Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/247513 
Year of Publication: 
2019
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 7 [Issue:] 1 [Publisher:] MDPI [Place:] Basel [Year:] 2019 [Pages:] 1-32
Publisher: 
MDPI, Basel
Abstract: 
Numerous tests designed to detect realized jumps over a fixed time span have been proposed and extensively studied in the financial econometrics literature. These tests differ from 'long time span tests' that detect jumps by examining the magnitude of the jump intensity parameter in the data generating process, and which are consistent. In this paper, long span jump tests are compared and contrasted with a variety of fixed span jump tests in a series of Monte Carlo experiments. It is found that both the long time span tests of Corradi et al. (2018) and the fixed span tests of Äit-Sahalia and Jacod (2009) exhibit reasonably good finite sample properties, for time spans both short and long. Various other tests suffer from finite sample distortions, both under sequential testing and under long time spans. The latter finding is new, and confirms the 'pitfall' discussed in Huang and Tauchen (2005), of using asymptotic approximations associated with finite time span tests in order to study long time spans of data. An empirical analysis is carried out to investigate the implications of these findings, and 'time-span robust' tests indicate that the prevalence of jumps is not as universal as might be expected.
Subjects: 
jump test
jump intensity
sequential testing bias
fixed time span
long time span
high-frequency data
JEL: 
C12
C22
C52
C58
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.