Identifying Jumps in Financial Assets: A Comparison Between Nonparametric Jump Tests

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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 Andersen, T. G. , Bollerslev, T. and Dobrev, D. 2007. “No-Arbitrage Semi-Martingale Restrictions for Continuous-Time Volatility Models Subject to Leverage Effects, Jumps and I.I.D. Noise: Theory and Testable Distributional Implications,”. Journal of Econometrics, 138: 125–180. [Google Scholar] ) and Lee and Mykland ( 2008 Lee, S. S. and Mykland, P. A. 2008. “Jumps in Financial Markets: A New Nonparametric Test and Jump Dynamics,”. Review of Financial Studies, 21: 2535–2563. [Google Scholar] ) 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.

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