Optimal choice of sample fraction in univariate financial tail index estimation

Cheong Chin

Journal of Applied Statistics, 2010, vol. 37, issue 12, 2043-2056

Abstract: This study introduces a technique to estimate the Pareto distribution of the stock exchange index by using the maximum-likelihood Hill estimator. Recursive procedures based on the goodness-of-fit statistics are used to determine the optimal threshold fraction of extreme values to be included in tail estimation. These procedures are applied to three indices in the Malaysian stock market which included the consideration of a drastic economic event such as the Asian financial crisis. The empirical results evidenced alternating varying behavior of heavy-tailed distributions in the regimes for both upper and lower tails.

Keywords: heavy-tailed distribution; Hill estimator; goodness-of-fit test; structural change (search for similar items in EconPapers)
Date: 2010
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/02664760903214403 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:37:y:2010:i:12:p:2043-2056

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CJAS20

DOI: 10.1080/02664760903214403

Access Statistics for this article

Journal of Applied Statistics is currently edited by Robert Aykroyd

More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().