Macroeconomics problems
Unit 5
An American businessman was at a pier in a small coastal Mexican village when a boat
with just one fisherman docked. Inside the small boat were several large yellowfin tuna.
The American complimented the Mexican on the quality of his fish and asked how long
it took to catch them. Not long, was the reply. The American then asked the Mexican
how he spent the rest of his time.
“I sleep late, fish a little, play with my children, and talk with my wife. I stroll
into the village each evening, where I sip wine and play guitar with my friends. I have
a full and busy life.”
The American replied, “I have an MBA and can help you. You should spend more
time fishing and, with the proceeds, buy a bigger boat. With the proceeds from what
you could bring in with the bigger boat, you could buy several boats; eventually you
would have a fleet of fishing boats. Instead of selling your catch to a middleman, you
would sell directly to the processor, and eventually open your own cannery. You would
control the product, processing, and distribution.
“You would need to leave this small village. Move to Mexico City, and then maybe
to Los Angeles, where you will run your expanding enterprise.”
The Mexican fisherman asked, “How long will this all take?”
The American replied, “Fifteen or twenty years.”
“But then what?” asked the Mexican.
“That’s the best part! When the time is right, you could go public. You’ll become
very rich; you would make millions!”
“Millions?” replied the Mexican. “Then what?”
The American said, “Then you would retire. Move to a small coastal fishing village
where you would sleep late, fish a little, play with your kids, spend time with your
wife. In the evenings, you could stroll to the village, where you could sip wine and
play your guitar with your friends...”
— MBA fable as told by Russ Roberts in How Adam Smith Can Change Your Life
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Finance
We must now confront head-on a problem between the micro and macro perspectives:
we do not all of us plant the seeds ourselves that are intended to grow into healthy
future fruit-bearing trees. We do not all build the factories together, do not collectively
pave the roads, do not as a group program the robots. We save, so that others might
do these jobs.
I am trying to teach you macroeconomics. You and I are trying to build human
capital together. This is a seed, too! I hope this seed grows into a mighty tree, that
your lives will be happy and meaningful. But this is not the only way I can help plant
seeds for the future.
The Naive Idea of Finance
This picture is NOT entirely true. But it is how most people think of the financial
system.
When I put my savings into an index fund, that is (like teaching) an attempt to
plant seeds. But I don’t know exactly where those particular seeds will be planted.
As individuals, we save financial assets, which are ultimately pieces of paper: stocks,
bonds, savings accounts, etc. It is our hope that the pieces of paper, representing
claims of ownership, will be a good store of value into the future. But this is not
guaranteed. We rely on others to plant these particular seeds for us, and then yet
others will tend to the future fruit that we hope the seeds will grow into.
But we personally don’t know where to put our “money”, don’t know the healthiest
seeds to plant, don’t know the best soil, don’t know the customers for different varieties
of seeds, don’t know which investment will be the next Google or the next Pets.com.1
Saving must be done in a coordinated fashion. The attempt of micro individuals to
save does not automatically, or necessarily, result in genuine saving (read: the creation
of investment goods) at the macro level. We can all of us together try to save, and
then fail. This is part of what Keynes was referring to as the Paradox of Thrift.
1If you haven’t heard of Pets.com, that is because it went bankrupt in the dot-com bust. It no longer exists. This is right around the time when most of you were born.
2
The naive idea behind the financial system is that it accumulations the “savings”
from many different people, and pools those savings into investment into capital goods
like factories. But we have already seen, from our discussion of banking, that banks
create new money with their lending.
Bottom line: much of this unit will contain major oversimplifications.
Financial Coordination
The purpose of the financial system is to coordinate the flow of money that is intended
to be spent on investment goods, rather than consumption goods. Every dollar of
spending goes to one or the other: C or I. An economy that is trying to save more
will decrease the amount spent on C, and increase the amount spent on I.
But again, this is a different group of people! So how does this work?
The Simplest Finance Story: the Bond Market
Most intro macro classes teach the loanable funds model. This can be seen as the
supply and demand for business saving/investment, which determines the real interest
rate r. This is not an especially intuitive model.
Instead, we will discuss a theoretical equivalent model, the market for bonds,
which might be simpler to grasp.2 In order to understand this market, we need to
understand financial instruments, including bonds.
What are bonds?
Bonds are a form of business liabilities. Businesses sell bonds to raise cash.
