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Forecasting Price Direction, Hedging and Spread Options in Oil Volatility

Received: 5 April 2017     Accepted: 8 October 2017     Published: 8 November 2017
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Abstract

The energy market aims to manage risks associated with prices and volatility of the asset. It is a capital intensive market, rippled with a range of chaotic, complex and dynamic interaction among its supply and demand derivatives. Models help users forecast such interactions, to provide investors with empirical evidence of the price direction. Evolutionary modeling is an art, whose science seeks to analyze input data and yield an optimal, complete solution for which conventional methods yield a corresponding, non-cost effective solution. Its solutions are tractable, robust and low-cost with a tolerance of ambiguity, uncertainty and noise as applied to its input. Our study aims to predict the OPEC Oil market with data collected over the period.

Published in International Journal of Economic Behavior and Organization (Volume 5, Issue 6)
DOI 10.11648/j.ijebo.20170506.11
Page(s) 114-123
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Energy, OPEC, Stochastic, Evolutionary Model, Price Direction, Volatility

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Cite This Article
  • APA Style

    Eboka Andrew Okonji, Yerokun Oluwatoyin Mary. (2017). Forecasting Price Direction, Hedging and Spread Options in Oil Volatility. International Journal of Economic Behavior and Organization, 5(6), 114-123. https://doi.org/10.11648/j.ijebo.20170506.11

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    ACS Style

    Eboka Andrew Okonji; Yerokun Oluwatoyin Mary. Forecasting Price Direction, Hedging and Spread Options in Oil Volatility. Int. J. Econ. Behav. Organ. 2017, 5(6), 114-123. doi: 10.11648/j.ijebo.20170506.11

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    AMA Style

    Eboka Andrew Okonji, Yerokun Oluwatoyin Mary. Forecasting Price Direction, Hedging and Spread Options in Oil Volatility. Int J Econ Behav Organ. 2017;5(6):114-123. doi: 10.11648/j.ijebo.20170506.11

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  • @article{10.11648/j.ijebo.20170506.11,
      author = {Eboka Andrew Okonji and Yerokun Oluwatoyin Mary},
      title = {Forecasting Price Direction, Hedging and Spread Options in Oil Volatility},
      journal = {International Journal of Economic Behavior and Organization},
      volume = {5},
      number = {6},
      pages = {114-123},
      doi = {10.11648/j.ijebo.20170506.11},
      url = {https://doi.org/10.11648/j.ijebo.20170506.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijebo.20170506.11},
      abstract = {The energy market aims to manage risks associated with prices and volatility of the asset. It is a capital intensive market, rippled with a range of chaotic, complex and dynamic interaction among its supply and demand derivatives. Models help users forecast such interactions, to provide investors with empirical evidence of the price direction. Evolutionary modeling is an art, whose science seeks to analyze input data and yield an optimal, complete solution for which conventional methods yield a corresponding, non-cost effective solution. Its solutions are tractable, robust and low-cost with a tolerance of ambiguity, uncertainty and noise as applied to its input. Our study aims to predict the OPEC Oil market with data collected over the period.},
     year = {2017}
    }
    

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    AU  - Eboka Andrew Okonji
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    AB  - The energy market aims to manage risks associated with prices and volatility of the asset. It is a capital intensive market, rippled with a range of chaotic, complex and dynamic interaction among its supply and demand derivatives. Models help users forecast such interactions, to provide investors with empirical evidence of the price direction. Evolutionary modeling is an art, whose science seeks to analyze input data and yield an optimal, complete solution for which conventional methods yield a corresponding, non-cost effective solution. Its solutions are tractable, robust and low-cost with a tolerance of ambiguity, uncertainty and noise as applied to its input. Our study aims to predict the OPEC Oil market with data collected over the period.
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Author Information
  • Department of Computer Education, Federal College of Education Technical, Asaba, Nigeria

  • Department of Computer Education, Federal College of Education Technical, Asaba, Nigeria

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