Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/55232 
Year of Publication: 
2009
Series/Report no.: 
Working Paper Series No. IF32V2
Publisher: 
Technische Universität Braunschweig, Institut für Finanzwirtschaft, Braunschweig
Abstract: 
A non-stationary regression model for financial returns is examined theoretically in this paper. Volatility dynamics are modelled both exogenously and deterministic, captured by a nonparametric curve estimation on equidistant centered returns. We prove consistency and asymptotic normality of a symmetric variance estimator and of a one-sided variance estimator analytically, and derive remarks on the bandwidth decision. Further attention is paid to asymmetry and heavy tails of the return distribution, implemented by an asymmetric version of the Pearson type VII distribution for random innovations. By providing a method of moments for its parameter estimation and a connection to the Student-t distribution we offer the framework for a factor-based VaR approach. The approximation quality of the non-stationary model is supported by simulation studies.
Subjects: 
heteroscedastic asset returns
non-stationarity
nonparametric regression
volatility
innovation modelling
asymmetric heavy-tails
distributional forecast
Value at Risk (VaR)
JEL: 
C12
C14
C15
C5
Document Type: 
Working Paper

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