mathematics that comes
with this normal distribution
Physics Envy
Humans crave simplicity and elegancy.
In physics, we have beautiful equations such as Newton’s second law
and Einstein’s mass-energy equivalence.
These equations are exceptional findings, and they are really elegant.
Unfortunately, not all subjects can be reduced to such Newtonian formulas.
Subjects which involve human behaviour definitely cannot, and this is where people go wrong a lot of times.
Munger calls this “physics envy”.
Professors in academia in the social fields want to be as elegant as their colleagues
in the science departments, but that is just not possible.
One of the greatest economists who has ever lived, John Maynard Keynes,
understood the problem of physics envy very well himself.
He has said that:
“To convert a model into a quantitative formula
is to destroy its usefulness as an instrument of thought.”
And, of course, he was talking about his own subject of economics here, not complaining
about Newton’s or Einstein’s findings.
For example, the model of supply and demand is a very useful thinking tool in economics.
If there’s high demand for a product, the price of that product tends to rise.
If there’s a low supply of a product, the price tends to rise too.
If the opposite is true, the price tends to fall.
However, if you try to put numbers on these things, you can go really wrong.
Moreover, the numbers can lead you into a false sense of security
because numbers seem less subjective.
There are many other cases where physics envy has led us astray.
The Capital Asset Pricing Model being one example.
Weighted Average Cost of Capital being another.
The Black-Scholes formula for options pricing being a third.
I learned about all of these at university, and it pains me to realize that
most of my efforts here were in vain.
I think I’ll bore you terribly if we discuss why these models are wrong at any deeper level,
so I’ll just give you the TL;DR.
The capital asset pricing model and Black-Scholes are wrong, for one thing, because they assume
that volatility in assets prices is one of the determining variables in securities investing,
and it absolutely is not.
I’ll let Munger explain why WACC is incorrect:
They said if you earned a hundred percent on capital
because you had some marvelous business, your cost of capital was a hundred percent.
And therefore, you shouldn’t look at any opportunity that delivered a lousy 80 percent.
80% is of course a magnificent return on assets, and if a model suggests that one shouldn’t be
involved in areas which yields such results, it’s a model that should go into the rubbish bin.
Vaguely Right Beats Precisely Wrong
John Maynard Keynes is credited with thisphrase
and this mental model is pretty much a spinoff of the last one.
Many professors who are too narrow minded solve problems kind of like this:
“If I can’t demonstrate it with my experiments, then it doesn’t exist.”
You do not want to make this mistake in your own investment approach.
Do not overweigh the stuff that is simple to quantify and apply statistical techniques to.
They may not be the most important variables to consider
just because you can easily attach numbers to them.
This is one of the reasons why Warren Buffett allegedly never has used a computer or calculator
for making his investment decisions.
It’s so easy to fall victim for overweighing the stuff that can be quantified.
Let’s get back to that Capital Asset Pricing Model.
It says that the expected return on an investment can be calculated by adding up a few easy to measure variables,
such as the beta of an investment.
The model will give you a very precise number – “this stock is expected to return 9.88% per year”
– and this is one part of what makes the equation so alluring.
But if you’ll use it, you’ll be, in John Maynard Keynes words, “precisely wrong”.
It’s stupid to think that the historical volatility of a security would be
the most important variable to consider in an investment decision.
You are leaving out all the important stuff!
How reliable and skilful is the management of the company?
What will the industry of the company look like 10 years from now?
How strong is the pricing power of the company? Etc. etc.
You’ll never get quantifiable or precise answers to questions like these,
well, except maybe in fiction: - 42.
But at least you are looking at the right stuff!
Vaguely right beats precisely wrong.
Secondary and Tertiary Effects
It’s been said that a butterfly can flap its wings in the Amazon jungle,
and subsequently, a storm ravages half of Europe.
It is very common for people to forget that, in complex systems,
one action will not just have a single effect.
It will have secondary and tertiary effects too.
Charlie Munger has said that as a meteorologist, he found secondary and tertiary effects very annoying.
And economics make meteorology look like a tea party.
Economics are so complex that even after the fact, it can be difficult to talk about causal
relationships and exactly which thing that led to another but let me have a jab at it here.
In 1906 a great earthquake in San Francisco later led to a run on banks and corporate trusts
attributing to the 1907 stock market crash.