Let us return to the accounting equation, this time as the accountants normally
write it:
Assets = Liabilities + Equity
I generally prefer to put liabilities on the other side of the equal-sign (easier to
understand) but there’s actually a reason the accountants normally write it this way.
2At least I hope so. If you see loanable funds, you can switch supply and demand to get the bond market. The demand for loanable funds comes from firms wanting to borrow funds to build capital goods. Likewise, the supply of bonds comes from firms wanting to sell bonds for cash to buy capital goods. Two ways of looking at the same idea, but bond markets are more tangible and therefore might be easier to understand. And I’d personally prefer to work with a real market rather than an abstraction.
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The purchase of a firm’s assets must be supported in one of two ways: either the
firm owners pay for those assets ourselves (risking their own net worth, or at least by
finding other potential owners to share the burden), or firms pay for new assets by
borrowing money to buy those assets.
Let’s go back to the T-account, this time for a random company.
Assets Liabilities
Assets: 100 Bonds: 80
(Equity: 20)
This company has 100 dollars worth of assets, supported in part by 80 dollars worth
of borrowed money in the form of corporate bonds. The book equity is thus 20 dollars.
The company also has issued shares of stock (the stockholders are the owners of the
company). Let’s say it’s 100 shares of stock, each of which is worth half a dollar.
Shares of Stock × Price Per Share = Market Capitalization
At 100 shares of stock, each worth fifty cents, the market capitalization of this
company — the total value of all stock outstanding — is 50 dollars. (It is almost never
the case that book equity matches the value of equity shares trading on the market.
Book equity is assets minus liabilities. Market cap is based on daily trading, which
fluctuates wildly.)
Stocks
Stocks represent ownership. They are high-risk assets: big expected return, but big
risk. Let’s suppose that the company is losing money, and can no longer pay its bills.
Creditors sue: these are the bond holders, and other other people owed money. The
company files bankruptcy. The T-account now looks like this:
Assets Liabilities
Assets: 70 Bonds: 80
(Equity: -10)
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The book equity is now −10 dollars.
The basic rule of bankruptcy is that the owners are wiped out: the value of stock
goes to zero. Big risk.
On the flip side of the equation? If the company had been successful, the stock
could have exploded in value and the shareholders could have made a return many
multiples of their original purchase of the asset. (The time-travel novel Rewind, which
is excellent, has the main character make money by being an early purchaser of the
stock of famous corporations.)
Bonds
Bonds are liabilities, not equity. They pay a contractual rate of return. That means
that bond-holders do NOT receive the major upside if the corporation they lend money
becomes mega-successful. That success goes to the riskier asset. Bond holders get paid
only the value of the bond.
The basic idea of a bond is that it is a simple loan.
The issuer makes a promise to pay money in the future. Then they sell this promise
for cash today. The cash is an asset. The promise to pay money in the future is a
liability.
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The holders of the bond will receive only the future promised payment, nothing
more, if the company is wildly successful. But simultaneously, the bond-holders carry
less risk. They avoid the worst pain. Back to the previous bankruptcy.
Assets Liabilities
Assets: 70 Bonds: 80
(Equity: -10)
The bond-holders will take a loss here.
The value of the assets is not enough to pay them back for the full value of their
bonds. Nevertheless, the value of the bonds will not go to zero. The stockholders will
receive nothing in bankruptcy. The bond-holders will get at least a little something
back. The bond does not have the great upside potential that stocks have, but at the
same time, the risk of loss is less.
More on Bankruptcy
This is important for macro, I promise.
There are two version of bankruptcy: restructuring or liquidation. In a liquidation,
when the company is seen as a total dumpster fire, the court will cut the value of the
bonds to the value of the liquidated assets:
Assets Liabilities
Assets: 70 Bonds: 80 70
(Equity: 0)
The stock is worthless. It is zero.
In a liquidation, the assets are sold, and given over to the creditors. There are
different categories of debt, some safer than others, and the court cases can last a
long time. (If you want a boring job that makes a lot of money, consider becoming a
corporate bankruptcy attorney.)
The other possibility for bankruptcy is if the firm can survive in the future if it has
less debt.
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If the court sees the company as a potentially valid going-concern — such as hap-
pened with the General Motors bankruptcy — then instead of killing the company, it
will be given new owners. Who? Often new shareholders are asked to step in with
new cash, but in some cases, the company’s creditors will be forced to take an equity
share of the new company. Their bonds can be converted into equity:
Assets Liabilities
Assets: 70 Bonds: 40
(Equity: 30)
This is a bankruptcy restructuring.
