A closer look.
A fat-tailed distribution assigns more probability to very large deviations than a thin-tailed benchmark such as a normal distribution. Rare observations can dominate totals and make estimates unstable.
Why it matters
A model that understates extreme outcomes can make a system look safer than it is.
A useful lens. Not a universal law.
- Fat-tailed does not mean every extreme event is likely. Tail definitions and the relevant comparison distribution need to be made explicit.
Associated thinkers
DiscussedNassim Nicholas Taleb ↗
Associated withBenoît Mandelbrot ↗
Associations marked provisional are awaiting source review.
Further reading
A researched reading list is planned for this entry. The current field notes and thinker associations are provisional editorial content.