Testing for Jumps in Near Non-Stationary Diffusion Processes

26 Pages Posted: 13 Oct 2017

Date Written: October 12, 2017

Abstract

In this paper, we show that despite the fact that Ornstein-Uhlenbeck (OU) processes fall within the general specification of asset price dynamics studied by Lee and Mykland (2008), the finite sample performance of their two tests for additive jumps is far from being satisfactory when the process deviates from the random walk, resulting in a strong size distortion and a power loss. Therefore, we propose a modification to their test that improves the finite sample performance for local-to-unity processes (in both explosive or stationary directions). We apply the tests on 21 years of 5-minute log returns of the Nasdaq stock price index and find that, unlike the other two tests, our test allows to detect jumps when log-prices exhibit clear upward or downward trend movements.

Keywords: Jumps, Ornstein-Uhlenbeck processes, random walk, local-to-unity, intraday data

JEL Classification: C12, C14

Suggested Citation

Laurent, Sébastien and Shi, Shuping, Testing for Jumps in Near Non-Stationary Diffusion Processes (October 12, 2017). Macquarie University Faculty of Business & Economics Research Paper No. 4/2017, Available at SSRN: https://ssrn.com/abstract=3052053 or http://dx.doi.org/10.2139/ssrn.3052053

Sébastien Laurent

AMSE ( email )

2 rue de la Charité
Marseille, 13236
France

Shuping Shi (Contact Author)

Macquarie University ( email )

Macquarie University
Sydney, NSW 2109
Australia

HOME PAGE: http://https://sites.google.com/site/shupingshi/home/

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