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Predictive Evaluation of Econometric Forecasting Models in Commodity Futures Markets

Author

Listed:
  • Zeng, T.
  • Swanson, N.R.

Abstract

The predictive accuracy of various econometrics models, including random walks, vector autoregressive and vector error-correction models, are investigated using daily futures prices of 4 commodities (the S&P500 index, treasury bonds, gold and crude oil).

Suggested Citation

  • Zeng, T. & Swanson, N.R., 1997. "Predictive Evaluation of Econometric Forecasting Models in Commodity Futures Markets," Papers 9-97-4, Pennsylvania State - Department of Economics.
    • Handle: RePEc:fth:pensta:9-97-4
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    Cited by:

    1. Hendry, David F. & Martinez, Andrew B., 2017. "Evaluating multi-step system forecasts with relatively few forecast-error observations," International Journal of Forecasting, Elsevier, vol. 33(2), pages 359-372.
    2. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2019. "Statistical and economic evaluation of time series models for forecasting arrivals at call centers," Empirical Economics, Springer, vol. 57(3), pages 923-955, September.
    3. Andrea BASTIANIN & Marzio GALEOTTI & Matteo MANERA, 2011. "Forecast evaluation in call centers: combined forecasts, flexible loss functions and economic criteria," Departmental Working Papers 2011-08, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    4. Scarpa, Elisa & Longo, Chiara & Manera, Matteo & Markandya, Anil, 2007. "Evaluating the Empirical Performance of Alternative Econometric Models for Oil Price Forecasting," International Energy Markets Working Papers 12118, Fondazione Eni Enrico Mattei (FEEM).
    5. Giliola Frey & Matteo Manera & Anil Markandya & Elisa Scarpa, 2009. "Econometric Models for Oil Price Forecasting: A Critical Survey," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 10(1), pages 29-44, April.
    6. Batchelor, Roy & Alizadeh, Amir & Visvikis, Ilias, 2007. "Forecasting spot and forward prices in the international freight market," International Journal of Forecasting, Elsevier, vol. 23(1), pages 101-114.
    7. Bastianin, Andrea & Manera, Matteo & Markandya, Anil & Scarpa, Elisa, 2011. "Oil Price Forecast Evaluation with Flexible Loss Functions," Energy: Resources and Markets 120042, Fondazione Eni Enrico Mattei (FEEM).
    8. Cheng, Gang & Yang, Yuhong, 2015. "Forecast combination with outlier protection," International Journal of Forecasting, Elsevier, vol. 31(2), pages 223-237.
    9. Baomin Dong & Xuefeng Li & Boqiang Lin, 2010. "Forecasting Long-Run Coal Price in China: A Shifting Trend Time-Series Approach," Review of Development Economics, Wiley Blackwell, vol. 14(s1), pages 499-519, August.
    10. Van Bellegem, Sebastien & von Sachs, Rainer, 2004. "Forecasting economic time series with unconditional time-varying variance," International Journal of Forecasting, Elsevier, vol. 20(4), pages 611-627.
    11. Chen, Shyh-Wei & Lin, Shih-Mo, 2014. "Non-linear dynamics in international resource markets: Evidence from regime switching approach," Research in International Business and Finance, Elsevier, vol. 30(C), pages 233-247.
    12. Andrea BASTIANIN & Marzio GALEOTTI & Matteo MANERA, 2011. "Forecast evaluation in call centers: combined forecasts, flexible loss functions and economic criteria," Departmental Working Papers 2011-08, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    13. Claudio Dicembrino & Pasquale Lucio Scandizzo, 2012. "The Fundamental and Speculative Components of the Oil Spot Price: A Real Option Value Approach," CEIS Research Paper 229, Tor Vergata University, CEIS, revised 18 Apr 2012.
    14. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2011. "Forecast Evaluation in Call Centers: Combined Forecasts, Flexible Loss Functions and Economic Criteria," Working Papers 20110301, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica.
    15. Saporta, Victoria & Trott, Matt & Tudela, Merxe, 2009. "What can be said about the rise and fall in oil prices?," Bank of England Quarterly Bulletin, Bank of England, vol. 49(3), pages 215-225.
    16. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    17. Ai Han & Yanan He & Yongmiao Hong & Shouyang Wang, 2013. "Forecasting Interval-valued Crude Oil Prices via Autoregressive Conditional Interval Models," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    18. Christian Pierdzioch & Marian Risse, 2020. "Forecasting precious metal returns with multivariate random forests," Empirical Economics, Springer, vol. 58(3), pages 1167-1184, March.

    More about this item

    Keywords

    FORECASTS ; ECONOMIC MODELS ; ECONOMETRICS;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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