The new company has much less debt to service, which means fewer interest pay-
ments in the future. This gives a nice new cushion of positive book equity. General
Motors was making the best cars it ever made when it went bankrupt. It made no
sense for the company to die. Instead, a new company was born with a smaller debt
burden.
How are bonds priced?
Obviously, we can use the standard idea of supply and demand to figure out the price
people will pay today to receive 1,000 dollars in one year’s time.
But we can get into slightly more depth in order to understand the process better.
Treasury Auctions
The government raises money by issuing bonds. The bonds are issued at auctions.
You all have seen how auctions work in silly movies and TV shows, right?
It doesn’t work exaaaaactly like that, but close enough for our purposes. The Trea-
sury official sits at the front of the room (not really, but close enough) and says to the
audience, “I have a 100 dollar bond here! The US government will guarantee payment
of 100 dollars in exactly one year’s time! Who wants to pay the US government for
the right, NAY, the privilege of receiving a financial asset guaranteed by the 14th
Amendment to the constitution of these great United States of America!”
The first bidder, “I’ll pay 80 dollars!”
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Note: paying 80 dollars today, to receive 100 dollars a year from now is, let’s do
the calculation... Future Payment Today’s Price
= 100 80
= 1.25 = 25%. That would be a 25% rate of
return.
The next bidder, “I’ll pay 90 dollars!” And the next “95 dollars!” “96 dollars!” “97
dollars!” A pause. Then one well-mustachioed gentleman in the back yells wearing a
broad white cowboy hat yells out, “I’ll pay 97 dollars and 73 cents!”
“Sold!” says the Treasury official “to the well-mustachioed gentleman in the white
cowboy hat!”.
And this is how bond prices are determined at auction. Basically.
(Question: What’s the interest rate on that bond?)
The price of a bond and the nominal interest rate can ALWAYS be found from
one another. They have an inverse relationship: the higher the price of the bond, the
lower the interest rate on that bond.
And if the price of the bond goes high enough — in the example above, if the
auction had gone above 100 dollars — then the nominal interest rate on the bond
would actual become negative. This has happened! It’s rare, but not impossible, when
people are very frightened of putting their money anywhere else.
After 2008, people with a lot of cash were afraid of big banks like Lehman failing
and them losing money in the bankruptcy. Rather than trust a bank with the cash,
or paying the expense of storing and guarding a large hoard of cash themselves, they
instead purchased government bonds at negative interest rates. This was very much
like a warehouse fee! (Remember the Goldsmith Fable. Buying government bonds was
like paying a fee to the goldsmith in order to use the safety of his vault.)
Consult a finance course or text for more infos on the financier’s terminology differ-
ence between an “interest rate” or a “yield”, or about how to do the above calculation
when dealing with coupon payments or other complications.
Open Market Operations
Previously we saw the market for holding real cash balances. We saw that the money
supply M can be changed by the central bank. But how is that done?
We saw in the market for Holding Real Money Balances that the central bank
could issue more M (increasing M P
in the short run), which would result in a change
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in the opportunity cost of holding money, the nominal interest rate i (which is equal
to r + π). More money would result in a lower nominal interest rate.
The bond market is the other side of this picture. The space here is the price of
a bond Pbond on the vertical axis — meaning the price of the bond today, how much
people would pay today in order to receive 1,000 in the future — and the quantity of
bonds Qbonds bought and sold on the horizontal axis. This is the space.
When the Fed creates new money, they do not just print it up and dump it from
helicopters. They purchase assets with that money. Normally, the assets they purchase
are US government bonds, called “Treasuries” because they’re issued by the Depart-
ment of the Treasury. This will effect the bond market. When the Fed suddenly shows
up to buy bonds, that will push out the demand for bonds.
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This will push up the price of bonds, like a higher bidder at the Treasury auction.
When the price of the bond goes up, the interest rate must go down: Future Payment Today’s Price
Today’s price is higher, so the nominal interest rate is lower.
This is exactly the same story as the money market!
With sticky prices, more money results in lower interest rates in the short run.
Why? The Fed uses that money to buy bonds, which increases the demand for those
bonds. When the price of a bond today is higher, the nominal interest rate on that
bond must necessarily be lower. We’re seeing the same story play out in two different
markets.
