Fat Tailed Distributions in Catastrophe Prediction

TL;DR

This paper explores the application of fat-tailed distributions in catastrophe prediction, highlighting their advantages over traditional Normal Distributions for modeling extreme events.

Contribution

It introduces the use of fat-tailed distributions specifically for catastrophe prediction, offering a novel approach compared to standard methods.

Findings

Fat-tailed distributions better model extreme catastrophe events.

Normal Distribution underestimates the probability of rare events.

Enhanced prediction accuracy for catastrophic risks.

Abstract

This paper discusses the use of fat-tailed distributions in catastrophe prediction as opposed to the more common use of the Normal Distribution.