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GARCH and Its Variants’ Model: An Application of Crude Oil Distributions in Nigeria

Received: 27 February 2021    Accepted: 11 March 2021    Published: 26 March 2021
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Abstract

This study investigates the need for variants of GARCH model when the former fails to fully embrace clumping volatility of either a positive or negative shock via asymmetrical effect, long-memory, high-frequency, and leverage effect. The volatility effect of distributions of crude oil (prices, barrels produced and exported) in Nigeria, for the period of fifteen (15) (1: 2006 to 8:2020) years obtained from Nigeria National Petroleum Corporation (NNPC) bulletin were examined via GARCH and it variants. Exploratory Data Analysis (EDA) and time plot analyzes were carried-out on the one hundred and seventy-six (176) data points. It was deduced that GARCH (2,1) optimally generalized the prices of crude oil among its variants of gjrGARCH (2,1), apARCH (2,1), iGARCH (2,1), and csGARCH (2,1), and that positive and negative shocks did not have the same impact on the volatility of prices of crude oil. In a similar vein, iGARCH (1,1) optimized barrels of crude oil produced and exported among eGARCH (1,1), GARCCH (1,1), gjrGARCH (1,1), apARCH (1,1), iGARCH (1,1), and csGARCH (1,1) for the years of studied. However, it was inferred that positive shock as real meaningful impact on the clumping volatility on barrels of crude oil produced and exported while negative shock as no meaningful impact on the volatility on barrels of crude oil produced and exported.

Published in International Journal of Accounting, Finance and Risk Management (Volume 6, Issue 1)
DOI 10.11648/j.ijafrm.20210601.14
Page(s) 25-35
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), 2024. Published by Science Publishing Group

Keywords

Crude Oil, Volatility, Positive Shock, Negative Shock, GARCH

References
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  • APA Style

    Rasaki Olawale Olanrewaju, Ezekiel Oseni. (2021). GARCH and Its Variants’ Model: An Application of Crude Oil Distributions in Nigeria. International Journal of Accounting, Finance and Risk Management, 6(1), 25-35. https://doi.org/10.11648/j.ijafrm.20210601.14

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    ACS Style

    Rasaki Olawale Olanrewaju; Ezekiel Oseni. GARCH and Its Variants’ Model: An Application of Crude Oil Distributions in Nigeria. Int. J. Account. Finance Risk Manag. 2021, 6(1), 25-35. doi: 10.11648/j.ijafrm.20210601.14

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    AMA Style

    Rasaki Olawale Olanrewaju, Ezekiel Oseni. GARCH and Its Variants’ Model: An Application of Crude Oil Distributions in Nigeria. Int J Account Finance Risk Manag. 2021;6(1):25-35. doi: 10.11648/j.ijafrm.20210601.14

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  • @article{10.11648/j.ijafrm.20210601.14,
      author = {Rasaki Olawale Olanrewaju and Ezekiel Oseni},
      title = {GARCH and Its Variants’ Model: An Application of Crude Oil Distributions in Nigeria},
      journal = {International Journal of Accounting, Finance and Risk Management},
      volume = {6},
      number = {1},
      pages = {25-35},
      doi = {10.11648/j.ijafrm.20210601.14},
      url = {https://doi.org/10.11648/j.ijafrm.20210601.14},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijafrm.20210601.14},
      abstract = {This study investigates the need for variants of GARCH model when the former fails to fully embrace clumping volatility of either a positive or negative shock via asymmetrical effect, long-memory, high-frequency, and leverage effect. The volatility effect of distributions of crude oil (prices, barrels produced and exported) in Nigeria, for the period of fifteen (15) (1: 2006 to 8:2020) years obtained from Nigeria National Petroleum Corporation (NNPC) bulletin were examined via GARCH and it variants. Exploratory Data Analysis (EDA) and time plot analyzes were carried-out on the one hundred and seventy-six (176) data points. It was deduced that GARCH (2,1) optimally generalized the prices of crude oil among its variants of gjrGARCH (2,1), apARCH (2,1), iGARCH (2,1), and csGARCH (2,1), and that positive and negative shocks did not have the same impact on the volatility of prices of crude oil. In a similar vein, iGARCH (1,1) optimized barrels of crude oil produced and exported among eGARCH (1,1), GARCCH (1,1), gjrGARCH (1,1), apARCH (1,1), iGARCH (1,1), and csGARCH (1,1) for the years of studied. However, it was inferred that positive shock as real meaningful impact on the clumping volatility on barrels of crude oil produced and exported while negative shock as no meaningful impact on the volatility on barrels of crude oil produced and exported.},
     year = {2021}
    }
    

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  • TY  - JOUR
    T1  - GARCH and Its Variants’ Model: An Application of Crude Oil Distributions in Nigeria
    AU  - Rasaki Olawale Olanrewaju
    AU  - Ezekiel Oseni
    Y1  - 2021/03/26
    PY  - 2021
    N1  - https://doi.org/10.11648/j.ijafrm.20210601.14
    DO  - 10.11648/j.ijafrm.20210601.14
    T2  - International Journal of Accounting, Finance and Risk Management
    JF  - International Journal of Accounting, Finance and Risk Management
    JO  - International Journal of Accounting, Finance and Risk Management
    SP  - 25
    EP  - 35
    PB  - Science Publishing Group
    SN  - 2578-9376
    UR  - https://doi.org/10.11648/j.ijafrm.20210601.14
    AB  - This study investigates the need for variants of GARCH model when the former fails to fully embrace clumping volatility of either a positive or negative shock via asymmetrical effect, long-memory, high-frequency, and leverage effect. The volatility effect of distributions of crude oil (prices, barrels produced and exported) in Nigeria, for the period of fifteen (15) (1: 2006 to 8:2020) years obtained from Nigeria National Petroleum Corporation (NNPC) bulletin were examined via GARCH and it variants. Exploratory Data Analysis (EDA) and time plot analyzes were carried-out on the one hundred and seventy-six (176) data points. It was deduced that GARCH (2,1) optimally generalized the prices of crude oil among its variants of gjrGARCH (2,1), apARCH (2,1), iGARCH (2,1), and csGARCH (2,1), and that positive and negative shocks did not have the same impact on the volatility of prices of crude oil. In a similar vein, iGARCH (1,1) optimized barrels of crude oil produced and exported among eGARCH (1,1), GARCCH (1,1), gjrGARCH (1,1), apARCH (1,1), iGARCH (1,1), and csGARCH (1,1) for the years of studied. However, it was inferred that positive shock as real meaningful impact on the clumping volatility on barrels of crude oil produced and exported while negative shock as no meaningful impact on the volatility on barrels of crude oil produced and exported.
    VL  - 6
    IS  - 1
    ER  - 

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Author Information
  • Department of Mathematical Sciences, Pan African University Institute for Basic Sciences, Technology and Innovation (PAUSTI), Nairobi, Kenya

  • Department of Banking and Finance, University of Lagos, Lagos, Nigeria

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