Author Archives: theusernamewhichismine

The stock market is not the economy, so what is it?

With the stock market down almost 25% year-to-date, it’s always necessary to remind people that the stock market is not the economy. The market can go way up in a “bad” economy (as we saw during the COVID lockdowns) and likewise can go way down in a “good” economy. But if the market is not the economy, then what is it?

Well in some ways that is a question with multiple answers. As stated in a previous post, for companies the stock market is a source of money, what professionals call “liquidity.” The ability to get more money when you need it just by selling stock, or to purchase assets with stock or borrow against stock, these are all ways that a company can treat stock like it is money and use it to grow their business. So when the stock market is down companies could have a harder time raising the money they need in order to grow and expand their business. In this way it can be argued that the stock market does affect the wider economy significantly by determining how easy it is for companies to grow and expand their business off the money from stock investors. If this source of money/liquidity is hard to come by (because of a bust stock market) then growth will suffer.

From an outside perspective however, the stock market can be seen as the expected near future of all the companies in the market. In a different post I explained that one mechanism that gives a stock value is the expectation of all future dividends (accounting for inflation and uncertainty). Dividends require profits in order to be sustainable, so if in the near future one expects most companies to turn unprofitable, then one would expect many companies to be forced to cut their dividend, and thus one would value stocks less and other investments (like bonds) more. Thus many people have argued that the stock market is a leading indicator for the economy as a whole, if the market is down then that probably says something about the near future of the companies in the market ie that they would be expected to be entering rough straights. In the same way the stock market can be the first thing to rebound out of a recession as investors look to the near future and expect profits and dividends to make a comeback.

So no, the stock market is not the economy. But this the stock market may tell us about the future of the economy, either directly causing that future (companies grow more slowly because it’s harder to raise money) or being an effect of that future (economic storm clouds cause the stock market to tank before the real economy). Either way, we should be prepared for whatever future it holds for us.

No one likes a scientific buzzkill

When doing science, you’ll often come upon mysteries you didn’t expect.  Some of these are exciting and will lead to new discoveries, but some of them are depressing because they mean you did the experiment wrong.  Take a common example: you do an experiment and find a result you didn’t expect.  You obviously want to know why you got the result you did, and so you spend a lot of time and effort looking into what part of the experiment could have been causing the unexpected result.  Eventually the answer could have been caused by contamination of your samples or misuse of your experimental design, either way you didn’t find something new and exciting, you just made more work for yourself since you spent a lot of time chasing down an answer only to find out you just needed to do the experiment all over.

But for those first few days or even weeks you can feel constantly like you’re on the precipice of some new discovery, something grand and publishable that everyone will see and be enlightened by.  I have had feelings like that, and it’s always been a let down to realize that there was nothing cool and exciting about my unexpected results, they simply came from not doing things correctly.  The danger is of course getting too into it, spending a lot of time and money chasing rabbit holes wondering why your data looks weird when the quick and simple answer is “do the experiment again and it will look right,” you can spend many years and millions of dollars just to learn that sometimes.  I thus usually try to look at results with a very pessimistic eye: it’s unlikely I just discovered something literally earth shattering because if it was this easy to discover then someone else would have already done so.  This can at times seem like the joke about the two economists who see 20$ on the sidewalk, but it’s a mindset that promotes healthy skepticism.

With all that said, the hardest part of this for me is making sure other people are healthy skeptics.  We’re all scientists in a lab and we all have that part of our brain that wants to solve a mystery and will spend way too much time and effort trying to do so.  It’s easy all the while to convince yourself that the answer to the mystery is big and groundbreaking enough to justify all the time spent, but so often it just isn’t.  I’ve been dancing around the point for a while but essentially: some people in my lab are looking at data which they think reveals amazing undiscovered insights into a disease we are researching.  I see the data and assume it’s some unknown contaminant causing it and that we should just redo the experiment.  We could spend our time trying to look more at the data or spend our time redoing the experiment, and I fear that if we spend too much time on the former we’ll all be really bummed out when it is a contaminant and we have to go back and spend more time on the latter.  But I can’t stop people from getting excited, just like the X-Files we all want to believe.

The American Challenge Finale: Eurofederalism for the future?

