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Persistency of Price Patterns in the International Oil Industry, 2001-2016

Author

Listed:
  • Ana Lorena Jim nez-Preciado

    (Instituto Polit cnico Nacional, Mexico)

  • Salvador Cruz-Ak

    (Instituto Polit cnico Nacional, Mexico)

  • Francisco Venegas-Mart nez

    (Instituto Polit cnico Nacional, Mexico)

Abstract

This paper is aimed at studying price patterns and their persistency in selected international oil companies (Exxon Mobil, British Petroleum, Royal Dutch Shell, and China Petroleum Sinopec). The proposal uses a one-step counting of price patterns and a two-step counting derived from transition probabilities of price patterns both procedures based on Japanese candlesticks. An extension of Kolmogorov Smirnov test for discrete variables, provided by Taylor and Emerson (2011), is used to measure the statistical significance of the obtained results. Furthermore, the persistence of patterns is examined via the correlation in two-step conditional probabilities by using Blomqvist s beta test. This method is useful to identify patterns even under market booms and busts, and in high and low volatility environments.

Suggested Citation

  • Ana Lorena Jim nez-Preciado & Salvador Cruz-Ak & Francisco Venegas-Mart nez, 2017. "Persistency of Price Patterns in the International Oil Industry, 2001-2016," International Journal of Energy Economics and Policy, Econjournals, vol. 7(1), pages 9-18.
  • Handle: RePEc:eco:journ2:2017-01-02
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    References listed on IDEAS

    as
    1. Jammazi, Rania, 2012. "Cross dynamics of oil-stock interactions: A redundant wavelet analysis," Energy, Elsevier, vol. 44(1), pages 750-777.
    2. Philip K. Verleger Jr., 2015. "Structure Matters: Oil Markets Enter the Adelman Era," The Energy Journal, International Association for Energy Economics, vol. 0(Adelman S).
    3. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
    4. Jiang, Zhi-Qiang & Xie, Wen-Jie & Zhou, Wei-Xing, 2014. "Testing the weak-form efficiency of the WTI crude oil futures market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 235-244.
    5. Alessandro Roncaglia, 2015. "Oil and its markets," PSL Quarterly Review, Economia civile, vol. 68(273), pages 151-175.
    6. Ibarra-Valdez, C. & Alvarez, J. & Alvarez-Ramirez, J., 2016. "Randomness confidence bands of fractal scaling exponents for financial price returns," Chaos, Solitons & Fractals, Elsevier, vol. 83(C), pages 119-124.
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    More about this item

    Keywords

    Oil Industry; Transition Probabilities; Persistent Price Patterns;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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