We propose a technique to avoid spurious detections of jumps in highfrequency data via an explicit thresholding on available test statistics

Pierre Bajgrowicz and Olivier Scaillet
Additional contact information
Pierre Bajgrowicz: University of Geneva

No 11-36, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: We prove that it eliminates asymptotically all spurious detections. Monte Carlo results show that it performs also well in nite samples. In Dow Jones stocks, spurious detections represent up to 50% of the jumps detected initially between 2006 and 2008. For the majority of stocks, jumps do not cluster in time and no cojump a ects all stocks simultaneously, suggesting jump risk is diversi able. We relate the remaining jumps to macroeconomic news, prescheduled company-speci c announcements, and stories from news agencies which include a variety of unscheduled and uncategarized events. The majority of news do not cause jumps. One exception are share buybacks announcements. Fed rate news have an important impact but rarely cause jumps. Another nding is that 60% of jumps occur without any news event. For one third of the jumps with no news we observe an unusual behavior in the volume of transactions. Hence, liquidity pressures are probably another important factor of jumps.

Keywords: jumps; high-frequency data; spurious detections; jumps dynamics; news releases; cojumps (search for similar items in EconPapers)
JEL-codes: C58 G12 G14 (search for similar items in EconPapers)
Pages: 69 pages
Date: 2011-05
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mst
References: Add references at CitEc
Citations:

Downloads: (external link)
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1343900 (application/pdf)

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:chf:rpseri:rp1136

Access Statistics for this paper

More papers in Swiss Finance Institute Research Paper Series from Swiss Finance Institute Contact information at EDIRC.
Bibliographic data for series maintained by Ridima Mittal ().