I know I haven’t written much about the American Challenge for a while, but as I read through the book I realized most all of my critiques would be retreads of what I had already said.  In the end, Jean-Jacque Servan-Schreiber’s thesis was made clear from the outset: Europe was falling behind in technology and economics and his preferred cure was Eurofederalism.  As an aside, some of my American readers might not know what Eurofederalism is, it’s basically the idea that Europe (the EU to be more specific) should continue forming an ever closer union between the states, such that political and economic power rests more and more with the supranational EU rather than the nations themselves.  Exactly what the end goal of Eurofederalism is varies from person to person, some people envision a United States of Europe, some want more federalism, some want less, but most would agree that the current amount of cooperation is not enough.  

With Servan-Schreiber’s thesis laid before us, it’s tempting to look back and try to judge how right he was.  On the one hand, I can see all his arguments from 1968 being made today in 2022: Europe still falls behind in certain sectors to American multinational corporations, and many Europeans still think the cure is Eurofederalism, so it’s tempting to call him a true visionary who noticed these things well before others did.  On the other hand, many of the problems he identified from 1968 were solved by Europe without the kind of Eurofederalism he envisioned.  University graduation steadily climbed in Europe to reach the same highs it did in America, Europe’s growth rate climbed so that America never outpaced it to the extent he though they would, and although Europe does not control many of the tech companies of today, they still have not missed out on the productivity gains that tech has brought because buying a computer is still as good as building in yourself.  Perhaps the Four Freedoms on the EU have helped Europe reach this point, but it’s clear that a common, EU-wide industrial policy was not necessary to maintain Europe’s economic growth in the face of American corporations.In the final tally, I do believe Servan-Schreiber was prescient for his day, identifying key weaknesses in the European economies and key strengths in the American one.  But in other ways he was wide of the mark, many industries he wanted to throw money at are not the ones building the future, and his preferred answer was not necessary for Europe to “catch up” in many ways to America’s standard of living.  Overall though, a very enjoyable read: 8/10.

Weekend thoughts: Technical Analysis seems like Exegesis

The stock market has been moving lately.  Up,  down, side-to-side, every movement can launch a thousand stories, but lately I’ve seen a lot of stories pop up of how someone should invest in this market and where they should put their money.  I’m not going to say I have the answers to this question, or even the knowledge of how to find the answers, but I’ll lay out the facts of where I think you will not find the answers.

As an overview, the market is down somewhere between 20% and 25% since January.  If you think the market is going to keep going down, you’d be advised to sell your stocks and hold them as cash until the market reaches a bottom and starts going back up.  If you think we’ve reached the bottom you’d be advised to buy more stocks and rake in the profits as the market goes back up.  There’s arguments for both, but some arguments that feel unsatisfactory are those based on technical analysis.  I don’t mean to be unkind, I know many people swear by TA, perhaps even some of my readers, but TA reminds me of something else I know too much about: exegesis.

Exegesis of the bible or any other holy book is supposed to mean explaining the passages so that your target audience will better understand and act upon them.  The problem is you can make exegesis say whatever you want, because ultimately your explanation is entirely up to you.  When Jesus said “a rich man cannot enter the Kingdom of Heaven anymore than a camel can pass through the eye of a needle” what did he mean?  An exegete can claim that this is a metaphor, that the eye of a needle is a metaphor for a very narrow gate which a camel overloaded with goods would not be able to pass through, so a rich man needs to give away some of his wealth to charity and then he can enter the Kingdom.  Another exegete would say that this isn’t a metaphor, it’s a plain statement emphasized with sarcasm.  A camel cannot pass through the eye of a needle, that’s just dumb, and so Jesus is saying a rich man cannot enter the Kingdom no matter how much he gives to charity.  We can’t know exactly what Jesus meant by this because we can’t call Him up and ask Him.  And there are hundreds of passages in the bible that an exegete can claim to mean whatever they want them to mean, as long as you define enough things as being metaphors or sarcasm or straight facts in order to defend your argument.  Exegesis is a way of creating whatever meaning you want out of Scripture.

