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Long memory and crude oil’s price predictability

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  • Roy Cerqueti

    (University of Macerata)

  • Viviana Fanelli

    (University of Bari)

Abstract

This paper discusses the usefulness of the long term memory property in price prediction. In particular, the Hurst’s exponents related to a wide set of portfolios generated by three crude oils are estimated by using the detrended fluctuation analysis. To this aim, the daily empirical data on West Texas Intermediate, Brent crude oil and Dubai crude oil for a period of more than 10 years have been considered. It is shown that specific combinations are associated to persistence/antipersistence long-run behaviors, and this highlights the presence of statistical arbitrage opportunities. Such an outcome shows that long term memory can effectively serve as price predictor.

Suggested Citation

  • Roy Cerqueti & Viviana Fanelli, 2021. "Long memory and crude oil’s price predictability," Annals of Operations Research, Springer, vol. 299(1), pages 895-906, April.
    • Handle: RePEc:spr:annopr:v:299:y:2021:i:1:d:10.1007_s10479-019-03376-y
    DOI: 10.1007/s10479-019-03376-y
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    References listed on IDEAS

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    Cited by:

    1. Viviana Fanelli & Claudio Fontana & Francesco Rotondi, 2023. "A hidden Markov model for statistical arbitrage in international crude oil futures markets," Papers 2309.00875, arXiv.org, revised Sep 2024.
    2. Viviana Fanelli, 2024. "Mean-Reverting Statistical Arbitrage Strategies in Crude Oil Markets," Risks, MDPI, vol. 12(7), pages 1-19, June.

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