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Dependence structures for multivariate high-frequency data in finance

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journal contribution
posted on 24.10.2012, 08:54 by W. Breymann, Alexandra Dias, P. Embrechts
Stylized 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. 1-14

Version

AM (Accepted Manuscript)

Published in

Quantitative Finance

Publisher

Taylor & Francis (Routledge): SSH Titles

issn

1469-7688

eissn

1469-7696

Copyright date

2003

Available date

24/10/2012

Publisher version

http://www.tandfonline.com/doi/abs/10.1080/713666155

Language

en

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