Economic Forecasting Is A Loser's Game, Don't Buy It!
Economic Forecasting Is A Loser's Game, Don't Buy It!
Economic forecasters make money by forecasting regardless of the outcome. They don't have skin in the game.
You may already know it, but if you don’t hear it from me:
“Economic forecasts don’t work.”
And economists generally make awful investors.
This is a forceful objection against the proliferation of macroeconomic forecasters on Substack and social media.
So, join me and let me tell you why macroeconomic forecasts are a loser’s game:
What is predictable doesn’t make you money.
The main measure of economic performance is really simple. Just multiply below two metrics:
Total hours worked
Value of output produced
This gives you Gross Domestic Product (GDP) which is the globally accepted measure of economic performance.
If you want to increase GDP growth, the formula is simple:
You should either increase the hours worked or value of output produced. So simple.
The main driver of the hours worked is population growth. More people living in the country, more total hours worked.
Birth rate tends to follow a stable long-term trend. It doesn’t change significantly year over year. Changes in the birth rate occur slowly in decades due to the mega-trends spanning into decades.
Here is how the birth rates changed in the US since 1980:
As you see, births per 1,000 women between the ages of 15 and 44 was just below 70 in 1980 and it was just above 55 in 2020.
In the four decades, births per 1,000 women decreased by 15. This happened in the course of 4 decades.
However, the effects of the change in birth rate are reflected on the economy even at a slower pace than the change itself. The reason is simple. It takes, on average, two decades for a person to join the workforce after birth.
If a meaningful bump happens in the birth rate tomorrow, it will take 20 years for us to see a meaningful growth in the workforce and birthrates don’t change that fast.
We can also increase the value of output per worked hour. This is called productivity growth.
Just like the birth rates, productivity also tends to follow a long-term secular trend.
The main reason for productivity growth is technological development. Thus, productivity tends to grow very fast after a significant technological development and then tends to significantly slow down until the next big leap.
In the last 500 years of human history, there has been only 4 events that caused a leap forward in productivity:
Industrial revolution that started in the 18th century.
Electricity revolution in the late 19th and early 20th century.
Computer revolution in the 1980s.
Internet revolution, 1990s-ongoing.
As you see, productivity growth doesn’t also happen overnight.
Events creating a meaningful bump in productivity are rare and take decades to mature.
As you see, the productivity growth in the US has never meaningfully passed above 3.5% year-over-year.
At the end, we have two data:
We know that the population is growing, though the growth rate is slowing.
We know that productivity is growing at a changing rate.
Both hours worked and output per hour worked are growing. Thus, we can easily say that the economy will keep growing in the foreseeable future.
This is sets the main trend:
We can confirm by looking at the chart above that increasing population and productivity growth set a secular trend of growth for the US economy.
This is the only dependable prediction we can make by looking at the fundamental data.
However, because this is so obvious, this prediction has no value.
We can’t make any money based on this prediction because it’s an extrapolation of long-term trends therefore they are commonly held. Thus, betting on them doesn’t generate superior performance.
Milton Friedman puts it the best:
“All these people look at the same data, read the same material and spend their time trying to guess what each other is going to say. Their forecast will always be moderately right—and almost never of much use.”
-Milton Friedman
What we need is a high value prediction.
What’s valuable isn’t predictable.
For millions of reasons that interact with each other simultaneously, short-term performance of the economy deviates from the trend line.
Long-term average return of S&P 500 is 10%, but you can hardly find any year that it returned 10%.
As you see, annual performance varies in a wide range from -50% to +60% with an average of 10% annual gain.
In this context, a short-term prediction about the stock market has a lot of value because if you can avoid -40% year, your overall return will dramatically increase.
This brings us to the following chain reasoning:
In investing, it’s easy to achieve an average performance. Just buy the benchmark.
Thus, investment success generally means outperforming others and averages.
Being right isn’t enough if most other people hold the same view.
Success doesn’t come from a correct forecast but from a superior forecast.
For the forecast to be superior, it should be somehow rare.
This brings up the question: Can such a superior forecast be obtained?
Most retail investors predicate their actions on forecasts that they make themselves or obtain from resources like:
Banks.
