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I used to live in Washington, DC.
I don't anymore, but I enjoyed it there.
It was an awesome place to be.
And one of the things that I love doing.
I'm not going to pretend I did this all the time, but I probably did it half a dozen times while I lived.
There was go to the Library of Congress in Washington DC and dig through old newspapers.
Now, let me explain that.
In the Library of Congress they have a section where they have, for probably about a dozen, maybe two dozen newspapers, every single edition that was ever published, going back to, in some cases, the 1700s.
It is absolutely fascinating.
They're all on microfilm.
You can dig through them pretty easily.
And I used to love going and picking out just a random day to read the New York Times from April 1st 1875 or the Hartford Gazette from a random day in 1925, whatever it would be.
The more random you made it, the more interesting I found it to be to read these old newspapers.
Yes, it's interesting to read the newspapers from the big dates of Pearl Harbor And 9-11 and when JFK was assassinated.
That's interesting.
But a random, otherwise normal day is very interesting to see what people were saying about the world in the past.
And lots of things stick out from this.
You see how culture has changed and politics has changed and business has changed.
One of the things I love doing here was just looking at the advertisements and you could see what people were buying and what things used to cost back then.
Maybe some people would find this boring.
I thought it was fascinating.
And one of the things I thought was very interesting that becomes very obvious when you do this is that the things that people predicted would happen in the past by and large did not come true.
And the things that did happen by and large were not predicted.
Like.
One of the big things that comes from this exercise is realizing how uncertain the world is and reading these old newspapers that have no hindsight bias in them.
The people writing these articles did not know what was going to happen next, like a historian might.
Really had no clue what the future was in store.
And yet they keep making predictions and we keep making predictions too.
And, of course, a hundred years from now, people are going to look back at what people wrote in 2025 and have the same feeling.
Look at these idiots.
They thought they knew what was going to happen next and they had no clue.
So that idea of the inability to predict what's going to happen next has always been interesting to me.
And most of that you can just chalk up to the world's uncertain.
It's a big world with trillions of moving parts.
Nobody can understand what's going to happen next.
That's true.
I also think there is a psychology of prediction that plays a huge role here, that there are things that go on inside of our heads that make us more confident than we should and impact how we make predictions and what people demand of predictions and what the audience who's listening to predictions wants to hear.
That plays a big impact on our inability to predict what happens next.
So let me go through a all right number one.
History is the study of surprising events.
Prediction is using historical data to forecast events that will happen next.
And think about that.
Do you see the irony?
When we study history, it's usually things that happened that nobody saw coming.
But then prediction is using history to try to predict what's going to happen next.
It's an unbelievable irony when you wrap your head around it, I think.
The most important events in historical data are the big outliers.
It's the record-breaking events.
That is what moves the needle the most.
That we pay attention to that actually makes a difference in society.
And we use those outliers to guide our views of things like worst case scenarios.
But of course, those record-setting events, when they occurred, had no precedent.
So the forecaster who assumes the worst or the best events of the past will match the worst or best events of the future is not following history.
They think they're being a student of history when they're actually doing the opposite.
They are accidentally assuming the history of unprecedented events happening doesn't apply to the future.
If you're a quote unquote student of history and you're saying look, this happened in the past and I'm using that as a guide to the future, you're actually doing the opposite, because the big events that happened in the past were unknown record-breaking, unprecedented events.
And basically what you're saying is we're not going to have any more of those in the future, right?
Nassim Taleb once wrote, quote In Egypt, scribes tracked the high water mark of the Nile and used it as an estimate for the future worst-case scenario.
The same can be seen in the Fukushima nuclear reactor, which experienced a catastrophic failure in 2011, when a tsunami struck.
It had been built to withstand the worst past historical earthquake, with the builders not imagining much worse and not thinking that the worst past event had no precedent.
Now doing something like that, using the past and assuming it's going to be what happens in the future, that is not a failure of analysis.
It's not that your calculations are wrong or you're looking at the wrong data.
It's a failure of imagination.
Realizing the future might not look anything like the past is a special kind of skill that is not generally looked highly upon by the analytical forecasting community on Wall Street and finance, whatever it might be.
Daniel Kahneman, the late economist, was once asked how we should respond when we make an analysis mistake.
When we predicted something that was going to happen in the economy, in the stock market, whatever it might be, that did not come true.
And I loved his answer.
This is what he said, quote Whenever we are surprised by something, Even if we admit that we made a mistake, we say oh, I'll never make that mistake again.
But in fact, what you should learn when you make a mistake because you did not anticipate something is that the world is difficult to anticipate.
That is a correct lesson to learn from surprises, that the world is surprising.
That last line, I think, should be written on forecasters' walls.
It should be all over their office on their desk.
The correct lesson to learn from surprises is that the world is surprising.
You could apply that not just to the economy and the broader world, but your own personal life as well.
All right, next one here.
Predicting the behavior of other people relies on understanding their motivations, their incentives, their social norms and how all those things can change.
That can be difficult if you are not a member of that group and you have a different set of life experiences.
This one is so common.
Let me tell you a little bit of history to show you what I mean.
One decade after World War I, the League of Nations declared that quote-unquote aggressive war was an illegal crime against humanity.
One year later, the Kellogg-Braid Pact got 61 countries to renounce war as an instrument of national policy.
They said, quote, Sounds wonderful, sounds awesome, and among the signatories of both documents.
Signing that aggressive war was a crime against humanity and we should never, ever do it again were Germany and Japan, who would, of course, go on to commit some of the most aggressive warfare in history just a couple of years after that.
Let me give you another quick, just kind of weird example to this.
I read this this morning.
I thought it was so interesting.