Keep in mind that we’re talking here about the market for very short-run bonds,
for example the 30-day bond. The US Treasury offers bonds of longer maturities, such
as the 10-year long bond. New money can actually increase the interest rate on the
long bond, even as it pushes down the interest rate on the short bond. Why? More
money can mean higher inflation expectations, and higher inflation will eat away the
value of the long bond’s future payments. Since the value of those future payments
will be lower, the long bond can drop in value today, even though the central bank is
demanding more bonds.
See the appendix for more details on this, and the yield curve.
The Seed Analogy
The seed analogy can become strained in finance. It is no longer quite as helpful.
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We can posit here that there is a supply of “savings”, as if I’ve helped produce a
bunch of seeds but I don’t want to eat them all. But I don’t personally know where
to plant the excess. What determines how many I want to plant, compared to how
many I want to eat today? Among other things: the real interest rate.
A higher real interest rate r should in general encourage me to hand my seeds over
to someone who knows where the best soil is. So a higher r should — all else equal —
encourage more quantity supplied of saved seeds.
There is another group of people who presumably know where the seeds go. They
would like to borrow our saved seeds, put them in nice soil, and as a reward for their
knowledge and hard knowledge, take a certain portion of the fruit for themselves.
Notice that these are the people who are borrowing seeds, and so it matters very much
to them what percentage return they have to pay to borrow them. If the real rate of
interest r is high, then the quantity of seeds they will want to borrow will be low. If
they’re forced to pay such a high rate of return, they can only plant seeds in the very
finest soil that they know. When the real return is lower, then they can borrow seeds
at lower cost and plant those seeds in lower quality soil and still make a profit.
This idea works better with the loanable funds graph than the bond market
graph.
But again, it’s not quite true.
I don’t build a bunch of seeds, and then lend my seeds to people who know where
to plant them. I just do economics. It’s my money that gets lent to others. And banks
don’t always need my money, since they can create their own.
We will stick with the bond market in this course. It is narrower, but more tangible.
Making the Model More Complicated
We won’t be doing that in this course.
But obviously, it is possible. The big question when trying to understand the
economy is: how much understanding do we gain as we add more and more complexity?
I don’t have an answer to that question. Finance is very complex.
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Why is Finance Important for Macro?
There are two reasons why all this finance stuff is incredibly important for macroeco-
nomics.
Reason Number One: Banks create money with their lending.
Bank liabilities are our money. When banks create money, it expands our broad
money supply M.
When a bank goes bankrupt, the people who own those bank liabilities — the
people who hold that money — can no longer use the money until the bankruptcy is
finished. When Lehman went bankrupt in 2008, there was more than 40 billion
dollars of frozen accounts. The liquidity — the broad money supply M — suddenly
disappeared.
This can have an immediate effect on aggregate demand! Nominal spending =
M V = nGDP = Aggregate Demand. Less money means people can spend less. 2008
saw the biggest drop in nominal spending (in aggregate demand) since the Great
Depression. Financial crisis can destroy the broad money supply, especially if the
central bank does nothing to stop it.
When the Fed had a meeting just a few days after Lehman went bankrupt, they
chose to do nothing. Says Ben Bernanke in his memoir (emphasis added):
Many participants saw signs of further slowing in the economy and saw
inflation concerns as a bit reduced. I reiterated my view that we were
probably already in a recession. At the end of the discussion we modi-
fied our planned statement to note market developments but also agreed,
unanimously, to leave the federal funds rate unchanged at 2 percent.
In retrospect, that decision was certainly a mistake.
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The Unpredictable Market Hypothesis
There is a second reason why finance is important in macro.
When people hear that you’re an economist, they often ask questions like, “Are we
in a bubble right now? Are stocks likely to fall soon?”
I don’t know.
I don’t know how you can get rich quickly. (I do know how you can get rich slowly:
get a good paying job and save a large percentage of your income.) There is a very
important idea in financial economics — which I have slightly mislabelled above —
which states why this is so often the wrong question to ask. The idea is simply this:
Financial asset prices are not predictable.
Why?
Imagine a different world in which asset prices were easily predictable. Say that
on every Friday right before market close, people got really happy and bid up prices.
Then every Monday on market open, people were sad to go back to work and the price
fell again to its previous level. Imagine this happened every week.
