Efficient Market Hypothesis (Series 65 and Series 66)

Transcript

SPEAKER_00 0:00

Welcome back to the deep dive. Today we are wrestling with uh what is probably the single most influential and definitely most debated theory in all of finance, the efficient market hypothesis, or you know, the EMH.

SPEAKER_01 0:12

It really is. It's this bedrock concept that's taught everywhere, the one that tells us financial markets are these incredible information processing machines. But it always brings up that one huge question for anyone with money in the market.

SPEAKER_00 0:23

Aaron Powell Are they truly rational, or can you actually consistently beat them? That's the one. And that's our mission for this deep dive. We've gone through a huge sack of sources for you, everything from the original academic work by Eugene Fama and Burton Malkiel to the uh the big counterarguments from behavioral guys like Robert Schleifer.

SPEAKER_01 0:42

Aaron Powell We really want you to get a quick grasp on not just what EMH is, but why it's still the dominant idea, even when it feels like real-world events are screaming that it's wrong.

SPEAKER_00 0:52

Okay, so at its core, what is it?

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At its heart, the EMH is incredibly, almost beautifully simple. It just proposes that all the known information about an investment like a stock is already perfectly reflected in its price.

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Instantly.

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Instantly. So in practical terms, a stock is always priced at its fair value. You're never really finding a true bargain or an overpriced dud because the market is just too fast.

SPEAKER_00 1:18

And if you believe that, the implication for you as an investor is, well, it's massive. It is. Yeah.

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It means you can't reliably make superior returns just by doing more research. The only way to get a higher profit is to take on more risk. That's it.

SPEAKER_00 1:34

So if the market's always right, what's the smart move for someone just trying to save for retirement?

SPEAKER_01 1:39

Aaron Powell It points you directly to passive management. The most rational thing to do is just stop trying to be the smartest person in the room.

SPEAKER_00 1:45

Aaron Powell By the whole market.

SPEAKER_01 1:47

Exactly. By a broad market index fund like an SP 500 tracker, keep your costs low and just match the market's return. Your effort is better spent on, well, literally anything else.

SPEAKER_00 1:57

All right, let's get into the mechanics, this idea that prices are just random, a random walk. Where did that actually come from?

SPEAKER_01 2:04

You have to go all the way back. I mean, way back to the early 20th century. A French mathematician, Louis Bachelier, was looking at commodity prices in 1900. But the term itself The term random walk was really formalized a few years later, 1905, by Carl Pearson.

SPEAKER_00 2:19

Aaron Powell A random walk. It just sounds like a fancy way of saying the market is total chaos.

SPEAKER_01 2:23

Aaron Powell It's a bit more precise than that. It means that tomorrow's price change is a random departure from today's price. So tomorrow's price only reflects tomorrow's news. The past has absolutely zero predictive power.

SPEAKER_00 2:36

Aaron Powell And that idea became the foundation for Eugene Fama, right, in the 60s and 70s.

SPEAKER_01 2:41

Aaron Powell Precisely. Fama took that and gave us the three nested forms of the EMH, which are all based on what kind of information is already baked into the stock price.

SPEAKER_00 2:50

Aaron Powell Okay, let's start with the first level.

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That'd be weak efficiency.

SPEAKER_00 2:53

And what information is reflected there?

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In the weak form, the theory is that current prices reflect all historical price and volume data. So every chart pattern you can find, every trading surge. It's all in there.

SPEAKER_00 3:05

So if that's true, what's a complete waste of time for an investor?

SPEAKER_01 3:08

Aaron Powell Technical analysis, you know, in TA, the whole practice of looking at charts for patterns and trends to predict the future. Trevor Burrus, Jr.

SPEAKER_00 3:14

Right. Trying to find head and shoulders patterns or whatever.

SPEAKER_01 3:17

Aaron Powell Exactly. If the market is weakly efficient, all those patterns are just meaningless noise.

SPEAKER_00 3:22

But the weak form does leave a little bit of a loophole open, doesn't it?

SPEAKER_01 3:25

It does. A believer in the weak form would say that while TA is useless, fundamental analysis. Well, that can still work.

