I think it is critical that we shed light on different types of risks that we are exposed to as investors. However, risk comes in many forms and sometimes we are the risk ourselves, and that is what I will be writing about in this blog post.
Imagine that you have found an attractive investment. You have done your due diligence and scrutinize every part of the company. You have read all the fine print about the company; what it is up to in the future; read about the Board of Directors and the management; gone through every item in the financial statements; done cash flow analysis, and screened the key ratios with other companies in the sector and so on. The only thing you have left is the invest. Well, that is a great start (!) but (there is always a but) there is something I want you to think about during, and after, your due diligence, and that is to assess your bias for your investing decision.
Introduction to Cognitive Biases
(Hull, 2015, pp. 572-574)
Our ability to identify risks effectively is affected by what are termed cognitive biases. These describe the tendencies for human beings to think in certain ways and be less than perfectly rational. One common cognitive bias is wishful thinking. It is sometimes difficult to distinguish between what we want to happen (e.g., a project to be a success) and what we think will happen. (Try asking a Manchester United supporter to estimate the chance of Manchester United winning the FA Cup next year!) When we want something to happen, we are liable to think only of reasons why it will happen.
Over 100 cognitive biases have been listed by psychologists. Much of the pioneering work was done by Daniel Kahneman and Amos Tversky.8 Kahneman won the Nobel prize for economics in 2002 for his work with Tversky on prospect theory, which is concerned with the way people choose between risky alternatives. (Tversky had died a few years earlier.) One important bias is anchoring.
When evaluating a potential outcome (e.g., the revenue resulting from a major new venture), we are liable to anchor onto the first estimate that is made. We tend to make relatively small adjustments to that estimate (this is referred to as “anchoring and adjustment”) and often never consider the full range of possible outcomes. In particular, important adverse outcomes may implicitly be considered to have no chance of occurring. To illustrate anchoring, one could ask a group of people to make a best-guess of something that is unknown to them such as the population of Iceland. They can then be asked to provide a range consisting of the 5th percentile to 95th percentile of their subjective probability distribution. If their estimates are good, the true population of Iceland should lie outside the range only 10% of the time. In practice, it is found that this happens much more frequently. Anchoring causes people to behave as though they know more than they do.
Another cognitive bias is availability. This is where recent information is given undue weight. Sadly, risk management can suffer from availability. Prior to the credit crisis, risk managers in some financial institutions were often not listened to because recent experience had been good. After the crisis, risk managers have had more influence, but as memories of the crisis fade, the “good times will last forever” attitude may return.
Another cognitive bias is known as representativeness. This is where individual categories a situation based on a pattern of previous experiences or beliefs about the underlying scenario. It can be useful when trying to make a quick decision, but it can also be limiting because it leads to close-mindedness and stereotyping. Based on previous experience, a senior manager at a financial institution might consider it almost impossible for any other financial institution to compete successfully with it in a particular market. However, if the manager’s past experience is limited, the previous situations might not be representative of future scenarios.
A mistake sometimes made in estimating probabilities is inverting the conditionality. Suppose that 1 in 10,000 people have a particular disease. A test that is 99% accurate gives you a positive result (suggesting that you have the disease). What is the chance that you have the disease? Your immediate response is likely to be 99%. However, the true answer is actually about 1%!
Out of 10,000 people there will be about 100 positive results on average but only one person with the disease. Hence, the probability we are interested in is about 0.01. This is an application of the result in probability theory known as Bayes’ theorem.
Yet another bias is the sunk costs bias. Suppose that a financial institution has already spent $1 billion trying to enter a new market. Things are not going well, and there seems very little prospect of success. Should the $1 billion influence the financial institution’s decision making? The answer is the $1 billion is what accountants refer to as a sunk cost. Regardless of the decisions taken now, it cannot be recovered.
The key issue is whether future profits will be sufficiently high to justify future expenditures. In practice, many people are reluctant to admit mistakes, and they continue with projects that are clearly failures for too long. Irrationally, they want to try to get back money already spent, even when the chance of this is very small.
Understanding these biases may assist decision making and the identification of key risks. It should be noted, however, that experiments have shown that it is extremely difficult to eliminate biases. Even when biases such as anchoring are carefully explained and subjects are given financial incentives to make good estimates, the biases persist.
The challenge with investments is identifying tail risks and trying to estimate the probabilities associated with the adverse scenarios giving rise to the tail risks as well as possible. The cognitive biases we have discussed (and many others have been documented) suggest that the risks will be underestimated. Nassim Taleb is particularly critical of the use of normal distributions for calculating risk measures and argues that extreme events such as the crash of 1987 or the credit crisis of 2007 to 2009 are more likely than many people think.
