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The predictability of aggregate returns on commodity futures

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  • Lutzenberger, Fabian T.

Abstract

This paper provides evidence that aggregate returns on commodity futures (without the returns on collateral) are predictable, both in-sample and out-of-sample, by various lagged variables from the stock market, bond market, macroeconomics, and the commodity market. Out of the 32 candidate predictors we consider, we find that investor sentiment is the best in-sample predictor of short-horizon returns, whereas the level and slope of the yield curve have much in-sample predictive power for long-horizon returns. We find that it is possible to forecast aggregate returns on commodity futures out-of-sample through several combination forecasts (the out-of-sample return forecasting R2 is up to 1.65% at the monthly frequency).

Suggested Citation

  • Lutzenberger, Fabian T., 2014. "The predictability of aggregate returns on commodity futures," Review of Financial Economics, Elsevier, vol. 23(3), pages 120-130.
  • Handle: RePEc:eee:revfin:v:23:y:2014:i:3:p:120-130
    DOI: 10.1016/j.rfe.2014.02.001
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    3. Jangkoo Kang & Kyung Yoon Kwon, 2019. "How about selling commodity futures losers?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1489-1514, December.
    4. Rehman, Mobeen Ur & Owusu Junior, Peterson & Ahmad, Nasir & Vo, Xuan Vinh, 2022. "Time-varying risk analysis for commodity futures," Resources Policy, Elsevier, vol. 78(C).

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    More about this item

    Keywords

    Asset pricing; Commodities; Predictability of returns; Predictive regressions; Forecasting;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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