Human vs. Machine: Disposition Effect Among Algorithmic and Human Day-traders


Can humans achieve rationality, as defined by the expected utility theory, by automating their decision making? We use millisecond-stamped transaction-level data from the Copenhagen Stock Exchange to estimate the disposition effect – the tendency to sell winning but not losing stocks – among algorithmic and human professional day-traders. We find that: (1) the disposition effect is substantial among humans but virtually zero among algorithms; (2) this difference is not fully explained by rational explanations and is, at least partially, attributed to prospect theory, realization utility and beliefs in mean-reversion; (3) the disposition effect harms trading performance, which further deems such behavior irrational.