Now imagine that you were a trader whose job it was to buy and sell assets to
make money. You see this predictable pattern. What do you do?
Quite obviously, you sell late Friday just before the weekend froth hits at market
close, and then you re-buy on Monday after prices have settled back down. Do this
every week for a couple years, then retire to Hawai’i. If the pattern is real, then other
traders should join you. They will also sell late Friday before the uptick in prices
— their selling, by the way, depressing the price and thereby making that uptick
disappear. Then they try to buy again on Monday when the price is lower — except
that when they all do this, the price does not predictably go lower.
The price stabilizes. The predictable pattern disappears.
The market price already contains all obvious information.
There are real life traders — and today, trading algorithms — whose job it is to buy
in one place and sell in another place, extremely quickly, in order to pick up a single
penny a hundred thousand times a day. There is money to be made here... but only
if you quite literally the best in the world at doing this.
I think I’m a decent economist. Am I the best in the world?
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No.
In the standard methodology of economics, we jump to equilibrium. We ignore
the dynamic process by which these traders (and computers) incorporate all of their
pattern-recognizing information into their purchases and sales of assets, and we jump
right to the final step: equilibrium. What is our best guess of the future (weighted)
price of any given asset? Today’s price. The market has already done all the work.
(The computers today work in tiny fractions of a second.)
In econo-finance terms, what we say is that in equilibrium (and we pretty much
always jump straight to equilibrium in our analysis), there is no arbitrage opportu-
nity remaining. Anywhere. There is no free money left to be made. The computers
took it all a nanosecond before you looked. This idea can be extended even to future
price trends. What will the market do tomorrow? I don’t know.
Why would I know better than a small army of quant traders on Wall Street with
physics PhDs from MIT and Cal Tech? Why would you know any better? They’re
already using their quite massive brain power, boosted by massive computing power
and better data sets than you or I have access to.
Through the university, I have access to daily stock prices for the last century,
which is more than good enough for most academic research purposes. It’s about 60
gigs of data on my hard drive here.
They have access to minute-by-minute prices. We’re talking terabytes of data here,
not gigabytes, with the supercomputers to handle it.
They’re in the for-profit sector, peeps. They are for realz. If they find a genuine
pattern, do you really think they’re going to tell us about it? No. They’ll make money.
And as they make money on the predictable pattern, it will disappear. We will
never even know it ever existed.
The Difference between “True” and “Useful”
One of the logical corollaries to this idea of unpredictable market prices is that “bub-
bles” are not a reasonable concept. Large upswings in market prices, followed by large
downswings? Sure, sure. But “bubbles”? No, not really, because being in a bubble
implies that people in general know that they’re in a bubble. But... if literally all the
smart money knows it’s a bubble (meaning, there is a predictable price crash coming)...
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then why is there a bubble?
If we all know for a “fact” that the stock market will suffer a major crash next
week, or even next year, then the stock market will crash today.
Right now. Immediately. Unpredictability allows large, volatile swings in asset
prices. But it doesn’t allow “bubbles”, as such.
So, is the Unpredictable Market Hypothesis true?
No.
No. No, it isn’t.
Different question: Is the Unpredictable Market Hypothesis useful?
Yes.
There is some limited predictability in asset prices. And if you are very smart,
and very disciplined, and very in control of your emotional state, and very patient,
very tolerant of very drudgerous and mind-numbing research, and have gonads of very
steel, then yes, you can make some money trading in the financial markets. I don’t
know personally how to advise you to do this. I lack the requisite skills. And that’s
entirely the point. Almost everyone lacks the requisite skills.
Watch the movie The Big Short (or even better, read the book by Michael Lewis)
and pay careful attention to the character of Michael Burry, diagnosed with Asperger
syndrome. (I’m not saying you need high-functioning autism to do this work. I’m
saying you need to be miles outside of the normal personality and skill spectrum to do
this work. Most people aren’t. Most people are much closer to average. That’s why
it’s the average.)
What the Unpredictable Market Hypothesis teaches is not absolute “truth”. It’s
not true. Not literally. There are some definite predictabilities to asset markets. But
our tiny human brains seldom, if ever, have any direct access to truth, anyway.
What this idea teaches is humility. We’re clever little monkeys wearing pants, but
what we don’t know dwarfs what we do.