Up until then record-low interest rates of 3% in 1924 caused investors to become more
aggressive which in the end was a component in the 1929 stock market crash
and the great depression.
Or, if you want a more recent one, the abandonment of the Glass-Stegall Act, once again allowing
commercial banks and investment banks to operate under the same roof, in 1999, arguably lead
to the financial crises almost ten years later.
For an investor, these complicated secondary and tertiary effects have a few important implications.
Firstly, it should make you realize that trying to outsmart the market by predicting bulls and bears
is a terribly difficult art, one might even argue impossible.
We’ve heard Munger say it before, but it probably won’t hurt being a bit repetitive:
Around here I would say that if our predictions have been a little better than other peoples’,
it’s because we tried to make fewer of them.
Secondly, there are specific cases where investors should beware too.
Munger says that it is very common in corporate life to forget about how competitors
will react in response to a certain move.
For example, say that you are predicting huge cost savings by investing in new machinery
or a new production plant.
The return on capital in such a project may look amazing, but often only when considering
your business decision in a vacuum.
If competitors do something similar prices will fall in the industry as a whole,
and the returns that were projected will disappear.
It’s like people in a crowd observing a parade.
Someone decides to stand on his toes, which seems fair for him at the time
- he’ll get a better view.
But in only a matter of minutes, everyone else is standing on their toes too,
and now no one has a better view, but they all have lots of lactic acid in their calves.
The Cancer Surgery Formula
A business with something glorious underneath,
disguised by terrible numbers that cause cutoff points in other people’s minds,
is ideal for us, if we can figure it out.
I think this is an important mental model for an investor specifically, and it’s something
I hadn’t heard about before making this series.
When doing cancer surgery, you are trying to remove what is dangerous and bad to persevere
what is still healthy and vibrant underneath.
Similarly, occasionally, you can find investments which has a great core, but there’s a lot
that is distracting and bad surrounding it that disguises the good parts.
Think about a company with multiple different business segments.
Perhaps they have diversified too much and focused too little on their core business.
These new projects haven’t been very successful, but the core is still intact and doing well.
In a sense, the good part of the investment is disguised, which is great for keeping down
the price of the business.
You know that I do not like to talk about my own investment ideas,
I see them as valuable assets just like regular business secrets.
However, I’ll say this.
One of the investments that I’m in right now is an example of the cancer surgery formula.
It’s disguised as an oil and gas company, and people really seem to hate these companies right now
because, well, they are probably doomed in the long run due to the environmental megatrend.
But in fact, the stock is not an investment in oil and gas.
It’s more of an asset play, as the company has tons of cash
and marketable securities on its balance sheet.
So, the investment is disguised as an oil and gas company, but it is in fact a classic
Benjamin Graham play of acquiring a business below net current assets.
Scale
Before, we talked about an important question that every long-term investor should ask him-or herself:
“What will the industry of the company look like 10 years from now?”
To remain relevant in an industry, a company that you invest in must possess a competitive advantage
meaning that, it must do something which allows it to beat its competitors.
One of the most important advantages within many industries is scale.
Some advantages of scale are purely mathematical.
In a circular tank, if you increase it size, you’ll need less steel per cubic meter
as volume grows faster than the surface for such a shape.
This can keep costs down in a production plant.
Other advantages of scale are just a result of the characteristics of the industry.
Newspapers, for instance, was truly a “winner takes all” industry for a while
because of scale advantages.
The paper with the most circulation attracted the most advertisers
and the paper with the most advertisers could hire the greatest journalists and write the greatest stories,
thereby creating a self-reinforcing loop.
Some modern examples are even crazier, scale can truly allow a single competitor
in an industry to dominate.
Take Google.
More than 90% of all search queries are posted here.
Why?
Because of scale advantages.
Google gets the most data about users because most searches happen there, which allows them
to present the best search results.
Moreover, advertisers know this, and they pay top-dollars to be seen on Google by this user-base.
This advantage is self-reinforcing like crazy.
In addition to this, there are more classical advantages of scale such as advantage in experience,
efficiency in production, social proof etc.
With scale comes bureaucracy too though, so the largest player doesn’t always win.
However, I’d say that being a large player is oftentimes advantageous.
Things cannot grow indefinitely though, and that shall be the first topic of the next video – limits.
Hope to see you for that one.
Cheers guys.