Identifying multiple outliers in heavy-tailed distributions with an application to market crashes
Schluter, Christian and Trede, M. (2008) Identifying multiple outliers in heavy-tailed distributions with an application to market crashes. Journal of Empirical Finance, 15, (4), 700-713. (doi:10.1016/j.jempfin.2007.10.003 ).
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Description/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.
| Item Type: | Article |
|---|---|
| ISSNs: | 0927-5398 (print) |
| Keywords: | outliers, outward testing, masking |
| Subjects: | H Social Sciences > HG Finance |
| Divisions: | University Structure - Pre August 2011 > School of Social Sciences > Economics |
| Item ID: | 153073 |
| Date Deposited: | 18 May 2010 11:33 |
| Last Modified: | 25 Apr 2013 22:45 |
| Contributors: | Schluter, Christian (Author) Trede, M. (Author) |
| Date: | September 2008 |
| Status: | Published |
| URI: | http://eprints.soton.ac.uk/id/eprint/153073 |
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