Mean reversion is a mental model from the field of statistics. It says that an event that is not average will be followed by an event that is closer to the average. I was suffering from the tendency to attribute meaning to a phenomenon governed only by chance.
Daniel Kahneman recounts an experience in his book Thinking Fast and Slow. While teaching flight instructors he was told how the act of praising the pilots on a recent good performance usually resulted in a poorer performance subsequently and vice versa. This logic goes against the conventional motivation theory that encouragement leads to improved performance. According to Kahneman, the flaw in their reasoning was that they had attached a causal interpretation to the inevitable fluctuations of a random process.
As Nassim Taleb wrote in Fooled by Randomness:
The ‘hot hand in basketball’ is another example of misperception of random sequences: It is very likely in a large sample of players for one of them to have an inordinately lengthy lucky streak. As a matter of fact it is very unlikely that an unspecified player somewhere doesn’t have an inordinately lengthy lucky streak. This is a manifestation of the mechanism called regression to the mean….in real life, the larger the deviation from the norm, the larger the probability of it coming from luck rather than skills…This can be easily verified in stories of very prominent people in trading rapidly reverting to obscurity, like the heroes I used to watch in trading rooms.
Here is an interesting insight from the book Innumeracy: Mathematical Illiteracy and Its Consequences:
…very intelligent people can be expected to have intelligent offspring, but in general the offspring will not be as intelligent as the parents. A similar tendency toward the average or mean holds for the children of very short parents, who are likely to be short, but not as short as their parents. If I throw twenty darts at a target and manage to hit the bull’s-eye eighteen times, the next time I throw twenty darts, I probably won’t do as well. This phenomenon leads to nonsense when people attribute the regression to the mean to some particular scientific law, rather than to the natural behavior of any random quantity.
Mean reversion creates two kinds of illusions. The first is the illusion of cause and effect. Out inherent tendency to look for what is causing a measurement to regress toward the mean, an exercise that is frequently fruitless. The second is the illusion of feedback, which makes it seem like favourable feedback leads to worse results and unfavourable feedback leads to better results.
Michael Mauboussin, author of The Success Equation, writes in his book:
Understanding and using the phenomenon of reversion to the mean is essential in making sound predictions [decisions]… Reversion to the mean is most pronounced at the extremes, so the first lesson is to recognize that when you see extremely good or bad results, they are unlikely to
continue that way. This doesn’t mean that good results will necessarily be followed by bad results, or vice versa, but rather that the next thing that happens will probably be closer to the average of all things that happen.
The only reason mean reversion happens is because of randomness. Anytime you hear that mean reversion is happening because of competitive forces, declining moat, etc. wear your lens of mental models and then investigate further. The intensity with which mean reversion affects an activity is directly proportional to the element of luck controlling the outcome in that activity.
In the current world of digital revolution and information explosion, it has become increasingly important for you to build a strong bullshit filter to separate the noise from real knowledge. Mean reversion is one such bullshit filter.