Physics Maths Engineering
Heavy-Tailed Probability Distributions: Some Examples of Their Appearance
Lev B. Klebanov,
Yulia V. Kuvaeva-Gudoshnikova,
Svetlozar T. Rachev
Peer Reviewed
Related Subjects
Abstract
We provide two examples of the appearance of heavy-tailed distributions in social sciences applications. Among these distributions are the laws of Pareto and Lotka and some new ones. The examples are illustrated through the construction of suitable toy models.
Key Questions
1. What are heavy-tailed probability distributions?
Heavy-tailed distributions have tails that decay slower than exponential distributions, meaning extreme events are more probable.
2. How do heavy-tailed distributions affect modeling in various fields?
They influence risk modeling and forecasting by accounting for rare, high-impact events that traditional models often overlook.
3. What are some real-world examples where heavy-tailed distributions are observed?
Examples include financial market returns, natural disasters, and network traffic patterns.
4. How can understanding heavy-tailed distributions improve predictions?
They help improve accuracy in predicting extreme events and reduce risk in areas like finance and insurance.
