|
EconStor >
Humboldt-Universität Berlin >
Sonderforschungsbereich 649: Ökonomisches Risiko, Humboldt-Universität Berlin >
SFB 649 Discussion Papers, HU Berlin >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10419/25177
|
| | |
| Title: | | Quantile sieve estimates for time series  |
| 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
|
| |
| | |
Download bibliographical data as:
BibTeX
|
| |
Share on:http://hdl.handle.net/10419/25177
|
Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.
|