Dependence structures for multivariate high-frequency data in finance
نویسندگان
چکیده
منابع مشابه
Dependence Structures for Multivariate High–Frequency Data in Finance
Stylised 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 analy...
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The stylized facts of univariate high-frequency data in finance are well known; see Dacorogna et al. (2001). In Breymann et al. (2003) we analyzed bivariate high frequency forex data as a function of the sampling frequency, however treating the data as iid. In the present paper, using the data from Breymann et al. (2003), we model the dynamics as GARCH type processes and investigate the stylize...
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Dependence modelling and estimation is a key issue in the assessment of financial risk. It is common knowledge meanwhile that the multivariate normal model with linear correlation as its natural dependence measure is by no means an ideal model. We suggest a large class of models and a dependence function, which allows us to capture the complete extreme dependence structure of a portfolio. We al...
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ژورنال
عنوان ژورنال: Quantitative Finance
سال: 2003
ISSN: 1469-7688,1469-7696
DOI: 10.1080/713666155