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Consumers display an expense prediction bias in which they underpredict their future spending. The authors propose this bias occurs in large part because: 1) consumers base their predictions on typical expenses that come to mind easily during prediction, 2) taken together, typical expenses lead to a prediction near the mode of a consumer’s expense distribution rather than the mean, and 3) expenses display positive skew with mode < mean. Accordingly, the authors also propose that prompting consumers to consider reasons why their expenses might be different than usual increases predictions – and therefore prediction accuracy – by bringing atypical expenses to mind. Ten studies ( N = 6,044) provide support for this account of the bias and the “atypical intervention” developed to neutralize it.

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The disposition effect is lower in a trading environment with salient information on current holdings. Using proprietary data from a European fintech platform for social trading, we analyze variation in trading behavior within and between private and publicly visible portfolios. The disposition effect diminishes by about 35% when trades and holdings become public. We find the level of transparency and the way financial information is illustrated can influence trading decisions. Our results suggests that requiring greater transparency from portfolio managers can reduce trading bias.