SPEAKER_00 3:34

Okay, let's just quickly define those two. TA is looking at charts. How is fundamental analysis or FA different?

SPEAKER_01 3:41

Fundamental analysis is about trying to figure out a company's true intrinsic value. You look at everything, earnings, management quality, the economy, and then you compare that true value to the current stock price to see if it's a bargain.

SPEAKER_00 3:54

So weak form says past prices are useless, but digging into a company's financials might still pay off. Now let's go to level two. Semi-strong efficiency. This one is a much bigger deal.

SPEAKER_01 4:05

It really is, because it's so much broader. It says that stock prices reflect all available public information. All of it. All of it. Not just the historical price data, but all the fundamental data too. Earnings reports, news articles, analyst ratings. If you can find it on the internet, it's already in the price.

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And here's where it gets really uh sobering for the listener. If the semi-strong form holds true, then all those analysts pulling all nighters.

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It's all for nothing. Neither technical nor fundamental analysis can help you consistently beat the market.

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Aaron Powell So under semi-strong, what's the only advantage left?

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The only thing left would be um non-public information, insider information. Trevor Burrus, Jr.

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Which of course leads us to the final and most extreme level.

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Strong efficiency.

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And this one is just everything.

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Everything, period. Past data, public data, and private insider information. If the market is strong form efficient, no one, I mean, no one has an advantage. You absolutely cannot beat the market.

SPEAKER_00 5:00

Aaron Powell But this really clean, elegant theory just crashes head-on into the messiness of, you know, real human beings. So we had to talk about the counter-argument from behavioral finance, which is all about market anomalies.

SPEAKER_01 5:12

Aaron Powell The anomalies are really the Achilles heel for the EMH. These are systematic, recurring patterns in the market that just don't seem consistent with perfectly rational pricing. They happen too often to just be a fluke.

SPEAKER_00 5:24

Okay, so what are the big ones? The anomalies that make you think, hey, maybe investors aren't so rational after all.

SPEAKER_01 5:30

Let's start with the valuation anomalies. The value effect is probably the most famous. Study after study shows that firms with low price to earnings ratios, we call value stocks, tend to generate higher returns over time.

SPEAKER_00 5:42

Okay, but hold on. Why is that an anomaly? Couldn't it just be that those stocks are riskier? EMH would say the PE ratio just reflects risk, not a mistake in pricing.

SPEAKER_01 5:52

And that is the absolute crucial point. Fama would argue, yes, it's just a premium for taking on more risk, but the behavioral critique is that the extra return you get is often way too large to be explained by risk alone. They argue it looks a lot more like the market is just underpricing these stocks.

SPEAKER_00 6:09

Okay, that makes the distinction clearer. It's about whether the extra return is justified by risk. What's another big one?

SPEAKER_01 6:15

The small firm effect. For decades, it's been observed that smaller companies, by market cap, tend to outperform larger, more established ones.

SPEAKER_00 6:23

And what's the behavioral explanation there?

SPEAKER_01 6:25

Well, again, it could just be risk. But the behavioral side suggests it's also a neglected firm effect. Smaller companies get less attention from analysts, fewer big institutions own them, so there might be little pockets of mispricing that you can exploit.

SPEAKER_00 6:40

And then there's the one that just sounds like a statistical headache the equity premium puzzle.

SPEAKER_01 6:44

It's a really powerful one. We all know stocks have historically done way better than super safe assets like treasury bills. In the US, that extra return, that premium, has been about 6.9% a year. And rational models have a really, really hard time explaining why that gap is so huge.

SPEAKER_00 7:00

A 6.9% annual gap is massive.

SPEAKER_01 7:03

If rational models can't explain it, how does psychology behavioral finance points to things like myopic loss aversion? Basically, investors get way too focused on short-term losses, which happen all the time with stocks. And because of that fear, they demand this irrationally high premium to be willing to hold them at all.

SPEAKER_00 7:21

And beyond these valuation issues, we also see these weird calendar patterns that suggest prices are predictable sometimes.

SPEAKER_01 7:27

Oh, absolutely. You've got the January effect. Yeah. Stocks, especially smaller ones or last year's losers, often seem to get a big price bump in January. Trevor Burrus, Jr.

