TY  - INPR
A1  - Franke, Jürgen
A1  - Stockis, Jean-Pierre
A1  - Tadjuidje, Joseph
T1  - Quantile Sieve Estimates for Time Series
N2  - 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.
T3  - Report in Wirtschaftsmathematik (WIMA Report) - 105 
KW  - conditional quantile
KW  - time series
KW  - sieve estimate
KW  - neural network
KW  - qualitative threshold model
Y1  - 2007
UR  - https://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/1834
UR  - https://nbn-resolving.org/urn:nbn:de:hbz:386-kluedo-14779
ER  -