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Illusion of correlation



Can you cancel an important initiative because of a black cat?

B. Venkatesh

An analyst I know never initiates a research report on Tuesdays. He claims that his recommendation is likely to go wrong if he does so. He bases his argument on what happened the last time he did that — he had issued a report on Bajaj Hindustan on a Tuesday and the stock later fell 15 per cent! You may also suffer from similar such beliefs. It is called “Illusion of correlation”. What does it mean?

We typically see a correlation even when none exists. Take the black cat effect. There is this belief that if a black cat crosses our path when we leave for an important work, the initiative is likely to fail. Never mind the origin of this superstition. The last time we crossed a black cat, our mission, perhaps, failed. So, we may conclude that a black cat crossing our path is, indeed, bad omen. That is the illusion of correlation.

Random mix of events

Why is it an illusion? Take the analyst. He, perhaps, does not remember the number of times that he initiated new reports on Tuesdays and nothing happened. When we believe our premonitions correlate with events, we only remember the times that both occur.

Psychologists have conducted extensive study in this area. One such study showed people the results of a hypothetical 50-day cloud-seeding experiment. The results showed the days when the cloud had been seeded and the days when it rained. The information was simply a random mix of results. Yet, people were convinced that cloud-seeding caused the rain!

The point is that we are more likely to remember instances when correlations exist. How is this understanding related to economics?

We arrive at decisions based on references. Correlation is one such reference point. The analyst delaying the report by one day may not have much impact. But what if you decide not to invest in equity because the market crashed the last time you did? Or what if you cancel an important initiative because of a black cat? Your economic decisions would then be sub-optimal.

(The author is an investment strategist.)

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