Constructing narrowest pathwise bootstrap prediction bands using threshold accepting
Typically, prediction bands for path-forecasts are constructed pointwise, while inference relates to the whole forecasted path. In general, no closed form analytical solution is available for pathwise bands in finite samples. We consider a direct construction approach based on bootstrapped prediction bands. The resulting highly complex optimization problem is tackled using the local search heuristic of threshold accepting. A comparison with pointwise and asymptotic bands is provided, demonstrating superior properties of the proposed bands in small samples. Finally, a real application shows the practical implications of using an appropriate tool for generating the prediction bands.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 29 (2013)
Issue (Month): 2 ()
|Contact details of provider:|| Web page: http://www.elsevier.com/locate/ijforecast|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Schwert, G William, 2002.
"Tests for Unit Roots: A Monte Carlo Investigation,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 20(1), pages 5-17, January.
- Anna Staszewska‐Bystrova, 2011. "Bootstrap prediction bands for forecast paths from vector autoregressive models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(8), pages 721-735, December.
- Jordà, Òscar & Marcellino, Massimiliano, 2008.
"Path Forecast Evaluation,"
CEPR Discussion Papers
7009, C.E.P.R. Discussion Papers.
- Jae H. Kim, 2004. "Bias-corrected bootstrap prediction regions for vector autoregression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 141-154.
- Kim, Jae H., 1999. "Asymptotic and bootstrap prediction regions for vector autoregression," International Journal of Forecasting, Elsevier, vol. 15(4), pages 393-403, October.
- Anna Staszewska, 2006.
"Representing Uncertainty about Response Paths: the Use of Heuristic Optimisation Methods,"
Computing in Economics and Finance 2006
379, Society for Computational Economics.
- Staszewska, Anna, 2007. "Representing uncertainty about response paths: The use of heuristic optimisation methods," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 121-132, September.
- Ruiz, Esther & Romo, Juan & Pascual, L., 1999.
"Effects of parameter estimation on prediction densities a bootstrap approach,"
DES - Working Papers. Statistics and Econometrics. WS
6304, Universidad Carlos III de Madrid. Departamento de Estadística.
- Pascual, Lorenzo & Romo, Juan & Ruiz, Esther, 2001. "Effects of parameter estimation on prediction densities: a bootstrap approach," International Journal of Forecasting, Elsevier, vol. 17(1), pages 83-103.
- Busch, Ulrike & Scharnagl, Michael & Scheithauer, Jan, 2010. "Loan supply in Germany during the financial crisis," Discussion Paper Series 1: Economic Studies 2010,05, Deutsche Bundesbank, Research Centre.
- Peter Winker & Dietmar Maringer, 2009. "The convergence of estimators based on heuristics: theory and application to a GARCH model," Computational Statistics, Springer, vol. 24(3), pages 533-550, August.
- Fitzenberger, Bernd & Winker, Peter, 1999.
"Improving the Computation of Censored Quantile Regressions,"
568, Institut fuer Volkswirtschaftslehre und Statistik, Abteilung fuer Volkswirtschaftslehre.
- Fitzenberger, Bernd & Winker, Peter, 2007. "Improving the computation of censored quantile regressions," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 88-108, September.
- Clements, Michael P. & Kim, Jae H., 2007. "Bootstrap prediction intervals for autoregressive time series," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3580-3594, April.
- Demetrescu, Matei & Kuzin, Vladimir & Hassler, Uwe, 2008. "Long Memory Testing In The Time Domain," Econometric Theory, Cambridge University Press, vol. 24(01), pages 176-215, February.
- Fresoli, Diego & Ruiz, Esther & Pascual, Lorenzo, 2011. "Bootstrap forecast of multivariate VAR models without using the backward representation," DES - Working Papers. Statistics and Econometrics. WS ws113426, Universidad Carlos III de Madrid. Departamento de Estadística.
- Winker, Peter & Fang, Kai-Tai, 1995. "Application of threshold accepting to the evaluation of the discrepancy of a set of points," Discussion Papers, Series II 248, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".
- Matei Demetrescu & Uwe Hassler & Vladimir Kuzin, 2011. "Pitfalls of post-model-selection testing: experimental quantification," Empirical Economics, Springer, vol. 40(2), pages 359-372, April.
- Kilian, Lutz, 2001. "Impulse Response Analysis in Vector Autoregressions with Unknown Lag Order," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(3), pages 161-79, April.
- James H. Stock & Mark W. Watson, 2001. "Vector Autoregressions," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 101-115, Fall.
When requesting a correction, please mention this item's handle: RePEc:eee:intfor:v:29:y:2013:i:2:p:221-233. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Shamier, Wendy)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.