What is Behavioral Economics?

Fundamentals · Nov 24, 2019

For many years, the majority of economists based their financial theories on a few basic assumptions: all market participants are perfectly rational (investors aren’t emotional at all), and they are also free from any biases or information processing errors. The real-life and practical economy showed that these assumptions don’t work in many cases and people tend to behave irrationally from time to time. It seems to be a part of human nature: we’re not robots, after all. This line of thinking gave birth to a new and booming field of research called behavioral economics.


Behavioral economics is a big field of study that touches behavioral finance, game theory, economic reasoning, customers' behavior, evolutionary psychology, and even artificial intelligence. We can’t cover it all in this article, but we’ll explain the core ideas and insights of behavioral economics, the efficient-market hypothesis and common decision-making biases that many investors seem to have.

Table of Contents

Efficient-market Hypothesis

To understand behavioral economics we should first take a quick look at the efficient-market hypothesis (EMH). The concept of efficient-market had dominated mainstream economics for more than 100 years. It states that all of the information about any tradable asset is already reflected in its price. Therefore, each investor who buys or sells an asset is supposed to have all of the possible knowledge about this asset so he can make a perfectly rational decision.

Students in universities were told that markets are always efficient, thus the market prices are always “right” by definition. Sure, everybody knew that this invisible hand, a term first mentioned by Adam Smith, works only within perfectly competitive and unregulated markets without oligopolies or monopolies. The point is, scholars never assumed that ordinary customers and business owners would act irrationally, stupid or even harmful towards each other. The idea was that all of the market participants are rational, fair and truthful.

So, if a price of a good, service or an asset is too low, this is just a temporary “market anomaly” that has to be fixed eventually as people learn about it and purchase this underpriced product. The opposite has to be true as well: if a price is too high, people will soon learn that there are similar products being sold at a lower price so they would buy them instead. Actually, EMH theory stated that prices can’t be too low or high, they are always “fair”.

In the modern world, this simple beautiful idea started to fail more and more often, so a new field in economics emerged with the mission to correct classic theories and to add new information on how the markets work. If EMH was 100% correct, it would be impossible to outperform the market in terms of risk-adjusted return.

The efficient-market hypothesis was developed and introduced in its modern form in 1970 by Eugene Fama, who proposed two concepts that have been widely used ever since. He introduced three types of efficiency (strong-form, semi-strong form, and weak efficiency) and argued that the notion of market efficiency couldn’t be rejected without an accompanying rejection of the model of market equilibrium, which is the fundamental price-setting mechanism accepted in economics.

In 2017, Richard Thaler, an American economist, received the Nobel Prize in economics for his studies in this field. An important part of his work was to prove that people are irrational, especially when it comes to making economic decisions. He also wrote a great book on behavioral economics that is really insightful.

You can watch how these two brilliant economists argue about the Efficient-market Hypothesis in this video by Chicago Booth Review.

Bubbles, Crises and Market Crashes

A big argument against the classic efficient-market hypothesis was that it doesn’t explain why bubbles, crises and market crashes occur. If everyone is acting rationally without mistakes and if everyone has a full access to all of the necessary market information, why do markets experience such unfortunate and harmful events such as the United States housing bubble of 2007? Why would people keep buying the real estate that is obviously overpriced and if they have the full information at hand? The answer is that people often don’t see the whole picture and many people base their decisions on anything but the real facts about the market.

Some could say that such bubbles are also natural and that they are fit to the efficient-market hypothesis (EMH) because after all, the prices tend to “return to reality”, but if the markets were truly efficient, this return lag wouldn’t be as long, as the world has seen.

So, behavioral economics is trying to explain and measure those lags and inefficiencies by bringing up psychology to economics. Daniel Kahneman, an Israeli-American psychologist, was awarded the Nobel Prize in Economics in 2002 for his work on the connection between psychology and economics. In this work, he researched human judgment and decision-making under uncertainty. His book , Thinking, Fast and Slow, provides some interesting insights on how our brains work.

What is Behavioral Finance?

