Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/25169
Authors: 
Ng, Wing Lon
Year of Publication: 
2006
Series/Report no.: 
SFB 649 discussion paper 2006,086
Abstract: 
This paper applies a non- and a semiparametric copula-based approach to analyze the first-order autocorrelation of returns in high frequency financial time series. Using the EUREX D3047 tick data from the German stock index, it can be shown that the temporal dependence structure of price movements is not always negatively correlated as assumed in the stylized facts in the finance literature. Depending on the sampling frequency, the estimated copulas exhibit some kind of overreaction phenomena and multiple tail dependence, revealing patterns similar to the compass rose.
Subjects: 
high frequency data
non- and semiparametric copulas
overreaction
tail dependence
compass rose
JEL: 
C14
C22
G14
Document Type: 
Working Paper

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