[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/baf/cbafwp/cbafwp1886.html
   My bibliography  Save this paper

Forecasting Commodity Futures Returns: An Economic Value Analysis of Macroeconomic vs. Specific Factors

Author

Listed:
  • Massimo Guidolin
  • Manuela Pedio
Abstract
We test whether three well-known commodity-specific variables (basis, hedging pressure, and momentum) may improve the predictive power for commodity futures returns of models otherwise based on macroeconomic factors. We compute recursive, out-of-sample forecasts for fifteen monthly commodity futures return series, when estimation is based on a stepwise regression approach under a probability-weighted regime-switching regression that identifies different volatility regimes. Comparisons with an AR(1) benchmark show that the inclusion of commodity-specific factors does not improve the forecasting power. We perform a back-testing exercise of a meanvariance investment strategy that exploits any predictability of the conditional risk premium of commodities, stocks, and bond returns, also taking into account transaction costs caused by portfolio rebalancing. The risk-adjusted performance of this strategy does not allow us to conclude that any forecasting approach outperforms the others. However, there is evidence that investment strategies based on commodity-specific predictors outperform the remaining strategies in the high-volatility state.

Suggested Citation

  • Massimo Guidolin & Manuela Pedio, 2018. "Forecasting Commodity Futures Returns: An Economic Value Analysis of Macroeconomic vs. Specific Factors," BAFFI CAREFIN Working Papers 1886, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    • Handle: RePEc:baf:cbafwp:cbafwp1886
    as

    Download full text from publisher

    File URL: https://repec.unibocconi.it/baffic/baf/papers/cbafwp1886.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. Sydney C. Ludvigson & Serena Ng, 2009. "Macro Factors in Bond Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5027-5067, December.
    3. Hong, Harrison & Yogo, Motohiro, 2012. "What does futures market interest tell us about the macroeconomy and asset prices?," Journal of Financial Economics, Elsevier, vol. 105(3), pages 473-490.
    4. Bessembinder, Hendrik & Chan, Kalok, 1992. "Time-varying risk premia and forecastable returns in futures markets," Journal of Financial Economics, Elsevier, vol. 32(2), pages 169-193, October.
    5. Rapach, David E. & Wohar, Mark E., 2006. "In-sample vs. out-of-sample tests of stock return predictability in the context of data mining," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 231-247, March.
    6. Frans A. De Roon & Theo E. Nijman & Chris Veld, 2000. "Hedging Pressure Effects in Futures Markets," Journal of Finance, American Finance Association, vol. 55(3), pages 1437-1456, June.
    7. Nicholas Kaldor, 1939. "Speculation and Economic Stability," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 7(1), pages 1-27.
    8. Scott H. Irwin & Dwight R. Sanders, 2011. "Index Funds, Financialization, and Commodity Futures Markets," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(1), pages 1-31.
    9. Gerald R. Jensen & Robert R. Johnson & Jeffrey M. Mercer, 2000. "Efficient use of commodity futures in diversified portfolios," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 20(5), pages 489-506, May.
    10. Stoll, Hans R., 1979. "Commodity Futures and Spot Price Determination and Hedging in Capital Market Equilibrium," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 14(4), pages 873-894, November.
    11. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    12. Victor DeMiguel & Lorenzo Garlappi & Francisco J. Nogales & Raman Uppal, 2009. "A Generalized Approach to Portfolio Optimization: Improving Performance by Constraining Portfolio Norms," Management Science, INFORMS, vol. 55(5), pages 798-812, May.
    13. Giampietro, Marta & Guidolin, Massimo & Pedio, Manuela, 2018. "Estimating stochastic discount factor models with hidden regimes: Applications to commodity pricing," European Journal of Operational Research, Elsevier, vol. 265(2), pages 685-702.
    14. Gary B. Gorton & Fumio Hayashi & K. Geert Rouwenhorst, 2013. "The Fundamentals of Commodity Futures Returns," Review of Finance, European Finance Association, vol. 17(1), pages 35-105.
    15. Stock, James H. & Watson, Mark W., 2006. "Forecasting with Many Predictors," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 10, pages 515-554, Elsevier.
    16. Paresh Kumar Narayan & Huson Ali Ahmed & Seema Narayan, 2015. "Do Momentum‐Based Trading Strategies Work in the Commodity Futures Markets?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(9), pages 868-891, September.
    17. Qian Shen & Andrew C. Szakmary & Subhash C. Sharma, 2007. "An examination of momentum strategies in commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 27(3), pages 227-256, March.
    18. Bossaerts, Peter & Hillion, Pierre, 1999. "Implementing Statistical Criteria to Select Return Forecasting Models: What Do We Learn?," The Review of Financial Studies, Society for Financial Studies, vol. 12(2), pages 405-428.
    19. David Hirshleifer, 1988. "Residual Risk, Trading Costs, and Commodity Futures Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 1(2), pages 173-193.
    20. Daskalaki, Charoula & Skiadopoulos, George, 2011. "Should investors include commodities in their portfolios after all? New evidence," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2606-2626, October.
    21. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    22. Gargano, Antonio & Timmermann, Allan, 2014. "Forecasting commodity price indexes using macroeconomic and financial predictors," International Journal of Forecasting, Elsevier, vol. 30(3), pages 825-843.
    23. James D. Hamilton & Jing Cynthia Wu, 2015. "Effects Of Index‐Fund Investing On Commodity Futures Prices," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56, pages 187-205, February.
    24. Bassam Fattouh & Lavan Mahadeva, 2014. "Causes and Implications of Shifts in Financial Participation in Commodity Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(8), pages 757-787, August.
    25. Daskalaki, Charoula & Kostakis, Alexandros & Skiadopoulos, George, 2014. "Are there common factors in individual commodity futures returns?," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 346-363.
    26. Leyuan You & Robert T. Daigler, 2013. "A Markowitz Optimization of Commodity Futures Portfolios," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(4), pages 343-368, April.
    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. Wang, Yudong & Liu, Li & Wu, Chongfeng, 2020. "Forecasting commodity prices out-of-sample: Can technical indicators help?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 666-683.
    2. Massimo Guidolin & Manuela Pedio, 2020. "Distilling Large Information Sets to Forecast Commodity Returns: Automatic Variable Selection or HiddenMarkov Models?," BAFFI CAREFIN Working Papers 20140, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