SPEAKER_00 7:36

And that's often tied to tax loss selling at the end of the year, right?

SPEAKER_01 7:39

That's the most common explanation. Yeah. People sell their losers in December for the tax deduction, artificially pushing the price down, and then it bounces back.

SPEAKER_00 7:47

Aaron Powell And it goes right down to the day of the week.

SPEAKER_01 7:49

It does. The day of the week effect shows that historically, returns tend to be positive on Fridays and uh negative on Mondays. It's a strange little pattern that seems more tied to human mood than anything rational.

SPEAKER_00 8:03

Aaron Powell And what about the long run? Is there a pattern there?

SPEAKER_01 8:05

Yes. And it's a big one. Long run return reversals. Researchers found that if a stock was a huge winner over, say the last five years, it was very likely to underperform over the next five years. And the losers often became winners.

SPEAKER_00 8:19

So mean reversion.

SPEAKER_01 8:21

Exactly. It suggests investors just get way too excited, push prices way too high or too low, and then the market slowly, slowly corrects that overreaction. So when you present this whole list of problems, this list of anomalies, the defense from the EMH camp always comes back to one single mechanism: rational arbitrage.

SPEAKER_00 8:41

Right. Arbitrage is the market's cleanup crew. The idea is if a stock price is clearly wrong, some smart, rational trader will swoop in, buy the cheap thing, sell the expensive thing, and in the process, push the price back to where it's supposed to be.

SPEAKER_01 8:54

And that's how efficiency is enforced. The problem isn't that arbitragers don't exist, it's that in the real world, they face a lot of limits.

SPEAKER_00 9:02

Okay, so let's get into those. What's the first big roadblock for arbitrage?

SPEAKER_01 9:05

The first is what's called noise trader risk. So the arbitrager is rational, but they have to operate in a market filled with uh noise traders, people acting on emotion or bad information.

SPEAKER_00 9:16

So the rational person can be right, but still lose money.

SPEAKER_01 9:19

Exactly. Imagine a stock is underpriced. The arbitrager buys it, expecting it to go up, but they have no idea when. They're terrified that the noise traders will just keep getting more pessimistic, pushing the price even lower in the short term and forcing them to sell at a loss.

SPEAKER_00 9:35

So the rational players get scared off by the irrational players.

SPEAKER_01 9:38

And the mispricing survives, it's a psychological standoff. The other big limit is more practical.

SPEAKER_00 9:43

What's that?

SPEAKER_01 9:44

Resource limitations. Arbitrage is expensive. And it's usually done by professionals managing other people's money. If the mispricing doesn't correct itself quickly, the people who provided the capital get nervous. They see the short-term losses and they pull their money out.

SPEAKER_00 9:58

Forcing the arbitrager to close the trade before it can pay off.

SPEAKER_01 10:01

Precisely. The price is still wrong, but the mechanism to fix it just ran out of time and money.

SPEAKER_00 10:07

We saw this entire debate play out so vividly during the 1987 crash. The market lost a third of its value in a day. The behavioral folks point to that and say, see, pure panic. EMH is dead.

SPEAKER_01 10:18

And you can see why. But the rational counterargument for people like Malkeel was that, well, actually, the fundamentals did change. Long-term treasury bond yields shot up from around 9% to nearly 10.5%. That's a huge shift in the cost of money.

SPEAKER_00 10:34

Explain how a seemingly small change like that can cause such a massive crash.

SPEAKER_01 10:39

Okay, so think of a stock's price as just the value of all its future profits, discounted back to today. That discount rate, the required rate of return, is tied to interest rates. So when interest rates jump up, all those future profits suddenly become worth a lot less today. The math is pretty stark. If your required return goes from, say, 11% to 13%, the rational price of a stock can fall from$100 to about$67. So a huge crash doesn't necessarily require irrationality.

SPEAKER_00 11:06

But even with that, the internet bubble gave us some examples that just seem impossible to defend. The famous Palm Pilot case.