Technical Analysis seems to do the same thing with stock market trendlines.  The line is going down, are we “testing support” and will soon break through to go even lower?  Or are we “finding support” and will bounce off to go higher?  You can draw the future trendline however you want, and I’ve honestly never heard of a cogent argument proving that some form of TA is true more often than any other form, or is true more often than a random coin flip.  I’ve seen both bulls and bears quote their TA studies to support their points, and yet I’ve never seen the kind of scientific analysis that can prove the methods to be useful.  The counterargument is that many people, some of them very wealthy and successful stock traders, use TA to build their portfolios and so TA must be useful otherwise those people wouldn’t keep doing it.  My response would be that TA is no more accurate than random chance, and since the market is not zero-sum and rises on average ~7% per year, many people can become supremely wealthy based on this random chance while believing they are beating the market.  I don’t know, it all just seems like wishful thinking, and I’d love to be directed towards some studies discussing the efficacy of TA as a strategy.

The log in your own eye?

There’s someone I love who really needs help but doesn’t want it. There’s an old saying about removing the log in your own eye before criticizing the speck in someone else’s eye. But at the same time, if someone just doesn’t see their problem, isn’t if your duty to try to help them? I can’t fix everything about myself, especially not all at once, but I can at least try to help someone fix themselves while also trying to fix myself. I don’t know what to do though, it’s hard to see someone not get the help they need especially if you love them, but it can destroy a relationship to try to help someone who doesn’t want it. I really hope I can help

Friday feelings: the importance of communication

I don’t want to get into too many specifics here, but this week was a lesson in the importance of communication.  Science is a collaborative process, the days of one person making discoveries have long since passed, and everything we do these days requires not just a team but multiple teams working in tandem.  With that comes a requirement for all teams to be on the same page so they can work together instead of going in circles.  My team recently received a sample to test but has no idea what the sample is or how it was produced.  Without this knowledge, how can we know what is in the sample?  If I see something odd in the sample, how can I know whether it’s important and must be removed or whether it’s a normal and expected part of the process?  And importantly, how can we replicate this work in our own lab if we don’t know how it was produced in the other lab?

Collaboration is of course difficult, we all have our own things to do any communicating to our collaborators sometimes only helps them and not us, so we don’t want to spend energy on it.  Still it’s necessary if a collaboration is going to work and collaboration is a thing that helps all of us. 

Just as important to collaborative communication is scientific communication to the wider community, usually through papers.  I’ve recently thought that scientific journals should also increase the standards to which they hold paper writers, too many will publish inscriptible images and vague methods that cannot be replicated at all, with your best bet in this case is usually the arduous process of calling the original scientist on the phone and asking him or her what the hell they did.  It’s like if you read a recipe and all it said was “cook it until it’s finished.”  What the hell does that even mean?  If you read a paper and you don’t know how the method was done, how can you ever build off that paper?  I’m not trying to accuse people of scientific misconduct or anything, I’m just trying to say that if I have no idea what you did, I’m not going to cite your paper or use it for my own research.  Good communication is important.

Can you beat the stock market?

Since my stock posts tend to get the most traction, let’s try this one.  I wanted to post because I was recently made aware of the Efficient Market Hypothesis which essentially states (in its weak, semi-strong and strong forms) that you cannot beat the stock market.  The weak form states you can’t beat the market using prior performance, the semi-strong states you can’t beat the market using prior and current performance, and the strong form states you can’t beat the market using insider knowledge.  Essentially weak = Technical Analysis is useless, semi-strong = fundamental analysis is useless, strong = insider trading is useless.  Taken together, these hypotheses seem unappealing to a day trader or stock picker, as they suggest the only winning move is the boring play of buying whole-market ETFs.  And yet that also creates a weird contradiction because if everyone believed the Efficient Market Hypothesis, everyone (including banks, hedge funds, and investment groups) would just buy and hold whole-market ETFs and never trade stocks individually.  There would essentially be no stock market in that case!

But getting back to the hypothesis itself, why would it be true that you can’t beat the market?  Let’s start with the weak and semi-strong forms, which only make statements about publicly available information.  The hypotheses in this case are yet another statement about the wisdom of the crowd: all of us are smarter than any one of us.  If you try to use available information to guess the next moves of a stock, you will find that the next moves are already “priced in” because the market beat you to it, and so there is no way to buy low + sell high.  Before you want to buy the price will go up, and before you want to sell the price will go down because the market is always faster and more accurate that the individual.  On the face of it this seems like the joke about the two economist walking down the street: one says to the other “look, a 20$ bill on the sidewalk!” and the other says “ridiculous, there are no 20$ bills on the sidewalk, someone would have already picked them up!”  The fact is that there always has to be someone who was first to use some particular information, and does that let them beat the market?  On the other hand this hypothesis isn’t talking about individual events but averaging across all possible events.  Yes you may have bought early this time, but you can’t consistently buy early and so you’ll buy late and lose as often as you buy early and win.

