Biases and Investment Decisions
Finally, the fourth main area of Behavioural Finance study we will examine is biases. A cognitive bias is defined as the common tendency to acquire and process information by filtering it through personal likes, dislikes, and experiences. Our biases influence how we receive and use information when making decisions. Our biases play a role in every aspect of our lives and, in particular, our biases impact our investment decisions.
Psychologists and behaviourists have identified dozens and dozens of cognitive biases that play roles in our lives. Below we have selected a few that unfortunately can influence investors in their decision making process:
- Survivorship bias
- Confirmation bias
- Escalation of commitment
- Ostrich effect
- Publication bias
- Reporting bias
Survivorship bias is one of the most prevalent influences when processing information and making decisions. It is described as the distortion that occurs when only the survivors of some event or process are considered and the failures are excluded from the data and/or analysis. For investors, Survivorship bias is prevalent within individual stock market indices, investment performance calculations, and data sets.
Example: A simple example of survivor bias influencing economic data and our subsequent conclusions could be the government’s Retail Sales Survey. For a little background, each month governments survey retailers and publish the data. The Retail Sales Survey is meant to capture the recent purchasing activity of consumers. Investors tend to view this survey results as important because approximately 70% of developed western economies are based upon the activities of their individual consumers. Thus, the theory is, if consumers are feeling financially healthy, they will tend to consume more and this increased consumption will be revealed in the monthly Retail Sales activity reported by the government survey. A healthy, confident consumer will lead to a healthy economy and a healthy economy will lead to a rising stock market.
Unfortunately, with the Retail Sales Survey, there does come a point in an economic slowdown where Survivorship bias can cause the data to begin improving without any actual improvement in the economy.
Example: Let's assume that you own a grocery store that employs 15 people in a small town. In addition, your town supports two other grocery stores. Each month the government calls to collect data for its Retail Sales from each of the three grocery stores. For the first six months of the recession all three stores report declining sales as local people lose their jobs and cut back on their spending. In the seventh month, you decide to close your store and lay off your 15 employees. You just could not hang on any longer. Next month when the government calls the two remaining stores, low and behold, both stores report an increase in sales, and the government’s Retail Sales Survey shows a marked improvement. This improvement subsequently appears as headlines in the news and investors interpret this improvement as a sign the economy has begun to improve. But the reality is that not only is the economy in your town worse, but now your 15 employees are unemployed.
Note: This is a simple example of Survivorship bias impacting data and it can cause serious distortions. Survivorship bias can lead to overly optimistic beliefs because failures are not included in the information analyzed. Stock market indices are also victims of Survivorship bias when their quarterly adjustments consistently replace failing companies with healthy growing companies. Mutual fund companies often merge poor performing funds with better performing funds and have the “new” combined fund adopt the better fund’s historical performance data, thereby eliminating the poor fund’s data.
Confirmation bias describes the tendency for individuals to search for and read information that confirms their accepted views and ignoring information that might oppose their beliefs. As a result, people collect and process information in an unbalanced way leading them to make decisions based upon a narrow and supportive data set. Confirmation bias can lead investors to ignore important information that might otherwise alter their decision. In addition, Confirmation bias can cause investors to hold on to losing investments even when the evidence suggests that it should be sold.
Studies have demonstrated that people tend to search for evidence that supports their beliefs, not information that contradicts them. Not only is their search for information biased toward their beliefs, but their analysis is also biased. Two individuals can collect the same information, but the method that each interprets the information may also be biased. For example, when reading a news article our Confirmation bias helps us to place greater importance on those points that support our beliefs and ascribe less importance to those that did not.
Note: Investors and analysts are both subject to Confirmation bias – investors when they read a report and analysts when they write the report. Analysts will write their reports emphasizing the supportive information and subordinating or omitting information that might weaken the basis for their recommendation.
Confirmation bias also helps to support Escalation of commitment and the Ostrich bias, each of which are discussed below.
