Here are another three biases and fallacies taken from the book “The Art of Thinking Clearly” by Rolf Dobelli.
It’s been enlightening in reviewing this long list of psychological biases that may trip you up.
In case you missed them, here are the links to the first seven parts of this series.
Part 1 – click HERE
Part 2 – click HERE
Part 3 – click HERE
Part 4 – click HERE
Part 5 – click HERE
Part 6 – click HERE
Part 7 – click HERE
You need to be alert for such biases as they can screw up your investment thought process and cause you to make costly mistakes.
The problem with averages
You have to be very careful when dealing with averages.
There is no such thing as a “normal” average, as each data set is unique and may be vastly different, thus making them incomparable.
Also, if there is an anomaly or an outlier (i.e. a statistic which differs greatly from the norm), this occurrence will skew the average significantly.
An example would be the comparison of dividend yields in a data set of 10 companies within an industry.
Nine of these companies may have dividend yields ranging from 2% to 4%, but one of the companies may sport a dividend yield of 20%, perhaps due to a special dividend from the divestment of a large asset.
This is a one-off payment of a special dividend but distorts the underlying “core” dividend yield for that company.
As a result, the average of all 10 companies may shoot up to 7% or 8%.
This statistic may provide the investor with the wrong impression as he may believe that the industry sports a high overall dividend yield.
Such instances may also occur with gross or operating margins as well as valuation metrics such as price-earnings or price-to-book ratios.
Hence, it pays to be careful when dealing with averages; instead, you can try using the median.
Information bias
Sometimes, bare facts are good enough for you to make an investment decision.
Some investors, however, try their utmost to obtain all the information they can lay their hands on.
It’s not unusual to hear of fervent investors who go about gathering the most comprehensive set of data, whether for their use or bragging rights.
However, excessive knowledge may turn out to be a waste of time as it will end up being both worthless and a distraction.
Gathering too much information ends up being counter-productive and will not add value to the quality of the decision.
Investors need to be mindful that quality decisions can still be made even if they do not have complete information, as there will always be an element of uncertainty and probability in all investing decisions.
The law of small numbers
This law relates to how averages may be skewed significantly when we are dealing with a small sample size.
A good example of this would be small retail stores that have more volatile economics (such as same-store sales or footfall) compared to larger stores as they have a smaller base.
Any changes will therefore exert an outsized effect.
Investors need to be wary when dealing with small data sets or sample sizes and to be mindful of how small absolute changes may result in large percentage changes.
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Disclosure: Royston Yang does not own any of the companies mentioned.
