Which Biases Should You Protect Against?

Mark Riepe: Nosology¹ is the branch of medicine that deals with the classification of diseases. Early nosologists struggled to develop a way to categorize diseases, diagnoses, and causes of death.² Should they be divided into order and species the way plants and animals were classified, or would another technique be better? One eighteenth century scientist identified and categorized over 2,400 different diseases.³ These days, doctors can choose between tens of thousands of different medical codes when diagnosing a patient. That kind of precision is great, but even if it were possible, it wouldn’t be practical to protect against everything, given that many of these diseases and diagnoses are exceedingly rare, and their impacts are so varied.

The field of behavioral economics shares some of these characteristics. In the mid-1970s, there were a handful of identified systematic biases. Today, the field has catalogued over 100 different biases and heuristics—and the list keeps growing.

But cataloging the list of biases and heuristics that could affect you is much different from understanding which ones are most common.

In this episode we are going to look at some empirical data from a survey whose results show which biases are most prevalent among investors and how these results differ by age group.

I’m Mark Riepe, and this is Financial Decoder, an original podcast from Charles Schwab.

It’s a show where we study the cognitive and emotional biases that can influence your financial decisions. And we offer strategies designed to help you mitigate those biases and improve your financial life.

We’ll get to the survey results in a minute. But before we do, many of the biases that appear in the survey results are ones that we’ve covered before on this show, but not all of them.

One that we haven’t covered is herding. Herding occurs when you get many investors doing exactly the same thing just because others are doing it.

The difficulty with herding is that investors are following others because they believe that the others have better information than they do. To a certain extent that makes sense. It’s just like seeing a lot of people at a restaurant that you’re not familiar with. You naturally assume that it’s worth checking out for yourself.

With investing, though, there’s a problem. When too many people crowd in and there are lots of buyers, then asset bubbles can inflate. At the other end of the spectrum, when the herd is selling, then markets can crash.

Another bias that popped up, and that I want to talk about today, is the anchoring bias. This bias involves people paying too much attention to an anchor or starting point when making an estimate. What makes this an especially devious bias is that people are easily manipulated into using nonsensical starting points.

In the original experiment that identified the anchoring bias,⁴ subjects were asked to estimate the number of African countries in the United Nations. But before the subjects guessed a number, they had to spin a wheel and decide whether or not the actual number of countries was higher or lower than the number that came up on the wheel. They then gave what they thought was the correct number.

What the subjects didn’t know was that the wheel was rigged so that for some participants the number on the wheel was 10, and for the others it was 45.

The people who got a 10 when they spun the wheel had an average guess of 25 countries, whereas those who spun a 45 had, on average, a guess of 65 countries.

What’s even more interesting is that when participants were paid for being accurate, the effect didn’t go away.

You may think that that’s a silly experiment under artificial conditions, but what makes this an especially devious bias is that people’s estimates are easily manipulated even in settings where the anchor is more plausible. In other words, people will adopt a starting point but pay too much attention to it and fail to adjust for idiosyncratic characteristics of what they’re estimating. In financial services, the effect has been documented in:

• Residential real estate,⁵ where appraisers were overly influenced by the asking price of the house, and
• Earnings forecasts of stocks analysts⁶ who tended to treat individual companies as being too similar to the industry average. 

Now we’re going to bring in a behavioral finance expert to discuss some of these biases in a little more detail—and see which ones turned out to be the most prevalent for different groups of people.

MARK: Joining me once again is Omar Aguilar. Omar is the chief investment officer for equities at Charles Schwab Investment Management and an expert in behavioral finance. He was a Fulbright Scholar at Duke University’s Institute of Statistics and Decisions Sciences, where he earned his master’s degree and PhD. Omar was our guest back on the episode titled “Should You Diversify Differently?” Omar, thanks for coming back.

OMAR AGUILAR: Thank you, Mark, thanks for having me.

MARK: Omar, you just completed a survey of independent financial advisors regarding behavioral finance. Tell me a little bit about the survey. What were you trying to accomplish, who were you surveying, etc.?

OMAR: Yes, this is very exciting, Mark. Over the course of the years we have always been very interested in the concepts of behavioral finance, and we have a strong commitment for education, to work with clients and advisors, to highlight the importance of behavioral finance in their practices.