Behavioral Finance, as a part of behavioral economics, studies the influence of irrational and emotional behavior on the financial markets.

Behavioral Finance is mostly about the efficient-market hypothesis and a very important figure here is Robert J. Shiller, who won the Nobel Prize in 2013 for presenting an argument on why the efficient-market hypothesis doesn’t always work. He is an author of many insightful books such as Irrational Exuberance and Phishing For Phools. Those books are pleasure to read: they’re full of interesting economic data as well as humorous personal stories.

The main reason why the efficient-market hypothesis fails to work in 100% of cases is the decision-making errors and biases that market participants have.

Decision-making Errors and Biases

Behavioral economics views the market participants such as traders and investors, as “normal”, i.e. not rational. Therefore they must have certain emotional, psychological and decision-making biases.

Psychologists identified many cognitive biases, here are just some of them:

  • Bandwagon effect - tendency to do or believe in something just because many other people do that.
  • Focusing effect - the tendency to overestimate the importance on some aspects of a problem.
  • Illusion of control - the tendency to overestimate one’s degree of influence over other external events.
  • Peltzman effect - tendency to take greater risks when perceived safety increases.

But more important non-rational decision-making biases related to the subject are:

  • Heuristics. Humans, as most of the animals, tend to make most of their decisions based on simple and subjective mental shortcuts.
  • Framing. The same asset can look more or less attractive depending on how it’s presented.
  • Noise trading. People often buy and sell assets based on “noise”, i.e. news, rumors, panic, and other social influence.
  • Loss aversion. It is an interesting concept that states that most people would rather avoid any losses than to have a chance to gain something.

The classification of behavioral finance concepts is different from one source to another: thestreet.com divides them into four groups (Mental accounting, Herd behavior, Anchoring, High self-rating), and corporatefinanceinstitute.com brings up these categories: Self-Deception, Heuristic Simplification, Emotion, and Social Influence.

The core idea behind all of the behavioral finance concepts is that people are not always rational, i.e. they are prone to acting under emotional influence.

Example 1: Home Bias

Our first example of a behavioral bias in the home bias. Home bias (patriotism) is a tendency to be more favorable towards something in or from a home country even if there is a better foreign alternative.

In trading and investing, home bias means that market participants tend to buy too much local assets. For example, a German trader might have some feelings towards German stocks and ignore more profitable alternatives from other countries, and a trader from Japan might pick a Japanese company as an investment.

Today’s market is truly global and there is no need to avoid foreign exposure, yet many people still don’t even consider the possibility to purchase a foreign stock. Professional traders know that better but many beginners get stuck inside their local markets.

For an American, choosing a U.S. stock might be a smart idea as the U.S. economy is objectively the strongest and the biggest right now, but even for Americans it might be a good idea to at least consider some foreign options in order to diversify their portfolios.

In science, this concept is called Equity home bias puzzle and it was first described in 1991.

Example 2: Loss Aversion

Loss aversion is about the fact that most of the people hate losing, and thus they prefer to avoid risks, even if the game (or a particular action in the game) is actually favorable for them from the statistical and mathematical point of view. This concept was first identified by Amos Tversky and Daniel Kahneman, whos work, as we mentioned earlier, had a huge impact on behavioral economics. This fear of losing can sometimes force people to fight for the status quo or do nothing, even when doing nothing is more dangerous than acting.

Almost any active trader experienced loss aversion at some point in their career. It happens when a trader doesn’t use the “stop-loss” order to close his positions when he obviously made the wrong bet and the price went in the wrong direction. Many unexpired traders don’t use any risk management strategies like the one percent rule at all and they suffer harmful consequences because of that. What they should do is to accept their losses, learn their lessons and move onto the next deal, instead, some of them would keep their positions open and wait when the market changes its direction to their favor. Usually, as the result of such emotional attachment to their money, in the long-run, those traders lose even more money as they would lose if they just accepted first small losses.

A more common example of the loss aversion is that some market participants would avoid certain risky assets even if the potential returns could be greater than risks. Instead of measuring alpha and beta they just avoid risky securities and lose profitable opportunities as the result.

