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Title:Quantile sieve estimates for time series PDF Logo
Authors:Franke, Jürgen
Stockis, Jean-Pierre
Tadjuidje, Joseph
Issue Date:2007
Series/Report no.:SFB 649 discussion paper 2007,005
Abstract:We consider the problem of estimating the conditional quantile of a time series at time t given observations of the same and perhaps other time series available at time t - 1. We discuss sieve estimates which are a nonparametric versions of the Koenker-Bassett regression quantiles and do not require the specification of the innovation law. We prove consistency of those estimates and illustrate their good performance for light- and heavy-tailed distributions of the innovations with a small simulation study. As an economic application, we use the estimates for calculating the value at risk of some stock price series.
Subjects:conditional quantile
time series
sieve estimate
neural network
qualitative threshold model
uniform consistency
value at risk
JEL:C14
C45
Document Type:Working Paper
Appears in Collections:SFB 649 Discussion Papers, HU Berlin

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