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Direction-of-change forecasting in commodity futures markets

Jiadong Liu, Fotis Papailias and Barry Quinn

International Review of Financial Analysis, 2021, vol. 74, issue C

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.

Keywords: Forecasting commodity futures; Direction-of-change; Dynamic probit model; Variable length Markov chain; Return signal momentum (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:74:y:2021:i:c:s105752192100020x

DOI: 10.1016/j.irfa.2021.101677

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