SYSTEMIC RISK AND COJUMPS IN HIGH FREQUENCY DATA

Radu Lupu () and Alexandra Mateescu
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Alexandra Mateescu: School of Advanced Studies of the Romanian Academy, Bucharest, Romania

Studii Financiare (Financial Studies), 2016, vol. 20, issue 4, 6-16

Abstract: Univariate jump detection procedures have been widely studied in the field of statistics of high frequency data, whereas the extension of jump detection to a multivariate framework, in order to understand the correlation between asset returns, is more recent. Cojumps refer to the joint occurence of extreme price movements. The identification of cojumps is extremely important for investors who usually own portfolio of assets. Decisions regarding portofolio allocation, risk management, hedging and pricing can be based on this analysis. The objective of this paper is to investigate the existence of cojumps in European financial market, employing data on the shares of 12stock market indexes. The situations with identified cojumps will be used to identify simultaneous reactions of these markets in order to develop a measure of the systemic risk.

Keywords: jumps; cojumps; simultaneity indicator; high frequency data (search for similar items in EconPapers)
JEL-codes: C10 C20 C30 C49 (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:vls:finstu:v:20:y:2016:i:4:p:6-16

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