The Wisdom of Crowds
In 1906, the early pioneering statistician Francis Galton visited a country fair with a
competition to guess the weight of a “dressed ox”. The competition had a small entry
fee, and the closest guesses would receive nice prizes — providing incentive to put at
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least some thought into the matter.
There were around 800 entries, most of them amateurs with no real-world experi-
ence in dead carcass weights. Galton was an early eugenicist — he coined the term
himself — and so had a robust contempt for common people.3 He thought the average
guess of the ignorant public would be very wrong.
The crowd’s average guess was 1,197 pounds. The reality is 1,198 pounds.
See James Surowiecki’s The Wisdom of Crowds for this story told with more detail,
and more verve, than I’ve told it here.
What the hell is going on?
I’ve been thinking about this result for nigh on fifteen years, and I can still barely
wrap my head around it.
There were some major scientific discoveries of the 20th century, including Ein-
stein’s relativity, quantum mechanics, the double-helix structure of DNA. All signif-
icant. But we can’t leave out Galton. His discovery of group wisdom out of mass
ignorance ranks right up there with the rest of them. This is, by far, the single most
important discovery in the history of the social sciences. I can think of nothing else
that comes remotely close.
Now I want us to make some sense of it, because it relates not just to the Unpre-
dictable Market Hypothesis but to the power of the market system in general. How?
How does this devil magic work, exactly?
Well... we don’t really have time to talk about it. See the appendix for a little
more, and the book recommendation for a lot more on this.
Prices are information.
The stock market has forecast nine of the last five recessions.
— Paul Samuelson
The point about financial markets that is relevant to us in macro is that we want to
gain information about how the economy works. Where do we gain that information?
3I have a healthy misanthropy myself, but Galton is a frightening lesson in how misguided and perverted an otherwise clever person’s thoughts can become if they wallow too freely in the contempt of their brothers and sisters on this planet. We’re not so very different as we sometimes like to believe, and we’re all in this mess together.
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From the markets. Including from the financial markets.
We shouldn’t necessarily trust market information. Markets are wrong all the
time. There’s some real useful truth to that Samuelson joke. At the same time, the
market will still have a guess. When the market price changes, it changes for a reason.
Maybe it’s a good reason, maybe a bad reason, and often enough we can’t even make
a reasonable guess for the reason.
But we should still listen. The market is incorporating information that we do not
have direct access to.
This is a macroeconomics class, not a finance class.
It is specifically for the reason that markets contain information, and that they eventu-
ally correct, that I think a focus on asset prices is absolutely essential for understanding
macroeconomic trends.
Prices must adjust for supply and demand to reach equilibrium. This means that
the price contains information, and we should pay attention to that information.
The real name for the Unpredictable Market Hypothesis is the Efficient Market
Hypothesis — “efficiency”, in this strange technical sense, means that the market
has already incorporated all available public information.
Is this true? No.
Is this useful? Yes.
Be a Bayesian: Change your damn mind.
A good probability and statistics education is the best thing you can do for yourself.
I don’t have time to teach you any of this. The most I can do is make a few book
recommendations. For pop books, Nate Silver’s The Signal and the Noise is a good
introduction to predictive analysis. Phil Tetlocks’s Superforecasting is even better.
For a strangely written, highly technical book that requires extensive undergrad math
background, see Jaynes’ Probability Theory. In these books, they use the fancy word
“Bayesian”. This comes from the single most important theorem in all of probability,
which is called Bayes’ Rule. Jumping past the math and two-dollar terminology, the
essence of the rule is very simple:
Always be changing your mind, based on all new information you see.
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I don’t trust market prices. You shouldn’t trust market prices, either. But mar-
ket prices change their mind CONSTANTLY, and this is exactly why I distrust the
information from markets less than I distrust essentially all other sources of economic
information. All that the fancy math says (and it’s not super hard, honestly...) is by
exactly how much you should be changing your mind when you learn something new.
But the more fundamental lesson is: always be changing your mind based on any new
data and new ideas you come across, even if only by a tiny bit.
There are other mathematical rules for coming to conclusions, but we don’t have
time for them. The most important rule is to listen to Keynes:
When my information changes, I alter my conclusions. What do you do,
sir?
— John Maynard Keynes
Exactly.
I think monetary policy is more powerful than fiscal policy, because the
market thinks so.
I’m trying to collect international data on this in a way that is understandable and
convincing, but I’m not very far along on that project.