It was from a book about different emotions.
And there's a quote in there where it says, "...asked to sort emotion words into piles.
Rejection was part of anger in China, but part of sadness in America."
So if you ask Chinese people, what emotion do you get when you are rejected?
They're more likely to say angry.
In America, they're more likely to say sad.
So even something that might seem like a universal emotion or common sense is totally different across different cultures.
It is so hard to predict what is going to happen next if you don't fully understand the cultural motivations and influences of people whose experiences and goals and position in the world are different than your own.
Now on a much lighter level, not talking about global war.
Part of why predicting something like the economy and business environment is so difficult is because you have very educated, highly trained, highly paid economists and Wall Street analysts, many of whom earn more than a million dollars a year, trying to understand the spending behaviors of a total population, many of whom live paycheck to paycheck.
And so if you ask me to predict the financial motivations of somebody exactly like me, I would be pretty good at it.
But if you add in someone who has seen the world through a completely different lens than I have, has lived a very different life than I have, has a very different family structure and motivations than I do, and they might look at risk and reward and goals in a way that I don't understand and therefore could never predict, then it's much more difficult to figure out what's going to happen next.
You often hear in behavioral finance that humans are often irrational.
And I think that is true, but it's incomplete.
A lot of times people just look irrational in the eyes of other people who have different motivations and goals than their own.
Next one.
Credibility is not impartial.
Your willingness to believe a prediction is influenced by how much you need that prediction to be true.
If you tell me that you found a way to double my money in a week, I'm not going to believe you by default.
That's just.
If you came to me and said I have a surefire stock trade that's going to double your money next week, I would say you're full of it.
Go away.
Leave me alone.
But if my family, if my children were starving and I owed somebody money next month that I don't have, I might listen to you.
Because that prediction that you said I can double your money next week, that would be so meaningful and impactful to me that I might listen to you.
I bring that up because I cannot tell you how many times I have heard a variation of the following.
Morgan, I have a friend who got laid off three months ago and to make ends meet they have taken up day trading.
I wish them the best of luck.
I hope they are successful, but I cannot help but thinking that the reason that person thinks they can be a successful day trader is because they need to be.
And that has influenced their willingness to listen to people who say, I have a day trading formula.
Chronicling the great plague of London in 1772, Daniel Defoe wrote quote the people were more addicted to prophecies and astrological conjurations, dreams and old wives' tales than ever they were before or since.
Almanacs frightened them terribly.
The posts of houses and corners of streets were plastered over with doctor's bills and papers of ignorant fellows quacking and inviting the people to come out to them for their remedies, which was generally set off with such flourishes as these.
And look, the plague killed a quarter of Londoners in 18 months.
And if I or you were in that situation, I would probably want to pay attention to those quacks and those fake doctors as well.
It is crazy to think that you can impartially judge a prediction if the outcome of that prediction will impact your well-being.
The majority of lottery tickets are purchased by the lowest income Americans.
And it's not even close.
The poorest 10% of people buy the vast majority of lottery tickets.
Why might that be?
I have a theory.
It's because the lowest income Americans overestimate their odds of winning the lottery.
Because when you feel trapped in a poverty-stricken stagnation, you desperately need to believe that you can buy a ticket out of your situation in order to maintain a certain level of functioning optimism.
So many decisions are statistically wrong, but supported by the incentives of the person who is making them, which is a good thing to remember when analyzing the predictions that you see and use to justify your own actions.
All right, next one here.
So much effort goes into making a forecast that updating your views when new information becomes available can trigger the sunk cost fallacy and cause you to be right or wrong for the wrong reasons.
Let me give you an example of this.
Say it is 2005.
By the way, I can't believe that was 20 years ago.
It feels like yesterday, right?
And say that you are a retail stock analyst.
You're covering the retail sector.
Your job is to predict how much Amazon will be worth in 10 years.
So you forecast economic growth and consumer purchasing power and trends in e-commerce and Amazon's profit margins, its market share, to calculate what you think Amazon will be worth in the future.
You do that.
You went to school, you have a big fancy, expensive degree and a lot of resources at your disposal.
You sit down and you make that forecast.
And then after you do that in a way that you never could have seen coming, AWS comes along.
AWS is Amazon's cloud computing product.
It is now huge in majority of its profits.
And that changes everything.
But you, in this situation, are a retail analyst.
You don't do cloud computing.
And whatever your forecast was in 2005, it did not include AWS because that product did not exist yet.
So what do you do in this situation?
Do you even pay attention to AWS?
If you do, do you upend your original forecast and throw it all over and say I was wrong and start over?
You spend a lot of time on that forecast.
Your career and your annual bonus might rely on it.
You don't want to tell everybody who followed you into that original prediction that everything you said back in 2005 turned out to be irrelevant.
That hurts.
Sunk costs hurt.
So maybe you just ignore it.
Your original forecast on Amazon was bullish, let's say.
You were bullish about the future and now that was the right call.
The stock went up and it went up a lot and you feel great.
Everybody praises you for the brilliant prediction, even though you never predicted AWS, which arguably was the biggest driver of returns.
You were right.
You were right, but you were right for the wrong reason.
And by the way, that story could have been reversed.
In a hypothetical world, you could have nailed the retail forecast, but never have foreseen some crazy acquisition that eventually led to its collapse.
Everybody would say that your original forecast was wrong, and those people criticizing you would also be right, but for the wrong reason.
When sunk costs make changing forecasts hard, updating your forecast hard and lead to outcomes that can be right or wrong for the wrong reason.
Both the person making the prediction and those receiving it as a client the people reading that prediction can be fooled.
That's it for this episode.
Thanks again for listening, and we'll see you next time.