So this summer we partnered with the Investments and Wealth Institute, the IWI, to conduct a survey with 300 advisors, to try to understand how they use the concept of behavioral finance in practice. So this survey was conducted by Cerulli Associates, and overall the findings show that advisors recognize and use behavioral finance more than we ever thought before the survey.

MARK: That’s interesting. One of the questions that interested me most was you asked the advisors which biases are most prevalent among their clients. What were, say, the two biggest?

OMAR: One of the ones that show up in the results of the survey was loss aversion, and the other one was recency bias. I know we’re going to discuss this later on, but those were very typical biases that you would expect, not only just from clients but also from advisors.

MARK: I want to ask you how the results differed by generation. Let’s start with millennials. Were their most important biases or most prevalent biases, were those any different from what you saw overall?

OMAR: Well, that was a component of the survey that we were keen to understand. You know, we have had over time the suspicions that, you know, the biases are different depending on the environment. Clearly we are all wired differently, and where part of the behavioral finance science shows that there are emotions and there are cognitive biases. But cognitive biases tend to be just a function of the environment, so whatever is your class, whatever is the society, whatever you live with.

So we did find differences in generations, and specifically when it talks about millennials, herding was one of the typical biases that we observed and that was confirmed by the survey, and confirmation bias was another one, a lot of that clearly because of the social media, because of the data information they have available.

MARK: What about Gen X, how do they stack up?

OMAR: Well, Gen X, which is an interesting generation, because it’s in between the baby boomers and millennials, what they showed in the survey is that they have confirmation bias, similar to millennials, but they also have recency bias. And the recency bias tends to be a little closer to what baby boomers have.

MARK: So speaking of baby boomers, what were those biases?

OMAR: Well, you know, as you would expect, loss aversion was one of them, especially as people are getting closer to retirement or are already in retirement, for that generation. And anchoring, anchoring is a critical one because it’s a cognitive bias that had made that generation successful.

MARK: Interesting. Let’s review those in more detail. Recency bias, I think of that as the tendency to pay too much attention to recent information. It often manifests itself by people extrapolating what’s just happened; they extrapolate it too far into the future. It’s tricky, though, from the standpoint of the investor. How is an investor supposed to know when the recent past represents a true sea change or a paradigm change, and how are you supposed to distinguish those events from something that’s just kind of a fluke circumstance?

OMAR: You’re right—it’s very hard to distinguish whether or not we’re just going to a different phase in the economic cycle, whether or not this is a change in the way that people invest, and many times, even in the media, you know, we hear people talking about, “This time is different.”

MARK: Let’s go to confirmation bias—that was something you mentioned for both millennials and Gen X. It’s similar to recency bias in that I think of it as a situation where people are misinterpreting information. In the case of confirmation bias, someone has formed an opinion, and then they are either ignoring information contrary to that opinion, or every piece of information they get they sort of manipulate it to end up supporting their point of view.

So how do you go about combatting this tendency? This really seems to be something that’s one of the more pernicious of the biases that are out there.

OMAR: Yes, again, another cognitive bias that clearly is very prevalent in these generations, because they will always find data, and they will always find information to confirm what they want to do, and I think that’s the biggest challenge, because now, with all the available information, clearly, they can ignore even the risk associated with their theses.

I always give an example, especially with millennials, about Bitcoin. The concept of Bitcoin, it’s new for everybody, but clearly it gets their attention, and yes, you can actually find a lot of research to confirm their views that it’s a good investment proposition, without ignoring the economic background, without ignoring the other alternatives that they have.

MARK: I think Bitcoin is a great example because it kind of leads into the next bias I wanted to talk about, which is herding. I think of herding as a situation where you’re making an investment just because you’ve seen someone else make an investment. What’s not to like about that approach?

OMAR: The difference between the confirmation bias is that you have a thesis and you want to find information and evidence to confirm your thesis. With herding, you don’t have a thesis; you just like what other people are doing. Your view is that if everybody else is successful, you don’t want to be out—the typical, you know, fear of missing out.

That’s a little more typical of certain generations because of again, the social media, the information, whatever they see out there. It is interesting that most people will find, say, the number of stars that they see for a restaurant, and even though they’ve never tried the restaurant, they may not even like the food, but just because they have five stars, they’re willing to go to that restaurant.