If you want an extended argument regarding this, you can consult The Money
Illusion blog written by Scott Sumner, and also his posts on the Econlog blog. (Be
warned: he’s not the best writer. His posts are much easier to read if you already have
a good understanding of economics. The good news: you are taking my course.) I was
a typical Keynesian until I read Sumner. He provided arguments, and he provided
data. I changed my mind.
Alternatives to the Unpredictable Market Hypothesis
Markets can remain irrational a lot longer than you and I can remain
solvent.
— John Maynard Keynes
Part of changing your mind is being aware of the best arguments against your
position.
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The most famous alternative to the idea that markets already incorporate available
information is Keynes’s “beauty contest” story. (Keynes was the most important
economist of the 20th century for a reason, yo.) As an analogy to financial markets,
he described a newspaper contest in which contestants were asked to pick the most
beautiful faces out of a hundred pictures. But the prize did not go to the six determined
by the editors of the paper, but rather by the democratic choice: the faces picked most
often by the crowd.
Says Keynes:
It is not a case of choosing those [faces] that, to the best of one’s judg-
ment, are really the prettiest, nor even those that average opinion genuinely
thinks the prettiest. We have reached the third degree where we devote
our intelligences to anticipating what average opinion expects the average
opinion to be. And there are some, I believe, who practice the fourth, fifth
and higher degrees.
The main problem I see with this idea is that some companies go bankrupt, and
some companies pay dividends. Objective markers for winners and losers do, in fact,
exist.
Of all the Fortune 500 companies in 1955, only 12% of them remained sixty years
later. Capitalism is churn and change, not the eternal evaluation of what average
opinion thinks of average opinion. Bankruptcy and buyouts are real.
To be fair, though, Keynes acknowledged that “rationality” can eventually return
to markets — he just thought sensible prices could depart for quite extended periods
of time, long enough to bankrupt even sensible traders.
Skepticism of market prices is undeniably warranted, especially for those of us
who rely on markets to provide information. We need to change our beliefs, just as
markets change their beliefs. I suggest always listening to the market. But I don’t
suggest always trusting the market.
And now for something completely different...
Unemployment!
to be finished soon...
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Appendix: Active Trading vs Index Funds
There’s another point to make about attempting to predict market prices.
Supposing that there is a trading group, hedge fund, whatever, that can genuinely
and reliably beat broad market returns by an average of 2-3% every single year. Per-
haps you would like to join this fund, provide your own money to enjoy that excess
return over the normal market.
How much can they charge you for the privilege of participating in their fund?
Up to 2-3% per year. So what exactly have you gained by attempting to rely on
their expertise?
The world is full of hedge funds that charge 2% annual fees on the money people
give them, and then an additional 20% of whatever gains your portfolio with them
makes, only if it happens to make any gains. So if they get lucky, they get 20% of
your gain, and if they don’t get lucky, they get 2% of your money anyway. It’s called
the 2-and-20.
It’s a nice racket that they can lose your money, and then charge you for the
privilege. If a fund takes a loss, most are designed to return to their previous level
of assets again before once again taking 20% of gains. Unless, of course, the fund is
closed after a loss...
John Meriwether was one of the founders of Long-Term Capital Management, a
major hedge fund whose failure in the late 1990s was so large it had to be mediated
by the Fed. After the failure, he started another fund, which lost nearly half its value
during the financial crisis that started the Great Recession. After that fund closed,
he started a third. (Meriwether is mentioned in Michael Lewis’s book Liar’s Poker. I
previously mentioned Lewis’s book The Big Short which was adapted into a motion
picture. Entertaining writer.)
Active traders take your money. They don’t care if you win or lose, because they
can take your money either way.
Index funds with very low fees — like Vanguard, which pioneered the practice —
give you broad, diversified market participation without the fund managers skimming
off the top to enrich themselves at your expense. I’m not saying that nobody can beat
the market, that future prices are truly unpredictable. What I am saying is that if
other people genuinely do have secret knowledge, the cost of that knowledge will be,
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at minimum, the entire value of what that secret would be worth.
Game theory can tell you, if common sense does not, that it’s simply not worth
paying 110 dollars for a 100 dollar secret. It’s better not to be envious of others. It’s
better to try to get rich slowly, not quickly, and it might not even be a good thing to
try to get rich at all. “Consumption” does not have to mean buying a lot of stuff.
