Self-Attribution Bias – Don’t Confuse Brains With a Bull Market!

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Self- attribution bias (or self-serving attributional bias) refers to the tendency of individuals to ascribe their successes to innate aspects, such as talent or foresight, while more often blaming failures on outside influences, such as bad luck. There are actually two kinds of self-attribution bias, namely self-enhancing bias and self-protecting bias.

Self-enhancing bias represents people’s propensity to claim an irrational degree of credit for their successes, for example, if people intend to succeed, then outcomes in accordance with this intention will be perceived as the results of them acting to achieve the intention, regardless of whether the actions indeed played a crucial role.




Self-protecting bias represents the corollary effect – the irrational denial of responsibility of failure, for example people trying to maintain their self-esteem by protecting themselves psychologically as they attempt to comprehend their failures.

Irrationally attributing successes and failures can impair traders in two ways. First, people who aren’t able to perceive the mistakes they’ve made are, consequently, unable to learn from those mistakes. Second, traders who disproportionately credit themselves when desirable outcomes do arise can become detrimentally overconfident in their own market savvy, leading to overconfidence bias.

When trades turn out well, people like to think that their method or analysis was fantastic, and that they are good traders. When trades do not turn out well, people will blame their broker, their platform, the news – basically anything but themselves. As you can see, over time, this leads traders to think that they are much better than they actually are.

What is the best solution for this?

One way to overcome this bias is to treat both winning and losing trades as objectively as possible, tabulating and recording them to obtain a running record. It also helps to do an objective post-trade analysis, reviewing your records to learn from past mistakes. With sufficient data, one can then objectively analyse the consistency of the methods and returns, and as they say – the numbers do not lie.

“Don’t confuse brains with a bull market.”

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