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 Aït-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.
Highlights
We focus on tests due to Barndorff-Nielsen and Shephard (2006); Lee and Mykland (2008); Aït-Sahalia and Jacod (2009); Corsi et al (2010), and Podolskij and Ziggel (2010), who study “fixed time span” jump tests; and tests due to Corradi et al (2014) and Corradi et al (2018) who study so-called “long time span” jump
We carry out a Monte Carlo investigation of long time span jump tests, which are designed to indicate whether the jump intensity in the underlying DGP is identically zero
We find that the long time span tests have good finite sample properties
Summary
We add to the financial econometrics literature by carrying out an extensive Monte. The use of long-span asymptotics ensures that these tests have power against non-zero intensity in the DGP rather than against realized jumps on a particular sample path with a fixed time span. For the case of our long time span jump intensity tests, we must provide a moderate amount of additional structure This is one of the key trade-offs associated with using either variant of test. Before discussing the tests that are compared in our Monte Carlo experiments, we first provide some heuristic motivation for long time span jump testing.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