Appreciate what you have. You’re already at least a hundred times richer than
literally every one of your ancestors from precious centuries. One of the keys to
happiness is to value what you already have.
A good economics education will tell you that there are some things money can’t
buy.
Appendix: Modeling Knowledge and Wisdom Together
This is the basic math of the Wisdom of Crowds.
We have a bunch of guesses:
Guess1, Guess2, Guess3, ... , Guessn
We add them together, and take the average, and somehow the result is...
Guess1 + Guess2 + Guess3 + ... + Guessn n
= Truth
That’s it. That’s the structure. So the clue is inside each guess.
The problem with individual guesses is that for certain questions, we have a decent
idea of how ignorant we are. For example, if I were to ask you the weight of the earth,
could you give me a reasonable answer without looking it up? Could you even get
within one or two orders of magnitude of the actual answer? Slaughtered beef is not
so hard a question, but nevertheless, I have never killed and dress an ox before. I don’t
even rightly know what it means to “dress” a dead ox.
We look at our individual guesses, and what we see by ourselves is just... ignorance.
Rank ignorance.
Guessox =?????
When dealing with a question we don’t know, we can only see our own ignorance.
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And yet... there must be knowledge, too. The only possible way for these guesses to
average out to something correct is for each and every guess to contain some kernel of
genuine knowledge.
This is quite easy to see. Let’s say we take the 800 guesses of the weight of the ox,
and add one quadrillion as your personal guess, and then take the average with the
rogue number averaged in with all the other numbers. If we do this, we get an average
“guess” of the slaughtered ox as weighing around a trillion pounds. But nobody in
that country fair guessed such a ridiculous number. Why? Knowledge. From our
personal perspective, we see our ignorance — which is vast! — but from a broader
perspective the vast ignorance of the many coalesces into the wisdom of the collective.
From a god’s eye view, so to speak, the guess is no longer pure ignorance. It looks like
this:
Guessox = Truth + Error
The error is the more significant component, from a personal perspective. We are
all wallowing in vast ignorance. I can’t run a nuclear reactor, can’t repair a fighter
jet, can’t manage a hotel, can’t perform brain surgery, can’t scuba dive, can’t do a
bajillion other things that other people do every day. Ignorance dominates our lives.
And yet... there is a small kernel of truth in our guess.
I wouldn’t guess a negative number for the weight of a dead cow. Would you? I
also wouldn’t guess a trillion pounds, or √ −1 pounds either. The question does not
call for complex numbers, and so I wouldn’t use them. All of this is knowledge. I
still know basically nothing about dead cows, but I know enough to get in the right
ballpark. And that is all that is necessary in this case.
When we add up all the guesses, the truth averages out to the truth. It sticks
around. But the error averages to zero. Poof! It’s gone. This requires very particular
circumstances (let me repeat my recommendation of Surowiecki’s book The Wisdom
of Crowds), but in short, it requires that the errors be non-systematic. There must
be no bias in the error, no desire among the crowd of people that, for example, 7777
is just the prettiest number (don’t you think?) and so half the crowd guesses that
number for cultural reasons.
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The Wisdom of Markets
The good news about markets is that they, sometimes, do a fantastic job of aggregating
collective bits of knowledge into useful civilizational wisdom.
The bad news about markets is that they, sometimes, do a less swell job of ag-
gregating collective bits of knowledge into useful civilization wisdom. The even worse
news is that the same is true of other societal systems. Democracy is a lot of things,
and one of those things is an attempt to aggregate the knowledge of the many into
a usable form for governance, but regardless of your political preferences, you
can probably think of an election where you disagreed with the choice that the people
made.
Financial markets fail one of the nice criteria for a good system that successfully
aggregates knowledge: market prices are visible to everyone. If all traders had to
independently guess the price of an asset, without knowing the past price trajectory
(is the market booming or busting???) then they might do a better job.
But markets also have a remarkably nice feature whose importance cannot possibly
be overemphasized: markets will correct. If you personally believe in asset pricing
“bubbles” (which ideally means not just a belief in volatile markets with extremely
large ups and downs, but predictably volatile markets), then you believe that bad prices
will eventually correct. That’s what the popping of a bubble means!
This is true even if you believe that you can’t personally take advantage of your
prediction.
Appendix: A Likely Violation of the Unpredictable Markets
Hypothesis
to be continued...
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