As to the strong form of the hypothesis, it’s the least defensible because remember it basically states “you can’t make money via insider trading.”  The conceit is that in this case any insider information isn’t purely such, and the wisdom of the market can “price in” insider information thanks to the constant stream of rumors and leaks that even the tightest-run ship is subject to.  Still strong-form hypothesis proponents were quick to point out that this doesn’t necessarily mean insider trading shouldn’t be illegal, it can still be true that the actions someone will take in order to perform insider trading are harmful and so insider trading should be banned.  Hiding bad or good information, making very short term decision to boost the stock at the expense of long-term corporate health, these are all bad things, even if the people making them can’t actually make money off of them, the fact that they think they’ll make money is reason enough to ban insider trading as a practice.

So to finish this ramble, I don’t know if I believe the efficient market hypothesis.  The weak and semi-strong forms obviously seem the most defensible, but it’s important to remember that many well-regarded stock traders with long histories of success don’t believe it.  And what’s true in mathematical economics isn’t always true in reality

The Chapwood Index is a very silly model of inflation

With inflation nearing double digits this year, so called “experts” have been crawling out of the woodwork to proclaim the Death of the Dollar and how they always said inflation would kill us all.  Most of these people make claims with no regard to reality, inflation is bad today and they say it will kill us all.  But 10 years ago when inflation was miniscule they also said inflation was bad and would kill us all.  The facts don’t matter, only the hatred of inflation.  Inflation is high?  We’re all gonna die.  Inflation is low?  It’s actually high.

I can understand the feeling of course, it doesn’t feel good knowing that year after year your money loses value.  But that feeling doesn’t translate much into reality, most Americans gained wealth in real terms from 2010 to 2020 (a trend only reversed around 2021).  So when your feelings of inflation conflict with the reality of inflation, what do you do?  If you’re Ed Butowsky (inventor of the Chapwood Index), you declare reality to be wrong.  You instead make up your own basket of goods (the Chapwood basket) and send open ended surveys asking people to track the changes in those prices.  And if your basket is unusually weighted towards such things as golf club memberships and financial planner’s fees, then yes you could show some strangely high inflation between 2010 and 2020 as the price of those things went up.  But the much larger and more representative basket from the Federal Reserve showed enough price drops in other things that it evened out into low inflation.

In the last decade you might have repeatedly heard calls about how the Fed and the Government are lying about the true rate of inflation, how everything is getting more expensive by double digits and how it’s destroying American wealth.  In the same breath these people probably tried to sell you gold, but that’s neither here nor there.  The point is that many people have tried to argue that the Federal Reserve is lying about the economy and that everything is going to hell in a handbasket, only “secretly” so that none of us plebs realize it.  This year as the economy has actually been rocked by inflation, those voices have been completely overwhelmed, because it’s very clear that genuinely high inflation feels nothing like the low-inflation period that characterized the last 10 years.

Basically the Chapwood Index (and indices like it) was designed to “prove” the point that America had super high inflation, to the tune to 10%, yet the index was completely ridiculous on the face of it.  If America experienced double digit inflation from 2010 to 2020, and if the nominal GDP numbers were accurate, then we would have experienced a real GDP decrease of around 50%.  That means 50% less total everything produced by the economy, 50% less cars, vegetables, and doctor’s appointments.  Yet this flies in the face of actual evidence showing a moderate increase in American production over that time frame.  Simple put, the evidence isn’t consistent with a prolonged decrease in real output.  Again, compare this to 2022 when America is experiencing actual inflation: nominal GDP is up by near double digits, but since inflation is also up by nearly that amount, the total American economy may have contracted slightly by the end of the year.  Super high inflation has been coupled to super high nominal GDP, and it’s still an open question as to whether inflation or GDP will win the year, but it’s clear that this year feels different than all the years from the last decade when people screamed about hidden inflation and buying gold.

