City Research Online

Abstract

In this paper, we examine the finite sample properties of test statistics designed to identify distinct underlying components of high-frequency financial data, specifically the Brownian component and infinite vs. finite activity jumps. We conduct a comprehensive set of Monte Carlo simulations to evaluate the tests under various types of microstructure noise, price staleness, and different levels of jump activity. We apply these tests to a dataset comprising 100 individual S&P 500 constituents from diverse business sectors and the SPY (S&P 500 ETF) to empirically assess the relative magnitude of these components. Our findings strongly support the presence of both Brownian and jump components. Furthermore, we investigate the time-varying nature of rejection rates and we find that periods with more jumps days are usually associated with an increase in infinite jumps and a decrease infinite jumps. This suggests a dynamic interplay between jump components over time.

Publication Type:	Article
Additional Information:	© 2025. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
Publisher Keywords:	High-frequency data; infinite jumps; finite jumps; Brownian motion; price staleness; microstructure noise
Subjects:	H Social Sciences > HG Finance
Departments:	Bayes Business School Bayes Business School > Finance
SWORD Depositor:	Symplectic Administrator

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