Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Breymann, Wolfgang | - |
dc.contributor.author | Dias, Alexandra | - |
dc.contributor.author | Embrechts, Paul | - |
dc.date.accessioned | 2018-04-04T07:58:34Z | - |
dc.date.available | 2018-04-04T07:58:34Z | - |
dc.date.issued | 2003 | - |
dc.identifier.issn | 1469-7688 | de_CH |
dc.identifier.issn | 1469-7696 | de_CH |
dc.identifier.uri | https://digitalcollection.zhaw.ch/handle/11475/4676 | - |
dc.description.abstract | 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. | de_CH |
dc.language.iso | en | de_CH |
dc.publisher | Routledge | de_CH |
dc.relation.ispartof | Quantitative Finance | de_CH |
dc.rights | Licence according to publishing contract | de_CH |
dc.subject.ddc | 332: Finanzwirtschaft | de_CH |
dc.title | Dependence structures for multivariate high-frequency data in finance | de_CH |
dc.type | Beitrag in wissenschaftlicher Zeitschrift | de_CH |
dcterms.type | Text | de_CH |
zhaw.departement | School of Engineering | de_CH |
zhaw.organisationalunit | Institut für Datenanalyse und Prozessdesign (IDP) | de_CH |
dc.identifier.doi | 10.1080/713666155 | de_CH |
zhaw.funding.eu | No | de_CH |
zhaw.issue | 1 | de_CH |
zhaw.originated.zhaw | No | de_CH |
zhaw.pages.end | 14 | de_CH |
zhaw.pages.start | 1 | de_CH |
zhaw.publication.status | publishedVersion | de_CH |
zhaw.volume | 3 | de_CH |
zhaw.publication.review | Peer review (Publikation) | de_CH |
Appears in collections: | Publikationen School of Engineering |
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Breymann, W., Dias, A., & Embrechts, P. (2003). Dependence structures for multivariate high-frequency data in finance. Quantitative Finance, 3(1), 1–14. https://doi.org/10.1080/713666155
Breymann, W., Dias, A. and Embrechts, P. (2003) ‘Dependence structures for multivariate high-frequency data in finance’, Quantitative Finance, 3(1), pp. 1–14. Available at: https://doi.org/10.1080/713666155.
W. Breymann, A. Dias, and P. Embrechts, “Dependence structures for multivariate high-frequency data in finance,” Quantitative Finance, vol. 3, no. 1, pp. 1–14, 2003, doi: 10.1080/713666155.
BREYMANN, Wolfgang, Alexandra DIAS und Paul EMBRECHTS, 2003. Dependence structures for multivariate high-frequency data in finance. Quantitative Finance. 2003. Bd. 3, Nr. 1, S. 1–14. DOI 10.1080/713666155
Breymann, Wolfgang, Alexandra Dias, and Paul Embrechts. 2003. “Dependence Structures for Multivariate High-Frequency Data in Finance.” Quantitative Finance 3 (1): 1–14. https://doi.org/10.1080/713666155.
Breymann, Wolfgang, et al. “Dependence Structures for Multivariate High-Frequency Data in Finance.” Quantitative Finance, vol. 3, no. 1, 2003, pp. 1–14, https://doi.org/10.1080/713666155.
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