Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/67963
Authors: 
Gürtler, Marc
Rauh, Ronald
Year of Publication: 
2012
Series/Report no.: 
Working Papers, Institut für Finanzwirtschaft, TU Braunschweig IF41V1
Abstract: 
In this paper we analyze an econometric model for non-stationary asset returns. Volatility dynamics are modelled by nonparametric regression; consistency and asymptotic normality of a symmetric and of a one-sided kernel estimator are outlined with remarks on the bandwidth decision. Further attention is paid to asymmetry and heavy tails of the return distribution, involved by the framework for innovations. We survey the practicability and automatization of the implementation. For simulated price processes and a multitude of financial time series we observe a satisfying model approximation and good short-term forecasting abilities of the univariate approach. The non-stationary regression model outperforms parametric risk models and famous ARCH-type implementations.
Subjects: 
heteroscedastic asset returns
non-stationarity
nonparametric regression
volatility
innovation modelling
forecasting
Value at Risk (VaR)
ARCH-models
JEL: 
C14
C5
Document Type: 
Working Paper

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