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Don't Get Stuck in Stock Stereotypes

Investors too often use an atypical success story, such as Google, instead of the more common unsuccessful venture, when seeking a basis of comparison for a new investment idea.

Don't Get Stuck in Stock Stereotypes

Jason Stipp: I'm Jason Stipp for Morningstar.

We've discussed a lot of the behavioral pitfalls that investors can fall into as they're making their investment selections, but one you might not have heard about is how stereotyping can impact your investment decisions.

Here to talk about that and some ways we can think about overcoming stereotyping is Raife Giovinazzo. He's director of research at Fuller & Thaler and also a manager at Allianz Global Investors' U.S. Large Cap Behavioral Advantage Fund.

Thanks for joining me, Raife.

Raife Giovinazzo: Thanks for having me.

Stipp: Stereotyping is something that we've heard about in a social sense, but you say it can also impact our investment decisions. You've read some research specifically about how stereotyping impacts us psychologically.

Giovinazzo: Yes. So, stereotyping is making decisions based upon the similarity to some stereotype or archetype of an event, rather than the underlying fundamentals or the true frequency.

A classic psychological experiment examined people's estimated frequencies in likelihood that a person, given a very vague description, was a particular graduate major.

First, there was a question to the students about how frequent are these various majors? And they match the actual frequency, which is humanities are a lot more common than engineering, for example.

Second, they said given this description of a high intelligence but not very creative person who likes tidiness and is neat and orderly--sort of the generic stereotype of what you'd think for an engineering student--they said, how similar is this to your image of this person, your stereotype of this person, and they all said, oh, it sounds like an engineering student.

The third group was asked, what do you think they are? And overwhelmingly people said, oh, it's an engineering student. The answers were 97% correlated with how they rated the similarity, and they were actually negatively correlated with what they'd previously said were the frequencies of the various graduate degrees.

The problem here is, this is a very vague description that they're going off of, and they're completely reacting to the similarity, to the stereotype, as opposed to considering what is the base rate, what is the underlying frequency of this kind of an event.

So, that's the standard research and I'm happy to talk about how it applies to stocks.

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Stipp: I think that we use these mental shortcuts all the time. Right now a hot area of the stock market is social media, and those stocks, because we're all familiar with them. So, when you think about investing and how stereotyping can be applied or misapplied, what kinds of areas do you encounter and what kinds of mistakes do investors make?

Giovinazzo: The problem is that stereotyping is used all the time because it's pretty effective. If you have to make a split-second judgment about something, the stereotype often has some accuracy to it, but of course, when we're investing, we don't need to make a split-second judgment. We can take the time to research and find out what are the underlying facts.

So, with the social media companies, people are thinking it's the next Google, maybe they should worry that it's the next Groupon that's going to go down after this, that isn't as hot. But it's very common for people to think about the stereotypes of how similar is this to the thing that I'm most familiar with?

Often the thing you're most familiar with in stocks is the one that's been most successful. Unless it's a horrible failure and then you hear a lot about it, the [companies] you're going to hear a lot [about] are the ones that were the successes. You're going to forget all the ones that faded away into the dustbin of history. And therefore, your stereotypes are going to be with the successful ones, not with the ones that perhaps [represent] the actual frequency of how often these kinds of companies succeed.

Stipp: And those successful ones, the Googles of the world, are one in several hundreds or even thousands that try to become the next Google, but aren't able to.

Giovinazzo: Yes.

Stipp: So, as an investor that's looking at these behavioral mistakes, how can you tell if the stereotyping is occurring? What signals in the market might indicate that people are doing this behavior?

Giovinazzo: It's hard to know exactly that stereotyping is happening, but one thing that we look at are the indications that there are overhyped stocks in the marketplace. We look at excess trading volume, things like excess volatility. Basically, excess attention to a stock out of whack their actual importance in the stock market. I think you definitely see this in the social media companies.

We all kind of know why, because we're all using these things in our own personal life. So we think, well, I know what they are, I'm talking about them. It's easy to translate that into the stock market. It's a little bit what happened with the Internet bubble--people got excited about using the Internet in their personal life and concluded, well, people providing these services are going to make millions and billions and trillions of dollars, and it didn't work out that way.

Stipp: So, when you're trying to overcome this stereotyping bias, what are some steps that you can take to make sure that you're not misapplying what you think you know about one company or one sector to another company and maybe even another sector?

Giovinazzo: I would say three things:

One is to try to take a broad view and try to look at the big picture about all the things that could be out there--and maybe if it helps to use stereotypes for good, think of some opposite stereotypes than the particular ones that come to mind. If you think it's the next Google, think, or is it the next Groupon? How to do I check?

The second thing I would say is to avoid the confirmation bias. We've talked about this previously, that the confirmation bias is the tendency to look for confirming evidence as opposed to disconfirming evidence. So, it's easy if you get into the mindset of, oh, this is next Google, and to find things that are similar. You need to purposely say, what are the things that are different that should make me disbelieve this similarity?

The third thing I would say is to try to look at the underlying base rates, … and this is, again, similar to a broad perspective… when I look at all of the categories of this kind of stock--new IPOs would be a category, even new media companies. Let me look at the full set of data and see, how often does it happen that these kinds of companies succeed, or this new product succeeds, or whatever it is, so that you look and ground your judgment in the base rates, not just in the similarity of some particular example that you have in mind.

Stipp: All right, Raife, thanks for helping us overcome some of our mental pitfalls and joining me again.

Giovinazzo: Thank you.

Stipp: For Morningstar, I'm Jason Stipp. Thanks for watching.

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