A heavy-tailed distribution is a type of probability distribution where the tail—representing extreme values—decays slower than an exponential distribution. This means that rare events have a higher likelihood of occurring compared to lighter-tailed distributions, such as the normal distribution. In practical terms, this can lead to unexpected large outcomes in various fields, including finance and insurance. Common examples of heavy-tailed distributions include the Pareto distribution and the Cauchy distribution. These distributions are important in modeling phenomena where extreme values play a significant role, such as in natural disasters or stock market crashes. Understanding heavy-tailed distributions helps in risk assessment and management.