Testing for co-jumps in high-frequency financial data: an approach based on first-high-low-last prices

Yin Liao () and Heather Anderson

No 9/11, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: This paper proposes a new test for simultaneous intraday jumps in a panel of high frequency financial data. We utilize intraday first-high-low-last values of asset prices to construct estimates for the cross-variation of returns in a large panel of high frequency financial data, and then employ these estimates to provide a first-high-low-last price based test statistic to detect common large discrete movements (co-jumps). We study the finite sample behavior of our first-high-low-last price based test using Monte Carlo simulation, and find that it is more powerful than the Bollerslev et al (2008) return-based co-jump test. When applied to a panel of high frequency data from the Chinese mainland stock market, our first-high-low-last price based test identifies more common jumps than the return-based test in this emerging market.

Keywords: Covariance; Co-jumps; High-frequency data; First-High-Low-Last price; Microstructure bias; Nonsynchronous trades; Realized covariance; Realized co-range. (search for similar items in EconPapers)
JEL-codes: C12 C22 C32 G12 G14 (search for similar items in EconPapers)
Pages: 52 pages
Date: 2011-08-18
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mst
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Citations: View citations in EconPapers (4)

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Journal Article: Testing for cojumps in high-frequency financial data: An approach based on first-high-low-last prices (2019)
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