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Dynamic asset price jumps and the performance of high frequency tests and measures

Worapree Maneesoonthorn (), Gael Martin () and Catherine Forbes ()

No 14/17, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: This paper provides an extensive evaluation of high frequency jump tests and measures, in the context of dynamic models for asset price jumps. Specifically, we investigate: i) the power of alternative tests to detect individual price jumps, including in the presence of volatility jumps; ii) the frequency with which sequences of dynamic jumps are identified; iii) the accuracy with which the magnitude and sign of sequential jumps are estimated; and iv) the robustness of inference about dynamic jumps to test and measure design. Substantial differences are discerned in the performance of alternative methods in certain dimensions, with inference being sensitive to these differences in some cases. Accounting for measurement error when using measures constructed from high frequency data to conduct inference on dynamic jump models would appear to be advisable.

Keywords: Dynamic price jumps; price jump tests; nonparametric jump measures; Hawkes process; discretized jump diffusion model; Bayesian Markov chain Monte Carlo. (search for similar items in EconPapers)
JEL-codes: C12 C22 C58 (search for similar items in EconPapers)
Pages: 34
Date: 2017
New Economics Papers: this item is included in nep-cta and nep-mst
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