# Caudas longas, curtose e risco

2015 Jan 25
**O Matt Bogard escreve um pequeno post com essas questões, e aponta algumas referências.**

O entendimento do que é Curtose (que é proveniente da estatística) é de fundamental importância em estudos para mensuração de amplitude de valores de uma variável específica; especialmente se esses estudos forem ligados a questões ligadas a probabilidade.

*They recommend that kurtosis be defined as “the location- and scale-free movement of probability mass from the shoulders of a distribution into its center and tails. In particular, this definition implies that peakedness and tail weight are best viewed as components [emphasis mine] of kurtosis…. This definition is necessarily vague because the movement can be formalized in many ways” (p. 116). In other words, the peaks and tails of a distribution contribute to the value of the kurtosis, but so do other features.*

*The tail of the distribution is the most important contributor. Although Balanda and MacGillivray do not mention it, the kurtosis is a non-robust statistic that can be severely influenced by the value of a single outlier. For example, if you choose 999 observations from a normal distribution, the sample kurtosis will be close to 0. However, if you add a single observation that has the value 100, the sample kurtosis jumps to more than 800!*