Example 3: Confirmation Bias

Confirmation bias is the tendency to interpret new evidence as confirmation of one’s existing beliefs or theories. This bias is quite common in many areas of life, and finance isn’t an exception.

For instance, a few days ago, Elon Musk presented a new vehicle - CyberTruck. Tesla stock went down by 6% right after the presentation during which Musk’s colleague broke the “unbreakable” truck’s glass.

Elon Musk is a very eccentric and controversial figure who has an army of haters and an army of fans. Both sides made their beliefs into cults and they look for any new shreds of evidence that would prove their view (either that he is a horrible phony liar, or that he is a reincarnation of Tesla himself and Leonardo Da Vinci combined). The objective truth lies somewhere between those two extreme views, but it’s hard for many people to think of Musk rationally.

So, when the presentation came out, reasonable watchers noted that this new eclectic pickup had 187,000 preorders in just 3 days, but a horde of emotional people marched online to write about the weak glass and a weird design instead. They were happy to see this “failed” presentation that proved that Musk’s business isn’t going very well, but Musk’s supporters from the opposite side are praying on any positive news that would prove their view that Musk is a genius.

People with confirmation bias only care about facts that will strengthen their position and they ignore those that are breaking their point of view. Unfortunately, in today’s hyper connected world we see this kind of bias very often as even journalism became “one-sided”.

Example 4: The CUBA fund

Let’s look at the CUBA fund case that Richard Thaler presented to prove his point. It’s a fund with ticker symbol “CUBA”, which had nothing to do with the country simply because Cuban market securities didn’t exist and because buying anything Cuban as a U.S. company was illegal. Suddenly, the fund grew in value from -10% to a +70% premium in a very short period of time. Why did it happen? Is fund’s real assets changed during a few months? Nope. It’s just President Obama announced his intention to relax the United States’ diplomatic relations with Cuba, so some investors assumed that this fund is somehow well-suited to enter the new market or that it already has some Cuban assets. In any case, the fund’s assets didn’t change and it wasn’t best prepared to enter the new market, yet its value went up based on some biases, wrong ideas or false expectations.

Conclusion: Traditional Economists vs Behaviorists

The debate between traditional economists and behaviorists is going on for a long time.

Behaviorists are looking for and point out so-called “anomalies” and defects of the market to prove their point. The example 4 above with the CUBA fund case illustrates a typical anomaly. Another big argument they have is the fact that bubbles exist, which is explained previously.

Traditional economists defend the Efficient-market Hypothesis by saying that it’s still a hypothesis, so it isn’t right in 100% of the cases, and that all those anomalies are anecdotal evidence and not a proper data that should be used. Plus, they politely ask behaviorists to show their working model which can replace the classical theory, but behaviorists don’t propose a new working solution.

However, there are a few points on which both sides agree, one of which is that in the long run value stocks are better than growth stocks. Also, both sides essentially want to explain and understand how the reality works and not all behaviorists necessarily want to completely destroy the classic theory, they just want to improve and modernize it.

It’s understandable why the attempt to connect economics, finance, and phycology can receive criticism. After all, many scientists tend to avoid everything that is not objective or not measurable, and some even say that psychology isn’t a serious science at all, ergo connecting it to economics is going to make the field even weaker. Some people state that the economics itself isn’t a science too. It’s relatively easy to point out why a certain idea doesn’t work, but it’s much harder to explain things and to discover the basic rules like the relation between the supply, demand, and market prices.

So, when economics accepts that a part of it is tightly connected to non-scientific psychology, it can cause some frustration. Today, it’s quite obvious that such a connection exists, it’s just much harder to express it in modern scientific terms. The only reliable conclusion from modern behavioral finance is that, to put it simply: nothing works as it supposed to. Unfortunately, there are no solutions so far that can reliably show us how things work in the real world.

Scholars and researchers understand that so they came up with so-called “quantitative behavioral finance” that uses mathematical and statistical methodology to understand behavioral biases which can help us to solve the problem of unreliability of psychology in economics.

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