Dependence structures for multivariate high-frequency data in finance
作者： W. Breymann , A. Dias , P. Embrechts
DOI: 10.1080/713666155
关键词: Economics 、 Bivariate analysis 、 Multivariate statistics 、 Finance 、 Scaling 、 Volatility clustering 、 Function (mathematics) 、 Series (mathematics) 、 Univariate 、 Econometrics 、 Stylized fact
摘要: 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 FX spot major markets investigated. First, as an indispensable prerequisite further analysis, the problem simultaneous deseasonalization is addressed. following sections we analyse detail dependence structure a function timescale. Particular emphasis put on tail which investigated by means copulas.
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