Self-attribution bias

A good year in a rising market can feel like proof of skill, even when the market itself did most of the work. Self-attribution bias is the tendency to take that credit anyway — and to explain away the losing trades as someone else's fault, or plain bad luck.

The workbook links it directly to overconfidence bias: the more an investor's wins get attributed to their own judgement, the more overconfident they become, which in turn makes the next round of self-attribution even easier to fall into.

Two passages in the workbook describe the mechanism. On overconfidence: "With illusion of superior knowledge, overconfidence bias is intensified when combined with self-attribution bias, where people confuse brain with bull market." On market anomalies: "Under self-attribution bias, investors tend to take credit for successes and blame others for failures. They follow information that supports their beliefs and disregard conflicting information."

Illustrative figures, not from the workbook. Consider an investor who places 10 trades in a rising market and profits on 7 of them. Under self-attribution bias, all 7 wins are filed away as evidence of stock-picking skill, while the 3 losses are attributed to "bad luck" or a "market manipulation" the investor could not have foreseen — rather than to the same skill (or lack of it) that produced the wins. The selective filing is what the workbook means by following confirming information and disregarding conflicting information: the investor's own trading record is read in whichever direction supports the belief that they are skilled.

Illustrative figures. Mr Anil Bhatia, a retail investor in Surat, made 12 stock trades during the 2021 bull run and profited on 9 of them. He credits his own "stock-picking instinct" for all 9 gains, and attributes the 3 losses to "the FIIs pulling out" — a factor he never mentions when a trade goes his way.

By early 2022, convinced of his skill, he concentrates two-thirds of his portfolio into three small-cap stocks he has "researched" — in reality, stocks that happened to rise in the earlier bull run. When the market corrects, his concentrated portfolio falls 28%, against a diversified peer's 9% drawdown over the same period. Because his earlier gains were attributed to skill rather than to a rising market, self-attribution bias left him with no reason to question the concentration until the loss had already happened.

Chapter 14, section 14.5.1 (Market Anomalies), names self-attribution bias as one of the behavioural biases that produce anomalies — alongside overconfidence and the disposition effect. Expect a question distinguishing self-attribution bias from plain overconfidence bias, since the workbook treats them as linked but separately named biases.

• Self-attribution bias is not identical to overconfidence bias. The workbook treats self-attribution as a bias that intensifies overconfidence — related, but separately named, and both can appear as distractors for each other.
• It involves selectively filtering information — following what confirms the investor's belief in their own skill and ignoring what contradicts it — which is why it compounds over time rather than self-correcting.
• It is distinct from the disposition effect, which is about holding losers too long and selling winners too early — self-attribution is about how an investor explains wins and losses after the fact, not about which positions they hold onto.