Escalation of commitment
Also referred to as Sunk Cost Fallacy, the Escalation of commitment bias describes the phenomenon where investors justify increasing their commitment to a losing investment and buy more. This bias is often referred to in age-old sayings such as “In for a penny, in for a pound,” and “Throwing good money after bad,” or “Averaging down.”
Despite the investment’s lost value and evidence that the investment is not worth buying today, investors will consistently add new money to the losing investment. Typically, the additional investments are accompanied with the statement, “If it gets back to what I have invested, I’ll sell.” More often than not, by refusing to acknowledge that the investment’s future prospects have changed and give up on it, investors will add to the deteriorating investment hoping to lower the investment’s per-share cost, thereby hopefully making the recovery of their investment easier.
Escalation of commitment is derived from an investor’s fear of loss and their overconfidence. They try to manage or salvage a losing investment by adding to it and their overconfidence does not allow them to accept they may have been wrong to make the investment in the first place.
The Ostrich effect comes into play when you are faced with apparently risky financial situations and pretend they do not exist. The name is derived from the myth that ostriches will bury their heads in the sand when confronted with danger.
Many investors act like ostriches by not looking at their investments during terrible stock market cycles. They try to avoid disappointment by ignoring their investments or by pretending that their investments are fine. They tell themselves, “Don’t worry about the investment’s decline in value, it will come back in time.”
Studies have been conducted that show investors will review their investments 50% to 80% less frequently during difficult investment market cycles than they do in good investment market cycles.
This behaviour is precipitated by an investor’s fear of loss, fear of regret, fear of making a dumb decision, and a lack of a strategy to deal with investing disappointments. Most investors plan their investment strategies for buying investments, not selling, and for investing in rising cycles, not declining investment cycles. As a result, investors do nothing, just like an ostrich, when confronted with danger.
This describes the tendency of writers and publishers to handle the reporting of positive outcomes differently than they do negative outcomes.
Investment analysts, strategists, advisors, and newspapers have a history that emphasizes positive results and outcomes by over-reporting positives and under-reporting negatives. This bias may be driven by their audience’s demands or by their own preferences, but either way as an investor we are much more likely to read and receive positive information than we are negative.
This bias can often lead investors to make decisions based upon information that is unbalanced toward the reasons we should buy and hold an investment. There is an old anecdote about Publication bias that goes something like this: “A scientist recently published the results of his exhaustive study into a new drug that fights cancer. When the drug was administered to chickens, one third showed significant improvement, one-third showed no improvement, and unfortunately, the third chicken ran away.”
In the world of investments, investors are constantly faced with positive Publication bias. How many times have we read that a company’s quarterly earnings have “exceeded the analysts’ expectations”? The company’s quarterly earnings might be 90% lower than they were in the year ago period, but analysts had expected the earnings to be down 95%, and thus, a 90% drop is reported as exceeding analysts’ expectations.
Reporting bias is associated with a tendency to under-report unexpected or undesirable results or outcomes. Negative or undesirable results are often associated with some degree of sampling or measurement error and are therefore reported and read with less importance. This bias toward doubting the validity of negative outcomes causes readers to place greater importance on positive outcomes than is associated with negative outcomes.
In general, Reporting bias can take many forms. A few are listed below:
- Time-lag bias: Depending upon the nature of the research results, the report may be delayed or published quickly.
- Duplicate publication bias: Positive results are more likely to be reported more frequently than negative results. Positive outcomes are more likely to be reported repeatedly; where as negative outcomes are less likely to be.
- Location bias: Results may be published in different locations depending on the outcomes reported. For example, newspapers and experts may publish positive data more prominently and frequently than they would negative data. A negative statistic may only be reported by the agency that calculates it, whereas a positive statistic might be published by the agency, by experts and by newspapers.
Remember: Behavioural Finance is an interesting, broad field of study showing us how our behaviour impacts our investment decisions. Put simply, every investor, analyst, economist, professional money manager, trader and investment strategist is a victim of his or her emotions, mental framework, mental anchors, and biases!