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Direction-of-change forecasting in commodity futures markets

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  • Liu, Jiadong
  • Papailias, Fotis
  • Quinn, Barry

Abstract

This paper examines direction-of-change predictability in commodity futures markets using a variety of binary probabilistic techniques. As well as traditional techniques, we apply Variable Length Markov Chain (VLMC) analysis, an innovative technique popularised in computational biology when predicting DNA sequences (Bühlmann & Wyner, 1999). To the best of our knowledge, this is the first application of VLMC in finance. Our results show that both VLMC and technical analysis methods provide strong predictability of the direction-of-change of commodity returns, with annualised mean returns of approximately 8%, substantially higher than the passive long strategy. Our results suggest that a short-term learning effect is present in commodities market which can be exploited using innovative direction-of-change forecasting techniques.

Suggested Citation

  • Liu, Jiadong & Papailias, Fotis & Quinn, Barry, 2021. "Direction-of-change forecasting in commodity futures markets," International Review of Financial Analysis, Elsevier, vol. 74(C).
    • Handle: RePEc:eee:finana:v:74:y:2021:i:c:s105752192100020x
    DOI: 10.1016/j.irfa.2021.101677
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