City Research Online

Abstract

We perform a comprehensive Monte Carlo comparison between nine alternative procedures available in the literature to detect jumps in financial assets using high-frequency data. We evaluate size and power properties of the procedures under alternative sampling frequencies, persistence in volatility, jump size and intensity, and degree of contamination with microstructure noise. The overall best performance is shown by the Andersen, Bollerslev, and Dobrev (2007) and Lee and Mykland (2008) intraday procedures (ABD-LM), provided the price process is not very volatile. We propose two extensions to the existing battery of tests. The first regards the finite sample improvements based on simulated critical values for the ABD-LM procedure. The second regards a procedure that combines frequencies and tests able to reduce the number of spurious jumps. Finally, we report an empirical analysis using real high frequency data on five stocks listed in the New York Stock Exchange.

Publication Type:	Article
Additional Information:	This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Business & Economic Statistics on 24 May 2012, available online: http://wwww.tandfonline.com/10.1080/07350015.2012.663250
Publisher Keywords:	jumps, nonparametric tests, high frequency data, stochastic volatility, Monte Carlo simulations
Subjects:	H Social Sciences > HG Finance
Departments:	Bayes Business School > Finance
SWORD Depositor:	Symplectic Administrator

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