Thu. Dec 7th, 2023

• Behavioral economics has a profound influence on our preferences and behaviors when it comes to Bitcoin.
• Fear of missing out (FOMO) and loss aversion are common “traps” that can lead to irrational decision making when investing in anything, including Bitcoin.
• Cognitive journeys such as recency bias can help explain the gyrations of the Bitcoin ecosystem and its 24-hour market.

Behavioral Economics & Bitcoin

Behavioral economics has long been cited to describe our “irrational tendencies” as consumers and investors, particularly when it comes to crypto in general and Bitcoin specifically. Common “traps” such as fear of missing out (FOMO), loss aversion, groupthink (“the bandwagon” effect) and the sunk-cost fallacy all have an influence on how we make decisions when investing in any asset class.

Fear Of Missing Out & Loss Aversion

Investing in anything is prone to these traps which account for people holding onto their investments longer than they should. Fear of getting in (FOGI) also paralyzes many from participating in the asset class due to confusion or technological leap of faith required to understand or use something new.

Recency Bias

The volatile nature of the Bitcoin marketplace is further exacerbated by recency bias, where people assume recent events will repeat themselves if they experience positive or negative events during their time invested. This irrational tendency can have undue influence on near-future decisions made related to investments.

24-Hour Market

The 24-hour market also amplifies this peak-end rule which weighs heavily on how someone experiences certain things, thus having potential for more significant influence over decisions made regarding investment strategies with Bitcoin.


Overall, behavioral finance concepts have interesting parallels with understanding the way people invest in bitcoin; FOMO and FOGI are two examples but there are many more that need to be considered when strategizing how best to participate in this asset class successfully long-term.

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