    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. Massimo Guidolin & Manuela Pedio, 2021. "Forecasting commodity futures returns with stepwise regressions: Do commodity-specific factors help?," Annals of Operations Research, Springer, vol. 299(1), pages 1317-1356, April.
    2. Massimo Guidolin & Manuela Pedio, 2020. "Distilling Large Information Sets to Forecast Commodity Returns: Automatic Variable Selection or HiddenMarkov Models?," BAFFI CAREFIN Working Papers 20140, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    3. Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2017. "Predictability and diversification benefits of investing in commodity and currency futures," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 52-66.
    4. Massimo Guidolin & Manuela Pedio, 2022. "Switching Coefficients or Automatic Variable Selection: An Application in Forecasting Commodity Returns," Forecasting, MDPI, vol. 4(1), pages 1-32, February.
    5. Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2023. "Commodity futures return predictability and intertemporal asset pricing," Journal of Commodity Markets, Elsevier, vol. 31(C).
    6. Miffre, Joëlle, 2016. "Long-short commodity investing: A review of the literature," Journal of Commodity Markets, Elsevier, vol. 1(1), pages 3-13.
    7. Daskalaki, Charoula & Skiadopoulos, George & Topaloglou, Nikolas, 2017. "Diversification benefits of commodities: A stochastic dominance efficiency approach," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 250-269.
    8. Ahmed, Shamim & Tsvetanov, Daniel, 2016. "The predictive performance of commodity futures risk factors," Journal of Banking & Finance, Elsevier, vol. 71(C), pages 20-36.
    9. Sakkas, Athanasios & Tessaromatis, Nikolaos, 2020. "Factor based commodity investing," Journal of Banking & Finance, Elsevier, vol. 115(C).
    10. Guillermo Llorente & Jiang Wang, 2020. "Trading and information in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(8), pages 1231-1263, August.
    11. Charoula Daskalaki, 2021. "New evidence on commodity stocks," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(6), pages 811-874, June.
    12. Hollstein, Fabian & Prokopczuk, Marcel & Tharann, Björn & Wese Simen, Chardin, 2021. "Predictability in commodity markets: Evidence from more than a century," Journal of Commodity Markets, Elsevier, vol. 24(C).
    13. Bredin, Don & O'Sullivan, Conall & Spencer, Simon, 2021. "Forecasting WTI crude oil futures returns: Does the term structure help?," Energy Economics, Elsevier, vol. 100(C).
    14. Gurdip Bakshi & Xiaohui Gao & Alberto G. Rossi, 2019. "Understanding the Sources of Risk Underlying the Cross Section of Commodity Returns," Management Science, INFORMS, vol. 65(2), pages 619-641, February.
    15. Daskalaki, Charoula & Skiadopoulos, George & Topaloglou, Nikolas, 2017. "Diversification benefits of commodities: A stochastic dominance efficiency approach," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 250-269.
    16. Sercan Demiralay & Selcuk Bayraci & H. Gaye Gencer, 2019. "Time-varying diversification benefits of commodity futures," Empirical Economics, Springer, vol. 56(6), pages 1823-1853, June.
    17. Mohammad Isleimeyyeh, 2020. "The role of financial investors in determining the commodity futures risk premium," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(9), pages 1375-1397, September.
    18. Bätje, Fabian & Menkhoff, Lukas, 2016. "Predicting the equity premium via its components," VfS Annual Conference 2016 (Augsburg): Demographic Change 145789, Verein für Socialpolitik / German Economic Association.
    19. Adams, Zeno & Glück, Thorsten, 2015. "Financialization in commodity markets: A passing trend or the new normal?," Journal of Banking & Finance, Elsevier, vol. 60(C), pages 93-111.
    20. ap Gwilym, Rhys & Ebrahim, M. Shahid & El Alaoui, Abdelkader O. & Rahman, Hamid & Taamouti, Abderrahim, 2020. "Financial frictions and the futures pricing puzzle," Economic Modelling, Elsevier, vol. 87(C), pages 358-371.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:baf:cbafwp:cbafwp1886. 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: Michela Pozzi (email available below). General contact details of provider: https://edirc.repec.org/data/cbbocit.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.