Other Important Cognitive Biases
Confirmation Bias (Investopedia, 20161)
Confirmation bias can create problems for investors. When researching an investment, someone might inadvertently look for information that supports his or her beliefs about an investment and fail to see information that presents different ideas. The result is a one-sided view of the situation. Confirmation bias can thus cause investors to make poor decisions, whether it’s in their choice of investments or their buy-and-sell timing.
For example, suppose an investor hears a rumor that a company is on the verge of declaring bankruptcy. Based on that information, the investor is considering selling the stock. When he goes online to read the latest news about the company, he tends to read only the stories that confirm the likely bankruptcy scenario and he misses a story about the new product the company just launched that is expected to perform extremely well. Instead of holding the stock, he sells it at a substantial loss just before it turns around and climbs to an all-time high.
Confirmation bias is a source of investor overconfidence and helps explain why bulls tend to remain bullish and bears tend to remain bearish regardless of what is actually happening in the market. Confirmation bias helps explain why markets do not always behave rationally. However, an investor who is aware of confirmation bias may be able to overcome the tendency to seek out information that supports his existing opinions and intentionally seek out contradictory advice.
Survivor Bias (Freakonomics, 2009)
The concept of survivor bias, if you don’t know it, is well worth being aware of. It’s most often used in finance, where it refers to a “tendency for failed companies to be excluded from performance studies”. Think of the Dow Jones Industrial Average, which indexes the stock prices of 30 of the largest and most important U.S. companies — until, that is, one of said companies does so poorly that it is booted from the index and is replaced by a company that’s doing better.
Over time, therefore, the DJIA reflects a different reality than many people presume. It is biased toward survivors — or, if you want to think of the concept more broadly, toward winners.
This winner’s bias, if you will, shows up in pretty much every realm imaginable: academics, medicine, politics, etc. I don’t mean to sprinkle skepticism all over your inherently positive thoughts about the world, but I do think it’s worth keeping winner’s bias in mind whenever you read (or write) something about the performance of a given group or institution or coalition.
Winner’s bias is perhaps especially pronounced in sport. The behaviors of winners are remembered and dissected far more thoroughly than those of losers, and given greater weight, even if the outcome was decided by a tiny margin.
Endowment Effect (Investopedia, 2016b)
Studies have shown repeatedly that people will value something that they already own more than a similar item they do not own. According to the old saw: a bird in the hand is worth two in the bush. It doesn't matter if the object in question was purchased or received as a gift, the effect still holds. People who inherit shares of stock from deceased relatives exhibit the endowment effect by refusing to divest those shares even if they do not fit with that individual's risk tolerance or investment goals, and may negatively impact a portfolio's diversification. Determining whether or not the addition of these shares negatively impacts the overall asset allocation is appropriate to reduce poor outcomes.
This bias applies outside of finance too. A well-known study which exemplifies the endowment effect, and has been replicated over and over, starts with a college professor who teaches a class with two sections: one which meets Mondays and Wednesdays and the second which meets Tuesdays and Thursdays. The professor hands out a brand new coffee mug with the university's logo emblazoned on it to the Monday/Wednesday section for free as a gift, not making much of a big deal out of it. The Tuesday/Thursday section receives nothing. A week or two later, the professor asks her students to value the mug. The students who received the mug, on average, put a greater price tag on the mug than those who did not. When asked what would be the lowest selling price of the mug, it consistently averaged significantly higher than where the students who did not receive a mug would pay for it.
Home Bias (Investopedia, 2016c)
Investing in foreign equities tends to lower the amount of systematic risk in a portfolio because foreign investments are less likely to be affected by domestic market changes.
However, investors from all over the world tend to be biased toward investing in domestic equities. For example, an academic study from the late 1980s showed that although Sweden possessed a capitalization that only represented about 1% of the world's market value of equities, Swedish investors put their money almost exclusively into domestic investments.
Freakonomics. (2009). Survivor Bias on the Gridiron, Freakonomics, Available Online: http://freakonomics.com/2009/09/17/survivor-bias-on-the-gridiron/.
Hull, J. C. (2015). Risk Management and Financial Institutions, 4 edition., Hoboken: Wiley.
Investopedia. (2016a). Confirmation Bias Definition, Investopedia, Available Online: http://www.investopedia.com/terms/c/confirmation-bias.asp.
Investopedia. (2016b). Endowment Effect Definition, Investopedia, Available Online: http://www.investopedia.com/terms/e/endowment-effect.asp.
Investopedia. (2016c). Home Bias Definition, Investopedia, Available Online: http://www.investopedia.com/terms/h/homebias.asp.