If you're just tuning in, you've found the second blog post in a series of six on behavioral finance. While the first post dealt with the history of the field, this article will dig into five of the most prevalent behavioral biases that trip up amateur and professional investors alike. I know, I know. I said this post would include ten, but that would make it way too long, so stay tuned for the following five shortly thereafter!
Behavioral biases have gotten a lot of attention in the press in the past few years, despite the fact that the first comprehensive study on judgmental heuristics and their biases was published decades ago in 1982 by Kahneman, Slovic and Tversky. Arguably, factors such as fee compression and the active management debate are causing a renewed interest in applying the principles of behavioral finance.
In general, behavioral biases fall into one of two categories: cognitive biases, and emotional biases. Each comes with its own particular set of pitfalls. The first type, cognitive biases, largely results in flaws in logic or reasoning, an inability to gather or employ all the available information in order to make a decision. Because these are logically driven, they can be better overcome with an improved focus on obtaining more complete information and acting accordingly.
In many ways, this makes them an easier set of biases to tackle than their emotional counterparts, which are easy to recognize and hard to correct. To that end, I outline 5 of the most common cognitive behavioral biases below, as well as some implications for investors and analysts.
Have you ever received a phone call from a non-profit asking for a donation? Chances are, they called and requested a highly specific amount: "Did you know that you can get started saving the children/animals/world with just $150?!" It turns out, that specific amount serves as an anchor you adjust downwards (or upwards!) from the initial ask, a form of underreaction. In the words of Kahneman and Tversky (1974), "Different starting points yield different estimates, which are biased toward the initial values. We call this phenomenon anchoring."
In the non-profit world, this means that organizations have every incentive to over-ask, with the goal of getting you to adjust your willingness to give downward, in order to secure your donation. In the financial world, this tendency to rely on the first piece of information can have a number of implications. First, consider the world of earnings surprises. Our tendency to anchor earnings estimates in spite of new information means that frequently, we underreact to changes in expected earnings.
Interestingly, a 2007 Federal Reserve study called "Anchoring Bias in Consensus Forecasts and its Effect on Market Prices" found that monthly economic reports exhibited biases towards the previous month's data ("which in some cases results in sizable predictable forecast errors"), but that market participants may actually anticipate the anchoring bias embedded in expert forecasts.
As it stands, this bias may have more implications for researchers and analysts than those looking to trade on so-called "expert advice." To see how, consider a typical research process: To establish some sort of baseline expectation of an economic forecast or stock price, and then to adjust according to changes in those expectations. It's common sense that we not reinvent the wheel every time we create a forecast, but it is wise that we perhaps be willing to reevaluate our initial estimate from time to time rather than simply anchoring future analysis around an initial study.
While there are certain cases where investors underreact to news, Barberis, Vishnay, and Schleifer (1997) suggest that there are other times where it seems that investors overreact. For example, De Bondt and Thaler's 1985 study "Does the stock market overreact?" finds that between two benchmarks of past "winners" and past "losers," the "winners" tend to underperform going forward, while the "losers" consistently outperformed going forward.
The explanation, according to the authors, can be traced back to overreaction. As high-performing stocks continue to exhibit favorable performance and beat earnings, it is possible that investors overreact to the stock price, which then at some point must correct back to its intrinsic value, resulting in later underperformance.
A corollary to this belief that a trend will persist is the ability to overreact to one-off circumstances - in other words, believing that you have identified a trend when there is in fact none. This includes not only believing that a positive surprise marks a turnaround, but also that a dip represents an apocalypse.
When disaster strikes (or at least perceived disaster), it's only natural to want to adjust the portfolio accordingly. However, acting with incomplete information or on false trends can create big problems for investors' portfolios. If you are dead set on selling securities and exiting positions, portfolio churn can rapidly eat away at returns. In addition, investors may suffer an opportunity cost once the market improves, losing out on the upside of the securities they sold. Obviously, this is an easy behavior for anyone to slip into, and it takes a great deal of discipline to correct.
3. Overconfidence (the Lake Wobegon Effect)
Let's continue our example of overreaction above. You identify a trend, or what appears to be a trend, and you act accordingly. And yet, there's another person on the other side of that trade, looking to profit from your ignorance. Obviously, not everyone can be right… yet the vast majority of people think they are.
What I'm talking about now is a particular bias referred to as overconfidence, also known as the Lake Wobegon Effect, a nod to the fictitious town created by Garrison Keillor for the radio broadcast, Prairie Home Companion. Lake Wobegon, says Keillor famously, is a place "where all the women are strong, all the men are good looking, and all the children are above average."
To put this in investing terms, overconfidence is an unwarranted faith in one's intellect, reasoning skills and investment process. In other words, people assume that they are far smarter and have better information than they actually do - we are ALL above-average investors.
So who is prone to this bias? Well, everyone. But Barber and Odean's 2001 paper "Boys Will Be Boys: Gender, Overconfidence and Common Stock Investment" finds that males exhibit greater overconfidence than females. This overconfidence resulted in elevated trading levels and decreased returns for male traders, though certainly both genders regularly fell prey to this bias.
