Identifying Multiple Outliers in Heavy-Tailed Distributions with an Application to Market Crashes • ChristianSchluter

C. Schluter and M. Trede (2008).”Identifying Multiple Outliers in Heavy-Tailed Distributions with an Application to Market Crashes.” Journal of Empirical Finance, 15, 1.

Abstract: “Heavy-tailed distributions, such as the distribution of stock returns, are prone to generate large values. This renders difficult the detection of outliers. We propose a new outward testing procedure to identify multiple outliers in these distributions. A major virtue of the test is its simplicity. The performance of the test is investigated in several simulation studies. As a substantive empirical contribution we apply the test to Dow Jones Industrial Average return data and find that the Black Monday market crash was not a structurally unusual event.”

Cite (toggle to un/fold)

@article{SchluterEmpFin08,
  title = {Identifying Multiple Outliers in Heavy-Tailed Distributions with an Application to Market Crashes},
  author={Schluter, Christian and Trede, Mark},
  journal = {Journal of Empirical Finance},
  year    = 2008,
  volume  = 15,
  number  = 1
}