Technical Traders and Herd Behavior in Markets
You ever watch financial news and hear someone say “the market broke through resistance” or “the market looks tired”? These phrases sound like the market is some living creature with feelings. And if you come from a science background, your first reaction is probably: what does that even mean?
Welcome to the world of technical analysis. And welcome to Chapter 7 of Burton and Shah’s book, where they ask a very uncomfortable question: are all these chart-reading traders just noise traders with fancier tools?
What Technical Traders Actually Do
So there are two ways to analyze stocks. Fundamental analysis looks at actual company data. Earnings, cash flow, dividends, balance sheets. The boring accounting stuff.
Technical analysis ignores all of that. Instead, it looks at price charts, trading volume, seasonal patterns, and tries to find repeating shapes in the data. Think of it like reading tea leaves, but with candlestick charts.
Here’s the thing. Academics used to laugh at technical traders. They compared chart reading to believing in voodoo. But by the early 2000s, technical trading went completely mainstream. The Market Technicians Association had 4,500 members across 85 countries. They even created a certification program, the Chartered Market Technician (CMT), with three levels of exams. Sounds familiar? Yes, it’s modeled after the CFA certification.
And it’s not just individuals. Large hedge funds started putting serious money into strategies based purely on past price history. The National Futures Association counted 4,500 firms and 55,000 associates, most of them doing some form of technical trading.
So whether the efficient market hypothesis likes it or not, technical trading is a massive part of how real markets work.
The Simple Idea: Trends Continue
The most basic belief in technical analysis is this: if a stock is going up, it will keep going up. If it’s going down, it will keep going down.
This is called trend following. And it’s exactly the kind of thing that makes traditional finance people nervous. Because if you model this mathematically, a trend-following noise trader doesn’t care about fundamentals at all. Bad earnings report? Doesn’t matter. The chart says up, so they buy.
And here’s where it gets interesting. If lots of traders follow the same trend, the trend becomes self-fulfilling. Price goes up, everyone buys more, price goes up more. This is not some theoretical worry. This is exactly how bubbles start.
Reversal Patterns: When Charts Get Creative
Trend following is simple. But technical traders also look for reversal patterns, which are shapes in the price chart that supposedly predict when a trend is about to flip.
Island reversal. This happens when a stock price jumps to a different level with a gap. Like it closes at $50 on Friday and opens at $55 on Monday with nothing trading in between. That gap creates an “island” on the chart. Technical traders believe the price must eventually come back and fill that gap.
Head and shoulders. This is probably the most famous chart pattern. The price forms three peaks, with the middle one being the highest (the “head”) and two lower peaks on either side (the “shoulders”). When traders see this shape forming, they expect prices to drop.
Here’s the fun part. A researcher named Carol Osler studied head-and-shoulders patterns in U.S. stocks and found they were unprofitable. But then Osler and Kevin Chang studied the same pattern in currency markets and found the opposite. It actually worked for German marks and Japanese yen. So the same pattern works in one market and fails in another. Make of that what you will.
Base building. This is when a stock drops and then trades in a narrow range for a while. Technical traders see this flat period as the stock “building a base” before it goes up again. Flip the chart upside down and you get “forming a top,” which predicts a drop.
The Cancel-Out Problem (That Doesn’t Cancel Out)
Here’s the argument that defenders of efficient markets always make: noise traders cancel each other out. Some buy, some sell, it all washes out in the aggregate. Like the Law of Large Numbers. Random behavior averages to zero.
But that argument has a big hole in it. It only works if noise traders are doing random, different things. If they’re all doing the same thing, looking at the same charts, following the same trends, then they don’t cancel out at all. They amplify each other.
And that’s exactly what happens with popular technical strategies. When thousands of traders see the same “breakout” pattern and all buy at the same time, that’s not random noise. That’s coordinated noise. That’s a herd.
Herd Instinct: Why Everyone Runs Together
Robert Shiller built a herd instinct model back in 1984, but nobody paid attention for years. The finance world wasn’t ready to hear it.
His argument went like this. The efficient market hypothesis says stock prices are just forecasts of future dividends. If a stock price moves, it should be because expected future dividends changed. But when Shiller looked at actual data, stock prices moved way more than dividends did. Prices were too volatile relative to what the fundamentals justified.
So Shiller proposed a model with two types of investors. “Smart money” investors who behave rationally. And “ordinary” investors, which is a polite way of saying noise traders. When ordinary investors get excited about a stock, they create demand that pushes prices above fundamental value. Smart money tries to push back, but if the fad lasts long enough, even smart money starts playing along.
The key insight: a short fad doesn’t matter much. Smart money can absorb it. But a long, slow-building fad? That moves prices significantly. And it can explain why stock prices are so much more volatile than the underlying fundamentals.
The Bubble Riders
The Abreu-Brunnermeier model from 2003 added something really interesting. Even the “rational” traders, the arbitrageurs who know the market is in a bubble, might choose to ride the bubble instead of betting against it.
Think about it. You’re a smart trader. You see that tech stocks are overpriced. You know there’s a bubble. But the bubble keeps growing. Your colleague who’s riding the wave is making 40% returns. Your short position is losing money every month. At some point, you start thinking: maybe I should just ride it too and get out before it pops.
This is a real problem for efficient market theory. Because the whole theory depends on rational traders correcting mispricing. But if rational traders decide it’s more profitable to join the bubble than fight it, who’s left to correct anything?
The model also shows that not all arbitrageurs notice the bubble at the same time. And even when they do, they don’t all act together. So the bubble can persist much longer than anyone expects. As the old saying goes: you only know you were in a bubble after it’s over.
Are Bubbles Built Into the System?
Burton and Shah end this chapter with a question that honestly keeps me up at night. Are bubbles just a normal feature of financial markets? Not bugs, but features?
Hyman Minsky argued exactly that. He said that stability itself creates instability. When things are going well for a long time, people take more risks. They borrow more. They get careless. And eventually the whole thing collapses. Then regulators rush to “fix” the system, but if Minsky is right, the next bubble is already being planted.
Reinhart and Rogoff, in their book This Time Is Different, pointed out that most economists treat bubbles like historical stories, not economic theory. We describe bubbles after they happen, but we can’t predict them. We don’t fully understand how they start or how they end.
What we do know is this: technical traders who follow the same charts, use the same patterns, and chase the same trends can feed a bubble through simple feedback loops. Price goes up, chart says buy, price goes up more.
What to Take Away
So are technical traders just noise traders with better software? Burton and Shah don’t say that directly. But they make a strong case that technical trading, especially trend following, is a form of systematic noise trading. And when enough people do it, the cancel-out argument fails. The noise becomes the signal.
For you as an investor, the practical lesson is this: when everyone is looking at the same chart and seeing the same thing, be careful. That’s not the market being smart. That’s the herd running together. And herds don’t always run in the right direction.
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