What do fat tails in distribution indicate?

Fat tails in a distribution signify that there is a significantly higher probability of extreme events occurring compared to what is suggested by normal distributions. In a normal distribution, most data points cluster around the mean, with probabilities tapering off sharply as one moves away from the mean. This results in a lower likelihood of observing extreme values.

However, when a distribution displays "fat tails," it indicates that the tails of the distribution are thicker than those found in a normal distribution. This characteristic means that there are more occurrences of extreme outcomes, such as major financial losses or gains, than would typically be forecasted by a model based purely on normal distribution assumptions. This is particularly relevant in risk management, as it highlights the inadequacy of standard models in predicting potential outlier events, leading to a greater emphasis on using alternative modeling techniques to better assess risks associated with extreme events.

In summary, recognizing fat tails is crucial for obtaining a more realistic understanding of risk, as they directly inform us that extreme events are more probable than indicated by traditional statistical models, influencing decision-making in various financial contexts.