IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v36y2020i1p129-134.html
   My bibliography  Save this article

Card forecasts for M4

Author

Listed:
  • Doornik, Jurgen A.
  • Castle, Jennifer L.
  • Hendry, David F.

Abstract

The M4 forecast competition required forecasts of 100,000 time series at different frequencies. We provide a detailed description of the calibrated average of Rho and Delta (Card) forecasting method that we developed for this purpose. Delta estimates a dampened trend from the growth rates, while Rho estimates an adaptive but simple autoregressive model. Calibration estimates a more elaborate autoregressive model, treating the averaged forecasts from Rho and Delta as if they were observed. The proposed method is easy to understand, combining very fast execution with an excellent forecast performance.

Suggested Citation

  • Doornik, Jurgen A. & Castle, Jennifer L. & Hendry, David F., 2020. "Card forecasts for M4," International Journal of Forecasting, Elsevier, vol. 36(1), pages 129-134.
    • Handle: RePEc:eee:intfor:v:36:y:2020:i:1:p:129-134
    DOI: 10.1016/j.ijforecast.2019.03.012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0169207019300834
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijforecast.2019.03.012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 127-152, April.
    2. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 169-177, April.
    3. Jennifer L. Castle & Jurgen A. Doornik & David Hendry, 2019. "Some forecasting principles from the M4 competition," Economics Papers 2019-W01, Economics Group, Nuffield College, University of Oxford.
    4. Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, vol. 16(4), pages 451-476.
    5. Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pantelis Agathangelou & Demetris Trihinas & Ioannis Katakis, 2020. "A Multi-Factor Analysis of Forecasting Methods: A Study on the M4 Competition," Data, MDPI, vol. 5(2), pages 1-24, April.
    2. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2021. "Modelling non-stationary ‘Big Data’," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1556-1575.
    3. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    4. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    5. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Selecting a Model for Forecasting," Econometrics, MDPI, vol. 9(3), pages 1-35, June.
    6. Ruben Loaiza‐Maya & Gael M. Martin & David T. Frazier, 2021. "Focused Bayesian prediction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 517-543, August.
    7. Doornik, Jurgen A. & Castle, Jennifer L. & Hendry, David F., 2022. "Short-term forecasting of the coronavirus pandemic," International Journal of Forecasting, Elsevier, vol. 38(2), pages 453-466.
    8. Diogo de Prince & Emerson Fernandes Marçal & Pedro L. Valls Pereira, 2022. "Forecasting Industrial Production Using Its Aggregated and Disaggregated Series or a Combination of Both: Evidence from One Emerging Market Economy," Econometrics, MDPI, vol. 10(2), pages 1-34, June.
    9. Wilson, Tom & Grossman, Irina & Temple, Jeromey, 2023. "Evaluation of the best M4 competition methods for small area population forecasting," International Journal of Forecasting, Elsevier, vol. 39(1), pages 110-122.
    10. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2020. "Short-term forecasting of the Coronavirus Pandemic - 2020-04-27," Economics Papers 2020-W06, Economics Group, Nuffield College, University of Oxford.
    11. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Forecasting Principles from Experience with Forecasting Competitions," Forecasting, MDPI, vol. 3(1), pages 1-28, February.
    12. Jennifer L. Castle & Jurgen A. Doornik & David Hendry, 2019. "Some forecasting principles from the M4 competition," Economics Papers 2019-W01, Economics Group, Nuffield College, University of Oxford.

    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. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Jennifer L. Castle & Jurgen A. Doornik & David Hendry, 2019. "Some forecasting principles from the M4 competition," Economics Papers 2019-W01, Economics Group, Nuffield College, University of Oxford.
    3. Miller, Don M. & Williams, Dan, 2004. "Damping seasonal factors: Shrinkage estimators for the X-12-ARIMA program," International Journal of Forecasting, Elsevier, vol. 20(4), pages 529-549.
    4. Olivares, Kin G. & Challu, Cristian & Marcjasz, Grzegorz & Weron, Rafał & Dubrawski, Artur, 2023. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," International Journal of Forecasting, Elsevier, vol. 39(2), pages 884-900.
    5. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    6. Giancarlo Bruno & Edoardo Otranto, 2006. "The choice of time interval in seasonal adjustment: A heuristic approach," Statistical Papers, Springer, vol. 47(3), pages 393-417, June.
    7. Mauricio Gallardo & Hernán Rubio, 2009. "Diagnóstico de estacionalidad con X-12-ARIMA," Economic Statistics Series 76, Central Bank of Chile.
    8. Hall, Viv B & Thomson, Peter, 2022. "A boosted HP filter for business cycle analysis: evidence from New Zealand’s small open economy," Working Paper Series 9473, Victoria University of Wellington, School of Economics and Finance.
    9. Kroes, James R. & Manikas, Andrew S. & Gattiker, Thomas F., 2018. "Operational leanness and retail firm performance since 1980," International Journal of Production Economics, Elsevier, vol. 197(C), pages 262-274.
    10. Kourentzes, Nikolaos & Athanasopoulos, George, 2021. "Elucidate structure in intermittent demand series," European Journal of Operational Research, Elsevier, vol. 288(1), pages 141-152.
    11. Quenneville, Benoit & Ladiray, Dominique & Lefrancois, Bernard, 2003. "A note on Musgrave asymmetrical trend-cycle filters," International Journal of Forecasting, Elsevier, vol. 19(4), pages 727-734.
    12. Massmann, Michael & Mitchell, James, 2003. "Reconsidering the evidence: Are Eurozone business cycles converging," ZEI Working Papers B 05-2003, University of Bonn, ZEI - Center for European Integration Studies.
    13. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
    14. Hai Yue Liu & Xiao Lan Chen, 2017. "The imported price, inflation and exchange rate pass-through in China," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1279814-127, January.
    15. Henryk Gurgul & Marcin Suder, 2013. "The Properties of ATMs Development Stages - an Empirical Analysis," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 14(3), pages 443-466, September.
    16. Carlos A. Medel, 2018. "A Comparison Between Direct and Indirect Seasonal Adjustment of the Chilean GDP 1986–2009 with X-12-ARIMA," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 47-87, April.
    17. Stefania D'Amico & Athanasios Orphanides, 2008. "Uncertainty and disagreement in economic forecasting," Finance and Economics Discussion Series 2008-56, Board of Governors of the Federal Reserve System (U.S.).
    18. Kirchner, Robert, 1999. "Auswirkungen des neuen Saisonbereinigungsverfahrens Census X-12-ARIMA auf die aktuelle Wirtschaftsanalyse in Deutschland," Discussion Paper Series 1: Economic Studies 1999,07, Deutsche Bundesbank.
    19. M. Angeles Carnero & Siem Jan Koopman & Marius Ooms, 2003. "Periodic Heteroskedastic RegARFIMA Models for Daily Electricity Spot Prices," Tinbergen Institute Discussion Papers 03-071/4, Tinbergen Institute.
    20. Flávio de Freitas Val & Wagner Piazza Gaglianone & Marcelo Cabus Klotzle & Antonio Carlos Figueiredo Pinto, 2017. "Estimating the Credibility of Brazilian Monetary Policy using Forward Measures and a State-Space Model," Working Papers Series 463, Central Bank of Brazil, Research Department.

    More about this item

    Keywords

    Automatic forecasting; Calibration; Forecast intervals; Regression; M4; Seasonality; Software; Time series; Unit roots;
    All these keywords.

    JEL classification:

    • M4 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting

    Statistics

    Access and download statistics

    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:eee:intfor:v:36:y:2020:i:1:p:129-134. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijforecast .

    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.