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Dependence structures for multivariate high-frequency data in finance
journal contribution
posted on 2012-10-24, 08:54 authored by W. Breymann, Alexandra Dias, P. EmbrechtsStylized facts for univariate high-frequency data in finance are well known. They include scaling behaviour, volatility clustering, heavy tails and seasonalities. The multivariate problem, however, has scarcely been addressed up to now.
In this paper, bivariate series of high-frequency FX spot data for major FX markets are investigated. First, as an indispensable prerequisite for further analysis, the problem of simultaneous deseasonalization of high-frequency data is addressed. In the following sections we analyse in detail the dependence structure as a function of the timescale. Particular emphasis is put on the tail behaviour, which is investigated by means of copulas.
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Citation
Quantitative Finance, 2003, 3 (1), pp. 1-14Version
- AM (Accepted Manuscript)
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Quantitative FinancePublisher
Taylor & Francis (Routledge): SSH Titlesissn
1469-7688eissn
1469-7696Copyright date
2003Available date
2012-10-24Publisher DOI
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http://www.tandfonline.com/doi/abs/10.1080/713666155Language
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