Economists.
Investment professionals.
These are all mainstream resources. Even the macroeconomic newsletters are mainstream in that sense.
Once a forecast reaches a few thousand people, it becomes mainstream because everybody will tell their friends and it will spread.
Therefore, such a superior forecast cannot be obtained in any mainstream way.
A valuable forecast requires:
a) Event causing a significant deviation from the trend.
b) Event should be infrequent.
Such events are very hard to correctly predict because of the randomness element involved and thus many such forecasts turn out to be wrong and cause investors to lose money.
There will always be a few correct predictions for any significant events.
However, this doesn’t come from the superior prediction skills of the forecasters, but rather from the immense size of the universe of predictions.
There are millions of people around the world making various economic predictions every year. The sample size is so big that a few of them are bound to become true.
John Kennet Galbraith says it best:
“There are two classes of forecasters: Those who don’t know, — and those who don’t know they don’t know.”
-John Kennet Galbraith
Forecasters don’t have skin in the game.
Every macro forecaster has a prediction of his own.
How many of them put their money in their predictions?
How many writers who predicted a recession shorted the market do you think?
They don’t do that. They buy S&P 500.
We, investors, are a different breed.
We have skin in the game.
I have never recommended a stock that I didn’t own, I have never bought a stock that I announced bearish views.
Because we don’t need to. What pays us is our ability to buy winning companies.
What pays forecasters is their ability to trigger people and make people watch & read themselves. They make money even though they pump out wrong predictions.
5 economic predictions by experts that went ridiculously wrong:
1) Irving Fisher, one of America's greatest ever economists, said in October 1929 that he believed equities had reached a "permanently high plateau." Less than two weeks later, stocks plunged and didn't reach the highs they fell from for 25 years.
2) In December 2007, Goldman Sachs chief investment strategist Abby Joseph Cohen suggested the S&P 500 would hit 1,675 by the end of 2008, a climb of 14% — it actually ended below 900.
3) Paul Samuelson, the first American to win the Nobel Prize in economics, said in 1961 that "the Soviet economy is proof that, contrary to what many skeptics had earlier believed, a socialist command economy can function and even thrive."
4) Former Fed chair Alan Greenspan warned in his 2007 book "The Age of Turbulence" that the world might need double digit interest rates to control inflation in the near future. Rates have been near zero for the vast majority of the time since.
5) Former National Association of Realtors chief economist David Lereah published a book called "Why the Real Estate Boom Will Not Bust—And How You Can Profit from It" early in 2006. It has not aged well.
Key lesson
Don’t attempt short-term economic forecasting. Don’t follow those who attempt it.
Investing is the only way.
The only dependable way to make money in the markets is gaining the ability to spot exceptional companies and buying them at attractive prices.
This is what we need, Substack is filled with dozens of individual stock pickers and investment research.
Even though they can make you some money, you can’t follow them forever. You have to learn.
This is why I am launching an investing course that will teach investing from the ground in a systematic way as a part of my vision to make this newsletter the only thing you need.
Here is the curriculum:
Week 1: Stock Market Dynamics
Week 2: The Concept of Fair Value
Week 3: How to Calculate Fair Value
Week 4: Exceptional Companies & Businesses to Avoid
Week 5: How to Find Exceptional Companies
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Week 7: Right Way to Think About the PE Ratio
Week 8: When to Buy & When to Sell
Week 9: Advanced Valuation
Week 10: Case Studies & Sample Portfolio
Bonus: Online meeting at the end of the course.
This means that for the next 10 weeks, you will get the course issue on Saturdays followed by a deep dive on Sundays. They will complement each other.
It starts next week. Price is $150.
Paid subscribers will get free access!
Special 30% Launch Discount continues until the end of this week.
Here is a link to claim it:
Over 30 years later, this economist’s quote still holds true because the financial services industry continues to achieve its alpha from fees paid for forecasting and other near-sighted nonsense more than from market-beating stock picks over long-term holding periods.
“There are two kinds of forecasters: Those who don’t know and those who don’t know they don’t know.” —John Kenneth Galbraith to the Wall Street Journal in 1993.
Is a lose-lose game in my understanding, nothing good comes out of it