Recency Bias

Recency bias causes investors to treat the most recent period of market behavior as the template for what lies ahead. After a prolonged bull market, investors assume equities will continue rising; after a sharp drawdown, they expect further declines. Neither expectation is grounded in analytical rigor — both are pattern-matching errors rooted in the vividness and accessibility of recent memory.

The bias has measurable consequences for capital allocation. Research on fund flows consistently shows that retail investors pour money into equity mutual funds and ETFs after strong market performance and withdraw assets after periods of weakness — precisely the opposite of buying low and selling high. During the bull market of 2017 through early 2020, net inflows into equity funds reached record levels. When the COVID-19 crash hit in March 2020, outflows accelerated as recency bias flipped from bullish extrapolation to bearish panic, causing many investors to crystallize losses near the trough.

Recency bias also distorts volatility expectations. After extended periods of low volatility — such as 2017, when the VIX spent months at historically depressed levels — investors price options cheaply and take on leveraged positions as though calm markets are the natural state. When volatility inevitably returns, those positions suffer outsized losses.

Kahneman and Tversky's availability heuristic, a closely related concept, explains part of the mechanism: events that are easy to recall — because they are recent, vivid, or emotionally significant — are judged to be more probable than base rates justify. A dramatic market crash in the past twelve months is cognitively available; a calm decade is not.

Countering recency bias requires explicitly incorporating long-run base rates into analysis. Looking at rolling 10- or 20-year return distributions, rather than the past 12 months, places current conditions in proper historical context and resists the pull toward extrapolation.