Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/146959
Authors: 
Raddant, Matthias
Wagner, Friedrich
Year of Publication: 
2016
Series/Report no.: 
Kiel Working Paper 2049
Abstract: 
The problems related to the application of multivariate GARCH models to a market with a large number of stocks are solved by restricting the form of the conditional covariance matrix. It contains one component describing the market and a second simple component to account for the remaining contribution to the volatility. This allows the analytical calculation of the inverse covariance matrix. We compare our model with the results of other GARCH models for the daily returns from the S&P500 market. The description of the covariance matrix turns out to be similar to the DCC model but has fewer free parameters and requires less computing time. As applications we use the daily values of beta coefficients available from the market component to confirm a transition of the market in 2006. Further we discuss properties of the leverage effect.
Subjects: 
Multivarite GARCH models
CAPM
market risk
JEL: 
C58
C55
G12
Document Type: 
Working Paper

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