Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/67961 
Year of Publication: 
2013
Series/Report no.: 
Working Paper Series No. IF43V1
Publisher: 
Technische Universität Braunschweig, Institut für Finanzwirtschaft, Braunschweig
Abstract: 
In this paper we analyze a multivariate non-stationary regression model empirically. With the knowledge about unconditional heteroscedasticty of financial returns, based on univariate studies and a congruent paradigm in Gürtler and Rauh (2009), we test for a time-varying covariance structure firstly. Based on these results, a central component of our non-stationary model is a kernel regression for pairwise covariances and the covariance matrix. Residual terms are fitted with an asymmetric Pearson type VII distribution. In an extensive study we estimate the linear dependence of a broad portfolio of equities and fixed income securities (including credit and currency risks) and fit the whole approach to provide distributional forecasts. Our evaluations verify a reasonable approximation and a satisfactory forecasting quality with an out performance against a traditional risk model.
Subjects: 
heteroscedasticity
non-stationarity
nonparametric regression
volatility
covariance matrix
innovation modeling
asymmetric heavy-tails
multivariate distributional forecast
empirical studies
JEL: 
C14
C5
Document Type: 
Working Paper

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