An additional 2001 paper by Odean and Gervais, "Learning to Be Overconfident," found that traders who are young and successful tend to exhibit the most overconfidence - and therefore trade the most. They link this phenomenon to a sort of self-serving bias wherein the logic is as follows: "If my portfolio goes up, then it's because I am a skilled manager or investor. If the portfolio goes down, it's because of systematic factors that are out of my control." By giving ourselves credit for the wins and not the losses, it's easy to inflate notions of our own skill and become overconfident.
As it happens, this is one of the more "dangerous" behavioral biases, because it so frequently results in portfolio churn, under-diversification and the underestimation of downside risk. To borrow Odean and Barber's phrasing, overconfidence is "hazardous to your wealth." In order to overcome this bias, make sure that you treat wins and losses equally objectively.
In addition, consider not just portfolio return versus the benchmark, but also metrics such as the Sharpe ratio, which allows you to establish whether your excess returns were achieved by taking on undue risk. Finally, carefully consider the sources of risk and return within the portfolio - which holdings did you do well on, and which holdings underperformed? What was your reasoning for buying those holdings? Look for commonalities - a tendency to buy the right stock at the wrong time, the presence of "that feeling" when you trade, etc.
4. Confirmation and Hindsight Bias
In the simplest terms, confirmation and hindsight bias feeds the fire of that little voice in the back of your head that says, "I knew it all along!" Certainly a form of overconfidence where we tend to overstate our own abilities, confirmation and hindsight bias applies to our current perceptions of past occurrences. People tend to believe they made an accurate prediction in hindsight, therefore further contributing to a general sense of overconfidence.
This phenomenon is illustrated in an interesting study by Fischoff, who asked participants to answer general knowledge questions. After revealing the correct answers, he asks those participants to recall their original answers and finds that in general, they tend to overestimate the quality of their original answers. In other words, the correct answers were "so obvious that clearly we must have thought of that."
Arguably, the most dangerous outcome of confirmation bias is that it reduces our ability to identify our own mistakes, and therefore, learn from them. Along the same lines, it allows us to conflate happy accidents with actual skill, making us think our predictions are better than they truly are and causing us to underestimate future risks.
In order to help overcome hindsight and confirmation bias, investors and traders should start by recognizing their own susceptibility. A more tangible practice is to keep full documentation of the rationale for your trades. What are the factors that caused you to buy or sell at a certain time? In the event of under- or outperformance, you can go back to that documentation and revisit your thought process, see what specific judgment errors were made, or what factors positively contributed to performance.
Likewise, maintaining a record of your outlook on the markets and economy is a great way to remind yourself of the mindset you had when making decisions a few quarters ago. Sure, you say you saw that bubble coming, but your previous Q3 outlook might tell you otherwise.
5. Availability Bias
I don't know about you, but my least favorite time to go to the beach is during Discovery Channel's Shark Week. It's a highly illogical quirk, as the statistical probability of being eaten by a shark is actually thirty times less likely than being hit by bits of airplane wreckage falling from the sky. And yet, I rarely look up.
This is an example of availability bias, the tendency to estimate the likelihood of an event occurring based on how frequently we've come in contact with stories of that event, whether it be media coverage, anecdotes from friends or personal experience. We rely on this incomplete information rather than seeking out more complete or factual information.
Related to this is the concept of recency bias: We tend to call to mind the things that we've most recently come in contact with, and base our estimates and predictions off of the ease with which a more particular topic comes to mind.
What's interesting about availability bias is that it's got the obvious markings of a cognitive bias - but not from a lack of willingness to consider full information, but rather the inability to do so. In other words, availability bias can be chalked up not necessarily to poor decisions, but simply to the fact that we revert to these types of heuristics in the absence of being able to fully crunch the numbers.
It is found that the average investor is far more susceptible to availability bias than are institutional investors, often lacking the tools or manpower to run a full analysis. In fact, institutional investors frequently profit from average investors' availability bias. A 2008 study by Odean and Barber - "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors" suggests that filtering out the universe of 7000 stocks turns out to be pretty darn hard.
As a result, average investors tend to trade on the names they see in the news, which unfortunately have a higher propensity to be "hot stocks." These selections are more susceptible to bad market timing and regression to the mean. Institutional investors, on the other hand, tend to be net winners of high trading volume days, as well as less susceptible to relying on attention-grabbing stocks.
To combat this bias, put your "devil's advocate hat" on, and approach every news recommendation or friendly bit of advice with a "what's the worst that could go wrong?" mentality. Understand that the more familiar you are with the name of a company, the more you will feel likely that it's a good buy, so take care to poke holes in your own argument. More importantly, establish a way of picking and finding names about which the media are agnostic, whether through an investment tool such as Morningstar, or even watching out for unknown names here on Seeking Alpha.
So there you have it: Five common cognitive biases. As an investor, do you suffer from these? How do you make sure you have full information before making an investment decision? Chime in, and stay tuned for emotional biases in our next post!
Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.
I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article.