So the whole idea of herding is even if you don’t know what you’re getting into, just because other people are doing it, you’re going to go in too. So that’s a little easier to mitigate because clearly you can actually question the reasons why you’re doing it, and at some point rational decisions will prevail.

MARK: Herding’s interesting because professionals suffer from it as well. I think you’re probably familiar with some of the research among stock analysts who estimate company earnings. There are a lot of good reasons not to be too far away from the average of everyone else’s estimate.

OMAR: Absolutely, and I think that’s a very typical bias of any human being, because you don’t want to be the odd duck. You don’t want to necessarily go completely opposite of what everybody else is doing, and I think it’s a tradeoff of the risk of being wrong when you’re trying to be completely different than the consensus, and that is applicable to investments, it’s applicable to other things as well.

MARK: Let’s talk about loss aversion. That refers to the tendency of people, they don’t want to realize a loss. It’s easy to say cut your losses, let your winners run, but that’s pretty hard to do in practice, so any advice for investors to overcome this?

OMAR: Yes, so loss aversion is probably the first bias that was probably the trigger of how the behavioral finance science was created. The whole idea of having utility function that is not symmetric, in other words, you don’t necessarily enjoy your wins at the same way that you suffer your losses. And I think just the fact that you clearly want to avoid the losses at all costs creates biases in the majority of people out there, in some other cases more. This is different than the other biases we just talked about because this tends to be a little more emotional. People obviously feel, and society feels, weird when you have losses, and therefore you want to avoid even getting to the decision of potentially doing that.  I think the example that you mentioned about cutting your losses, just the typical of rebalancing, when things are going well, most people say there’s no reason why we actually even have to change anything because everything is going well, and I think that’s sort of the typical mistake that people make when they have loss aversion, just, you know, having a fear of even accept that you made a wrong decision is a very typical bias of any human being.

MARK: So how do you recommend overcoming loss aversion?

OMAR: So in order for that to be overcome, you know, what we normally, you know, would discuss is, create an implementation plan that is disciplined, that allows you to rebalance, that allows you to, no matter what it is, you clearly have a calendar schedule where you’re going to actually cut your losses, you’re going to actually trim your winners, but you’re going to continue to maintain your stability at all given points, even if things are going great, staying that as your plan for implementation usually tends to mitigate some of that bias.

MARK: I think that’s a great example. Earlier you were talking about cognitive versus emotional biases, and to a certain extent you can imagine it being easier to kind of learn your way out of a cognitive bias. Emotional biases, you’re not going to learn your way out of that. You need to put in, as you were just describing, some structural processes that are going to keep you on track.

OMAR: Absolutely, and it’s the difference between that cognitive piece and the emotional piece. I always try to think about it as like rooting for a team in sports—the emotional part will keep you engaged with your team, even if you know the odds of winning are low. You’re not going to root for the other team, and the only thing you can do is just set yourself ready because you’re still going to be emotionally attached to those decisions.

MARK: So I thought you talked a little bit about this earlier, but it is kind of interesting, the differences of which were the most prevalent biases among the different generations. Ultimately what do you think is driving that?

OMAR: Well, the reality is because we are all humans. I think it is important for investors to understand that, yes, when it comes down to money, when it comes down to finance, when they start their planning, there will be an emotional and a behavioral component that will be part of it.

Now the difference between generations has to do with our experiences. Overall, the environment that baby boomers lived when they were in their ’20s, in their ’30s, it is very different than the environment that millennials are living today.

In the case of the baby boomers, the majority of the time they have lived through a bull market, so it is very comfortable for them to think that the market will continue to go up, and, yes, we will have corrections and everything else, but eventually things will go up, and clearly the last 10 years have shown some of that.

When you think about the experience that millennials have had over the same time period, when they were in high school and college and they’re graduating from college, they ended up in the worst possible financial crisis that we have had in a long time. Therefore, their experience and their skepticism towards investments in equities is probably very different than the experience that baby boomers or Generation X may have had.

MARK: Great insights, Omar, as always. Thanks for being here.

OMAR: Thanks, Mark. Thanks for having me again.

Omar gave us a lot of great advice regarding how to mitigate some of the more prevalent biases.

Here are some additional thoughts on a few of them.

Let’s start with confirmation bias. This is an especially difficult bias to combat. One interesting study looked at how investors interacted with a message board that contained opinions of individual stocks.⁷

The study involved asking investors who used the message board their opinion regarding a set of stocks. The message board was then manipulated to highlight messages about those stocks.

