The Motley Fool

The Art of Thinking Clearly: Part 9

Continuing on with this series, here are another three biases and fallacies derived from the book “The Art of Thinking Clearly” by Rolf Dobelli. It pays to be alert and aware of these biases in order to be able to make better decisions and to avoid screwing up our investment thought process.

The problem with averages

When investors line up a list of financial or operating metrics for a group of companies, they may encounter an issue with using averages. Simply put, averages are easily skewed by an anomaly or outlier, such that the average may not make sense anymore. There is no such thing as a “normal” average as it really depends on the sample size and data set chosen.

Be careful when comparing margins or dividend yields, as these numbers may be affected by a company that has an exceptional gain or loss, or has declared a bumper dividend. With such instances, the number may appear very large or small and thus impact the average for the entire group. Always remember to think logically about the data and to remove any one-off effects before analysis.

Information bias

Unnecessary or redundant information is useless and serves as a distraction. Rather than being utilised for optimal decision-making, additional information may end up being counter-productive as it does not bring any added value to the table. The problem is that investors have a tendency to try to gather as much information as they can, believing that this will ultimately enhance the quality of their investment decision.

My experience tells me that bare facts are usually more than sufficient, as too much additional information may serve to confuse rather than assist. In fact, the more information is gathered, the more time is also spent in sifting through what is relevant and what is not. Investors need to learn to do more with less and to avoid being trapped by information bias.

The law of small numbers

When the population size is small, any changes to the population tend to skew the numbers greatly. This has a significant impact when the sample size is small, as changes can have an outsized effect and present more volatility than anticipated. An example given is store dynamics in a small town – as the population of stores and people is smaller, any changes in footfall (due to, for example, a promotion) could alter the store’s economics drastically.

Investors who are examining a niche industry or sector should take note of this law as it could significantly impact the results of their study. When dealing with small numbers, it’s always important to understand the background and context for the numbers so as to avoid being misled by them.

The information provided is for general information purposes only and is not intended to be personalised investment or financial advice.