Identifying multiple outliers in heavy-tailed distributions with an application to market crashes
Identifying multiple outliers in heavy-tailed distributions with an application to market crashes
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.
outliers, outward testing, masking
700-713
Schluter, Christian
ae043254-4cc4-48aa-abad-56a36554de2b
Trede, M.
5ad7e623-b129-4796-a5bb-b1e56cf2f9a6
September 2008
Schluter, Christian
ae043254-4cc4-48aa-abad-56a36554de2b
Trede, M.
5ad7e623-b129-4796-a5bb-b1e56cf2f9a6
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), .
(doi:10.1016/j.jempfin.2007.10.003).
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.
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e-pub ahead of print date: 12 November 2007
Published date: September 2008
Keywords:
outliers, outward testing, masking
Organisations:
Economics
Identifiers
Local EPrints ID: 153073
URI: http://eprints.soton.ac.uk/id/eprint/153073
ISSN: 0927-5398
PURE UUID: 534a41eb-088c-41f4-ba5a-ef89213681a2
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Date deposited: 18 May 2010 11:33
Last modified: 14 Mar 2024 01:26
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Author:
M. Trede
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