There are two findings from the study I want to highlight.

First, the stronger opinion the investors had about a stock, the more likely they were to click on those messages that supported their belief. That’s the essence of confirmation bias right there. In this study, if the investor had a strong buy or strong sell opinion on a stock, they clicked on messages supporting that point of view 69% of the time. Only 19% of the time did they click on messages that expressed the opposite point of view.

Second, the higher the investor’s self-perceived investment knowledge, the greater their level of confirmation bias.

Let’s go back to the beginning of this episode and the discussion of nosology—the classification of diseases. There are many diseases in the catalog for which there is no cure. The best we can do is manage the symptoms.

In my opinion, confirmation bias is one of those incurable diseases. You can’t cure it, but if you can contain it, then you can reduce the damage.

One treatment is to limit the size of your positions or the amount of money you allocate to a particular stock or strategy. That way, if the strategy turns out to be misguided and you’re unwilling to be deterred, at least you haven’t fully committed to it, so the damage is reduced.

A treatment for herding is to think for yourself. The essence of herding is that you’re making a decision solely because someone else is doing it. That’s plausible if they know more than you, but how do you know that they do? What is their informational advantage? Are they encouraging you to follow them? If so, what’s their motivation? Finally, let’s say you get good answers to all of those questions. Does the investment that the herd is piling into make sense for you given your financial situation and emotional situation?

Just because an investment makes sense for many other people doesn’t mean it makes sense for you.

As for anchoring, one of the reasons it’s so pernicious is that you need to start somewhere. In other words, if you’re going to make an estimate, you need a starting point. Starting with a plausible anchor makes a lot of sense. The problem lies in rationally determining what’s plausible.

One technique that might help you is to get a sheet of paper and write down the reasons why the estimate you’re giving differs from the anchor.

There’s some evidence that this works. The reason is that people think the anchor or starting point is more similar to what they’re estimating than it actually is. You need to focus on the differences in order for them to get proper attention in your estimate, and writing it down by hand helps with that exercise.

Let me give you an example. Let’s say you’re starting to think seriously about retirement and you’re estimating your spending needs.

You don’t know where to start, so you just assume you’ll spend 80% of you’re spending today.

You just created an anchor, and it isn’t a bad one, as the 80% number is a common rule of thumb.

My suggestion to you is to not stop there. Go the extra mile and start writing down all of the ways your spending habits will differ from what you spend today.

Can they be accommodated within the confines of the 80% rule?

Maybe they can and maybe they can’t. Everyone’s situation is at least a little different. Until you take the time to do the detailed work, you won’t know how much you need to adjust away from the anchor to get to an answer that’s right for you.

If you’d like to learn more about the details of some of the biases we discussed today, check out Schwab.com/BehavioralFinance.

Thanks for listening. If you’ve enjoyed the show, tell a friend or colleague and leave us a review on Apple Podcasts and other platforms. Reviews are always appreciated.

If you’re new to the show, you can always go back and listen to previous episodes at Schwab.com/FinancialDecoder.

For important disclosures and a transcript, see the show notes and Schwab.com/FinancialDecoder.

¹ https://en.wikipedia.org/wiki/Nosology

² https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1361216/

³ https://www.3mhisinsideangle.com/blog-post/the-first-nosologists-classifying-disease-in-16th-century-london/

⁴ Amos Tversky and Daniel Kahneman, “Judgment Under Uncertainty: Heuristics and Biases,” Science, 1974.

⁵ Gregory P. Northcraft and Margaret A. Neale, “Experts, Amateurs, and Real Estate: An Anchoring-and-Adjustment Perspective on Property Pricing Decisions,” Organizational Behavior and Human Decision Processes, 1987.

⁶ Ling Cen, Gilles Hilary, and KC John Wei, “The Role of Anchoring Bias in the Equity Market: Evidence from Analysts’ Earnings Forecasts and Stock Returns,” Journal of Financial and Quantitative Analysis, February 2013.

⁷ JaeHong Park, Prabhudev Konana, Bin Gu, Alok Kumar, and Rajagopal Raghunathan, “Information Valuation and Confirmation Bias in Virtual Communities: Evidence from Stock Message Boards,” Information Systems Research, December 2013.