Estimation of Jump Tails

Tim Bollerslev and Viktor Todorov

No 10-37, Working Papers from Duke University, Department of Economics

Abstract: We propose a new and flexible non-parametric framework for estimating the jump tails of Itô semimartingale processes. The approach is based on a relatively simple-to-implement set of estimating equations associated with the compensator for the jump measure, or its "intensity", that only utilizes the weak assumption of regular variation in the jump tails, along with in-fill asymptotic arguments for uniquely identifying the \large" jumps from the data. The estimation allows for very general dynamic dependencies in the jump tails, and does not restrict the continuous part of the process and the temporal variation in the stochastic volatility. On implementing the new estimation procedure with actual high-frequency data for the S&P 500 aggregate market portfolio, we find strong evidence for richer and more complex dynamic dependencies in the jump tails than hitherto entertained in the literature.

Keywords: Extreme events; jumps; high-frequency data; jump tails; non-parametric estimation; stochastic volatility (search for similar items in EconPapers)
JEL-codes: C13 C14 G10 G12 (search for similar items in EconPapers)
Pages: 48
Date: 2010
References: Add references at CitEc
Citations:

Downloads: (external link)
http://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID15 ... ctid=1589753&mirid=1 main text

Related works:
Journal Article: Estimation of Jump Tails (2011)
Working Paper: Estimation of Jump Tails (2010)
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:duk:dukeec:10-37

Access Statistics for this paper

More papers in Working Papers from Duke University, Department of Economics Department of Economics Duke University 213 Social Sciences Building Box 90097 Durham, NC 27708-0097.
Bibliographic data for series maintained by Department of Economics Webmaster (webmaster@econ.duke.edu).