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Free lunch in the oil market: a note on Long Memory

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  • Sylvain Prado

    (EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

Abstract

In the crude oil market the phenomenon of Long Memory can be easily identified with the help of the simple (but effective) methodology of Katsumi Shimotsu. The Exact Local Whittle estimator and two testing strategies provide a strong assessment of the phenomenon. We present evidences and we suggest a profit opportunity. Furthermore, the existence of Long Memory discloses an inefficient oil market.

Suggested Citation

  • Sylvain Prado, 2011. "Free lunch in the oil market: a note on Long Memory," Working Papers hal-04140982, HAL.
    • Handle: RePEc:hal:wpaper:hal-04140982
    Note: View the original document on HAL open archive server: https://hal.science/hal-04140982
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    References listed on IDEAS

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    1. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
    2. Leïla Nouira & Ibrahim Ahamada & Jamel Jouini & Alain Nurbel, 2004. "Long memory and shifts in the unconditional variance in the exchange rate euro/us dollar returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00272871, HAL.
    3. Katsumi Shimotsu, 2006. "Simple (but Effective) Tests Of Long Memory Versus Structural Breaks," Working Paper 1101, Economics Department, Queen's University.
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    5. Amine LAHIANI & Mohamed EL HEDI AROURI & Duc KHUONG NGUYEN, 2010. "Forecasting the Conditional Volatility of Spot and Futures Oil Prices with Structural Breaks and Long Memory Models," EcoMod2010 259600101, EcoMod.
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    Cited by:

    1. Delavari, Majid & Gandali Alikhani, Nadiya & Naderi, Esmaeil, 2013. "Does long memory matter in forecasting oil price volatility?," MPRA Paper 46356, University Library of Munich, Germany.
    2. Delavari, Majid & Gandali Alikhani, Nadiya, 2012. "The Effect of Crude Oil Price on the Methanol price," MPRA Paper 49727, University Library of Munich, Germany.
    3. Akbar Komijani & Esmaeil Naderi & Nadiya Gandali Alikhani, 2014. "A hybrid approach for forecasting of oil prices volatility," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 38(3), pages 323-340, September.

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    More about this item

    Keywords

    oil market; long memory; ARFIMA-FIGARCH;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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