Testing for Jumps and Jump Intensity Path Dependence

37 Pages Posted: 14 Jul 2017

See all articles by Valentina Corradi

Valentina Corradi

University of Surrey - School of Economics

Mervyn J Silvapulle

Monash University - Department of Econometrics & Business Statistics

Norman R. Swanson

Rutgers University - Department of Economics; Rutgers, The State University of New Jersey - Department of Economics

Date Written: December 6, 2015

Abstract

In this paper, we fill a gap in the financial econometrics literature, by developing a “jump test” for the null hypothesis that the probability of a jump is zero. The test is based on realized third moments, and uses observations over an increasing time span. The test offers an alternative to standard finite time span tests, and is designed to detect jumps in the data generating process rather than detecting realized jumps over a fixed time span. More specifically, we make two contributions. First, we introduce our largely model free jump test for the null hypothesis of zero jump intensity. Second, under the maintained assumption of strictly positive jump intensity, we introduce a “self excitement test” for the null of constant jump intensity against the alternative of path dependent intensity. The latter test has power against autocorrelation in the jump component, and is a direct test for Hawkes diffusions (see e.g., Aït-Sahalia, Cacho-Diaz and Laeven (2015)). The limiting distributions of the proposed statistics are analyzed via use of a double asymptotic scheme, wherein the time span goes to infinity and the discrete interval approaches zero; and the distributions of the tests are normal and half normal, respectively. The results from a Monte Carlo study indicate that the tests have good finite sample properties.

Keywords: diffusion model, jump intensity, jump size density, tricity

JEL Classification: C12, C22, C52, C55

Suggested Citation

Corradi, Valentina and Silvapulle, Mervyn J and Swanson, Norman Rasmus and Swanson, Norman Rasmus, Testing for Jumps and Jump Intensity Path Dependence (December 6, 2015). Available at SSRN: https://ssrn.com/abstract=2998255 or http://dx.doi.org/10.2139/ssrn.2998255

Valentina Corradi

University of Surrey - School of Economics ( email )

Guildford
Guildford, Surrey GU2 5XH
United Kingdom

Mervyn J Silvapulle

Monash University - Department of Econometrics & Business Statistics ( email )

Wellington Road
Clayton, Victoria 3168
Australia

Norman Rasmus Swanson (Contact Author)

Rutgers University - Department of Economics ( email )

NJ
United States

HOME PAGE: http://econweb.rutgers.edu/nswanson/

Rutgers, The State University of New Jersey - Department of Economics ( email )

75 Hamilton Street
New Brunswick, NJ 08901
United States
848-932-7432 (Phone)

HOME PAGE: http://econweb.rutgers.edu/nswanson/

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