Nobel Laureate Robert Schiller has referred to investing as ‘a social activity.’ Why is that, and do you agree with him?
Yes, although ‘active investing’ is more prone to social influence than ‘passive investing.’ Passive investing is typified by a buy-and-hold portfolio strategy for long-term investment horizons, with minimal trading. It doesn’t require much interaction and you don’t need to follow up with anyone; you just passively receive updates over time, but you can otherwise forget about it.
On the other hand, active investing involves frequent trading, with the goal of beating average index returns. When an investor is buying individual stocks of a company, they often look for tips on social media, or they might ask their friends what looks good. In one survey, individual investors were asked what drew their attention to the firm whose stock they most recently bought. Almost all of them referred to direct personal contact — and personal interaction was also important for institutional investors. To quote Schiller, that’s because “Investors spend a substantial part of their leisure time discussing investments, reading about investments or gossiping about others’ successes or failures in investing.”
In my recent paper with David Hirshleifer (University of California/Irvine) and Johan Walden (University of California/Berkeley), we explored how heuristics (‘rules of thumb’) and biases in social interactions promote the adoption of personal investing decisions. Getting information from our social networks is quick and efficient, but in the investing realm, this phenomenon had not yet been studied.
Talk a bit about how biases creep into active investing.
Both receivers and deliverers of investment-related information are subject to heuristics and biases. When we make decisions in life, we often don’t have the time or resources to compare all of the important information before we make a choice. So, we use heuristics to help us reach decisions quickly and efficiently. There can be biases in many aspects of active investing: how information is communicated, what the receiver bases their decision on, and how they react to the communicated information, to name a few.
The bias at the root of our study is on the information deliverers’ side, and we call it ‘Self-Enhancing Transmission Bias,’ or SET. Put simply, it means that people really like to share investment information that enhances their image. We all want other people to view us in a favourable way and project that we know what we’re doing. In the investing realm, this can translate into an investor saying something like, ‘Hey everyone, listen up; I made a killing on this stock last week.’ The problem is, SET also involves leaving out any information about losses that were incurred during the same period. People aren’t exactly lying, but they often selectively omit certain information in order to make themselves look good.
People selectively omit certain information
to make themselves look good.
On the receivers’ side, the ‘representativeness heuristic’ is particularly common. People over-weight past returns and are subject to ‘selection neglect’. This means they don’t consider the fact that they will disproportionately receive messages about high rather than low returns. We also found that investors pay greater attention to messages about extreme returns, whether they be positive or negative. When cognitive processing power is limited, a focus on extremes is a useful heuristic. In fact, research indicates that extreme cues are more salient than moderate cues in a wide variety of settings.
How does this attraction to extremes manifest itself in investing?
If there is a stock that has gone up in value since an investor purchased it, that investor is much more likely to talk about this at work, over a meal with friends or on social media. And as a listener seeking tips and good advice — which is pretty much everyone — if you don’t adjust for SET, you can easily be fooled into thinking that you should copy what that investor did.
We can force financial firms to disclose specific material information, but we can’t force people to tell the whole truth in every circumstance. That’s why investors have to be so cautious when they hear something about a high-performing stock from an acquaintance, on TV or on social media. My advice is, never take what people say at full face value. By the way, the same principle holds true for communications coming out of investment firms: it’s all about how they phrase things. A firm can tailor a message to try to stoke positive sentiment, and investors need to be aware of that.
Why are investors so attracted to high risk investments?
When individual investors start picking active investments, they tend to be high risk ones, measured by high volatility and ‘skewness.’ If you ask the person why they made this investment, they will often say, ‘I heard a lot of great things about it, and I trust my friends’. Whenever you rely on friends, colleagues or ‘experts’ for stock tips, there is always some level of naive thinking going on. That’s because, as indicated, bad experiences are very much underreported, and that gives an investor impression that highly volatile investments tend to have better performance than ‘boring’ passive investments.
When people make a lot of money on a stock, they talk about it on social media or at a gathering, and then other people jump in on the bandwagon. But if you follow up down the road, you usually see that the stock has come back to earth. For example, look at Netflix. They have had a really good last three years but recently, they have come back to earth — back to where they were in 2018. So stock bubbles can burst quickly. The fact is, a few people will make money in a stock bubble — the lucky ones — but most investors are better off investing the passive way. It’s like when you buy a lottery ticket: on average, people know they will lose money. But because they’ve seen media reports and advertisements about the luxury lifestyles of the few lucky winners, they choose not to think about the other 98 per cent of people who got nothing for their ticket.
Social environments can have significant
effects on economic outcomes.
One reason why people continue to invest in very speculative stocks — and why there is often a lack of diversity in portfolios — is that diversification and passive investing are both about reducing risk; and everyone knows, when you reduce risk, you lower your chances of ‘making a killing.’ Let’s face it, nobody wants to talk about earning 1% on an investment. In order to have bragging rights, you have to take risks. You need to try and find the next Twitter or next Tesla, before they take off or a bubble forms. That’s why people area always actively searching for tips.
Talk a bit more about the appeal of ‘high skewness’.
As indicated, the best example of a positive-skewed investment is a lottery ticket. The possibility of an extreme positive outcome is what attracts people to high-skewed investments. But that attraction tends to place upward pressure on price and can lead to return anomalies. Our model offers an explanation for the overvaluation of volatile or ‘lottery-like’ categories of stocks, which include growth stocks, distressed firms, firms that have recently undertaken IPOs, and heavy trading and overvaluation of firms that are attractive as topics of conversation (e.g. sports, entertainment and media firms, or firms with hot consumer products.) Put simply, higher variance and skewness promote the spread and adoption of influential investment strategies.
How would you summarize the takeaways from your research?
The traditional framework for investing entails doing your own research and conducting statistical analysis using cyclical data. But that’s not what we studied; we looked at the social aspects of investing, which explains how really bad investment ideas can catch fire and propagate in the investor community.
Our social approach to investment decision making and asset pricing accounts for the non-rational processes by which ideas are transmitted between investors in their social networks. Active strategies (i.e. those with high volatility, skewness, and personal engagement) spread the most after they experience high returns. As returns are realized, investors communicate with and persuade each other over time. This suggests that variations in the social environment that may seem unimportant at the individual level can actually have significant effects on economic outcomes. Our model suggests that a shift in the social acceptability of talking about one’s successes, or of discussing personal investments more generally, can have large effects on risk taking and active investing. In sum, sociability, SET and other features of the communication process for investment information collectively determine the popularity and pricing of active investments.
What are the implications for investors?
People need to be skeptical about all the information out there—especially on social media. You always need to consider what the deliverer of the information didn’t tell you. From a personal finance perspective, you should only listen to experts when their views are the result of research based on statistical analysis rather than anecdotal evidence, because anecdotal evidence is very likely to be biased to focus on positive messaging.
Whenever advice is coming from an investment group or someone on TV, the fact is, they may be trying to sell you on their investment services. If this is the case, they are smart enough to know how to frame their messaging to make you believe they know what they’re doing. We advise investors to do their own due diligence and to consider people’s incentives and hidden (or absent) messages. Social media can be a valuable source of information, but when it comes to investing, people need to be very cautious. Social environments can have significant effects on economic outcomes.
Bing Han is the TSX Chair in Capital Markets and Professor of Finance at the Rotman School of Management. His paper, “Social Transmission Bias and Investor Behavior,” appeared in the Journal of Financial and Quantitative Analysis.
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