SPEAKER_01 11:12

Ah, yes. The 3COM and Palm spinoff. It's the perfect textbook example of arbitrage limits. So 3COM spun off a small piece of its subsidiary, Palm, but 3COM still owned 95% of Palm's stock.

SPEAKER_00 11:24

And what happened in the market?

SPEAKER_01 11:26

For a while, the market value of the 95% stake in Palm that 3COM still owned was worth more than the entire market value of 3COM itself. Which means the market was saying that the rest of 3com's massive profitable business had a negative value.

SPEAKER_00 11:42

That's completely absurd. It was free money, so why didn't arbitragers just fix it?

SPEAKER_01 11:46

Because they couldn't. To do the trade, you needed to buy 3COM and short Palm. But there was almost no Palm stock available to short. The mechanism was broken. You couldn't execute both sides of the trade.

SPEAKER_00 11:57

So a guaranteed profit just sat there completely out of reach because of a market technicality. Wow. That really shows how irrationality can persist.

SPEAKER_01 12:05

So to really decide where you land on this, you have to look at the empirical data. Can we actually measure this random walk in the real world?

SPEAKER_00 12:12

There was a really compelling study on this using Apple stock prices from 1981 to 2013. I mean, if any stock is efficiently priced, it should be Apple.

SPEAKER_01 12:20

Right. And the test was simple. Does yesterday's price change tell you anything at all about today's price change? If EMH is right, the answer should be a hard no.

SPEAKER_00 12:29

And what did they find?

SPEAKER_01 12:31

They found that statistically, the change in Apple stock price was completely random. Yesterday's price had no power to predict today's price. It was a pretty powerful piece of evidence for the strong form, at least in that one case.

SPEAKER_00 12:43

Aaron Powell But I think the most powerful real-world evidence for the EMH uh isn't in these statistical tests. It's in the performance, or really the lack of performance of the professionals.

SPEAKER_01 12:55

This is the ultimate test, and it runs 24-7. If the market was full of these easy-to-exploit inefficiencies, then the smartest, best paid fund managers should be able to beat it consistently.

SPEAKER_00 13:06

But they don't. The data is just brutal on this point.

SPEAKER_01 13:09

It's so clear.

SPEAKER_00 13:19

And we have to be so careful about the data we even see because of something called survivorship bias.

SPEAKER_01 13:24

Absolutely. The really bad funds don't stick around. They get shut down and merged away. So when you look at the average return of funds, you're only looking at the ones that survived, which makes the whole group look better than it really is.

SPEAKER_00 13:35

And even among the survivors, do the winners keep winning?

SPEAKER_01 13:38

Very, very rarely. There's almost no performance persistence. Yeah. The top funds of one decade are often the dogs of the next. One huge study tracked hundreds of funds over 30 years. Only five. Five out of 355 managed to beat the market by 2% a year after costs. It's just so incredibly hard to maintain an edge.

SPEAKER_00 13:57

Aaron Powell, so where does all of this leave us? We have these two competing realities. On one hand, the EMH is still the dominant theory because markets are, you know, incredibly good at processing information. But on the other hand, behavioral finance has this mountain of evidence showing systematic anomalies.

SPEAKER_01 14:13

Aaron Powell But here's the clever counterargument from the EMH side. Any truly reliable pattern you discover, like the January effect, will eventually self-destruct.

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Why? Because once everyone knows about it.

SPEAKER_01 14:25

Everyone tries to profit from it. Rational investors will pile in to arbitrage it away, and in doing so, they make the pattern disappear. The very act of trying to beat the market is what makes the market so hard to beat.

SPEAKER_00 14:35

Which brings us to this beautiful kind of final paradox that keeps this whole debate alive. It was laid out by Grossman and Stiglitz back in 1980.

SPEAKER_01 14:45

It's the ultimate puzzle. The market can't be perfectly efficient. Because if it were, if prices reflected all information instantly and for free, then there would be no incentive for anyone to do the hard work of digging up that information in the first place. The analysts would all quit.

SPEAKER_00 15:01

So the market has to be just inefficient enough to reward the people who are out there looking for information, but it's also too efficient to let any of them win for very long. It's what keeps the whole machine running and it leaves you, the listener, right in the middle of that puzzle.