Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/67963 
Year of Publication: 
2012
Series/Report no.: 
Working Paper Series No. IF41V1
Publisher: 
Technische Universität Braunschweig, Institut für Finanzwirtschaft, Braunschweig
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

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.