Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/101621 
Authors: 
Year of Publication: 
1995
Series/Report no.: 
Diskussionsbeiträge - Serie II No. 252
Publisher: 
Universität Konstanz, Sonderforschungsbereich 178 - Internationalisierung der Wirtschaft, Konstanz
Abstract: 
There are various parametric models to analyse the volatility in time series of financial market data. For maximum likelihood estimation these parametric methods require the assumption of a known conditional distribution. In this paper we examine the conditional distribution of daily DAX returns with the help of nonparametric methods. We use kernel estimators for conditional quantiles resulting from a kernel estimation of conditional distributions.
Document Type: 
Working Paper

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