Basically what I’m saying is inflation isn’t really missable, if it’s there it’s there and people know it.  Everyone knew the price of goods was increasing in 2021, but the Fed and the government acted slowly because they predicted the increase would be small and “transitory.”  But when inflation jumped to 4% and now nears 8%, it was obvious and didn’t require creating a whole new index just to see it.

How can you fix science that has become engineering?

One of the toughest questions in science is simply “when do you admit you were wrong?”  It’s never an easy thing to do, but we all understand that in the scientific method sometimes our most beautiful, most beloved hypotheses turn out not to describe the world as it truly is.  But people are human and it’s only natural that they’d prefer their favorite hypothesis to be right, and of course there’s always the possibility that just around the corner is some new evidence that will finally prove them right…

This process of clinging to an unsupported hypothesis in the face of repeated failures is something I discussed in a previous post.  There, I discussed working in a lab where we treating our hypothesis more as an engineering problem, we felt we knew that what we were doing was possible if only we could do it right.  Repeated failures never swayed our view of this point, and rather than admit it might be impossible, we would just double down and try again.  When that sort of thinking infects a lab, how do you treat it?  How do you get scientists to go back to being scientists, to go back to accepting or rejecting hypotheses based on the evidence and not taking them as gospel prior to even doing the experiment?

I think one thing that might help this process would be a revolution in the publishing industry in which null results would be considered publishable.  Right now it is very rare to get a paper published that says “we failed to prove something new.”  Novelty is desired, overturning the established paradigms is desired, and failing to accomplish either basically condemns your work to the trash bin, totally unpublishable.  I have often thought that null results should still be archived, if only to tell future scientists where the pitfalls lie and dissuade them from wasting more time on a fruitless endeavor.  But until null results are as publishable as positive results, people will still have a substantial interest in redoing failed experiments just in the hope that this time it will succeed, to do otherwise would force them to admit defeat and start all over from the beginning.

Games that play themselves

There’s a certain type of game I really really like.  It doesn’t have a good category, some games of this type would be called “management,” others would be called “strategy,” but what makes them enjoyable to me is that they’re the types of games where you struggle mightily to do every task the game throws at you, but by the end of the game you have developed systems in which the game basically plays itself.  Let me give some examples.

Factorio is the game that most comes to mind in this.  For Factorio the key word is “automation,” you start the game crash-landing on an alien world and have to hand-mine and hand-craft every single item you’ll need to survive.  Anything you want to build you have to place one by one across the world as well, and so the early game consists of running around mining, crafting, and building hundreds of things by hand.  The goal of the game is to defend yourself from the aliens and launch a rocket ship to escape, but as you progress closer to the rocket everything you want to build or research becomes exponentially more expensive and difficult. 

The trick is that the game gives you systems that you can do to make everything exponentially cheaper and easier.  This biggest game-changer is the ability to create little robots that can perform just about every job for you, and by that point in time the game almost feels like it plays itself.  You can put down big blueprints of what you want to be built and what you want to be crafted and the bots will do everything for you.  Need more resources?  The bots can build mining bases.  Need more science?  The bots can build your labs.  Suddenly everything you had been doing by hand can be done for you and the feeling is just so liberating that I often like to sit back and watch as the bots do everything for me.

The other game that comes to mind is Victoria 2.  Now this game is completely different, it’s not management but more strategy.  Victoria 2 puts you in control of a historical nation starting in 1836 and tells you to guide their destiny from the 19th into the 20th century.  Want to industrialize Japan and become a world power?  You can do that.  What to unite Italy into a single nation?  You can do that.  What to play as France and enact your Napoleonic fantasies?  You do you man, but you can do that. 

The important point is that at the start of the game your nation will normally be poor, illiterate, and un-industrialized, even the nations of Europe were like this in 1836.  This means that there will be tough choices to be made in order to grow your economy, educate your populace, and industrialize your society.  But doing all these things makes the game easier and easier, until by the end of the 19th century you’re likely to be rich, highly educated, and highly industrialized, at which point you can make lots of money even with a fully-funded state apparatus, and capitalists will run around building whatever factory your country needs before you can even ask.  By the end of the game, it is almost playing itself in this way.

I don’t know exactly why I like games like this.  Maybe it’s just about the feeling of liberation you get when something that used to be so hard becomes easy to you, but for whatever reason I really really like games like these and would be happy to be recommended more like them.