IDEAS home Printed from https://ideas.repec.org/p/zbw/sfb475/199836.html
   My bibliography  Save this paper

A selective procedure for combining forecasts

Author

Listed:
  • Troschke, Sven-Oliver

Abstract

If there are various forecasts for the same random variable, it is common practice to combine these forecasts in order to obtain a better forecast. But an important question is how to perform the combination, especially if the system under investigation is subject to structural changes and consequently the best combination method is not the same all of the time. This paper presents a data driven approach, which for each point of time selects a combination technique from a given set of combination techniques. Properties and limitations of this selection procedure are investigated using simulated data from normal distributions.

Suggested Citation

  • Troschke, Sven-Oliver, 1998. "A selective procedure for combining forecasts," Technical Reports 1998,36, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  • Handle: RePEc:zbw:sfb475:199836
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/77304/2/1998-36.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Thomas D. Russell & Everett E. Adam, Jr., 1987. "An Empirical Evaluation of Alternative Forecasting Combinations," Management Science, INFORMS, vol. 33(10), pages 1267-1276, October.
    2. Klapper, Matthias, 1998. "Combining German macro economic forecasts using rank-based techniques," Technical Reports 1998,19, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    3. Deutsch, Melinda & Granger, Clive W. J. & Terasvirta, Timo, 1994. "The combination of forecasts using changing weights," International Journal of Forecasting, Elsevier, vol. 10(1), pages 47-57, June.
    4. Spyros Makridakis & Robert L. Winkler, 1983. "Averages of Forecasts: Some Empirical Results," Management Science, INFORMS, vol. 29(9), pages 987-996, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    2. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 4, pages 135-196, Elsevier.
    3. Esteban Fernández-Vázquez & Blanca Moreno, 2017. "Entropy Econometrics for combining regional economic forecasts: A Data-Weighted Prior Estimator," Journal of Geographical Systems, Springer, vol. 19(4), pages 349-370, October.
    4. Bacci, Livio Agnew & Mello, Luiz Gustavo & Incerti, Taynara & Paulo de Paiva, Anderson & Balestrassi, Pedro Paulo, 2019. "Optimization of combined time series methods to forecast the demand for coffee in Brazil: A new approach using Normal Boundary Intersection coupled with mixture designs of experiments and rotated fact," International Journal of Production Economics, Elsevier, vol. 212(C), pages 186-211.
    5. Park, Timothy A. & Gubanova, Tatiana & Lohr, Luanne & Escalante, Cesar L., 2005. "Forecasting Organic Food Prices: Testing and Evaluating Conditional Predictive Ability," 2005 Annual meeting, July 24-27, Providence, RI 19412, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Lessmann, Stefan & Sung, Ming-Chien & Johnson, Johnnie E.V. & Ma, Tiejun, 2012. "A new methodology for generating and combining statistical forecasting models to enhance competitive event prediction," European Journal of Operational Research, Elsevier, vol. 218(1), pages 163-174.
    7. Schneider, Carsten & Klapper, Matthias & Wenzel, Thomas, 1999. "An evaluation of forecasting methods and forecast combination methods in goods management systems," Technical Reports 1999,31, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    8. Li Fuchun & Tkacz Greg, 2004. "Combining Forecasts with Nonparametric Kernel Regressions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(4), pages 1-18, December.
    9. Chan, Chi Kin & Kingsman, Brian G. & Wong, H., 1999. "The value of combining forecasts in inventory management - a case study in banking," European Journal of Operational Research, Elsevier, vol. 117(2), pages 199-210, September.
    10. Wenzel, Thomas, 2000. "Hits-and-misses for the evaluation and combination of forecasts," Technical Reports 2000,26, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    11. Elkin Castaño Vélez & Luis Fernando Melo Velandia, 2000. "Metodos de combinacion de pronosticos: una aplicacion a la inflacion," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 52, pages 113-165, Enero Jun.
    12. Wenzel, Thomas, 1999. "Combination of biased forecasts: Bias correction or bias based weights?," Technical Reports 1999,50, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    13. Kourentzes, Nikolaos & Petropoulos, Fotios & Trapero, Juan R., 2014. "Improving forecasting by estimating time series structural components across multiple frequencies," International Journal of Forecasting, Elsevier, vol. 30(2), pages 291-302.
    14. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    15. Pesaran, M. Hashem & Weale, Martin, 2006. "Survey Expectations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 14, pages 715-776, Elsevier.
    16. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    17. Samuels, Jon D. & Sekkel, Rodrigo M., 2017. "Model Confidence Sets and forecast combination," International Journal of Forecasting, Elsevier, vol. 33(1), pages 48-60.
    18. Julia A. Minson & Jennifer S. Mueller & Richard P. Larrick, 2018. "The Contingent Wisdom of Dyads: When Discussion Enhances vs. Undermines the Accuracy of Collaborative Judgments," Management Science, INFORMS, vol. 64(9), pages 4177-4192, September.
    19. Torsten Heinrich & Juan Sabuco & J. Doyne Farmer, 2022. "A simulation of the insurance industry: the problem of risk model homogeneity," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(2), pages 535-576, April.
    20. Chen, Bin & Maung, Kenwin, 2023. "Time-varying forecast combination for high-dimensional data," Journal of Econometrics, Elsevier, vol. 237(2).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:sfb475:199836. See general information about how to correct material in RePEc.

    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 CitEc recognized a bibliographic reference but did not link an item in RePEc 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/isdorde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.