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State-space Implementation in Forecasting Carbon and Gas Prices in Commodity Markets

Author

Listed:
  • Rialdi Azhar

    (Department of Accounting, Faculty of Economics and Business, Universitas Lampung, Indonesia)

  • Febryan Kusuma Wisnu

    (Department of Agriculture Engineering, Faculty of Agriculture, Universitas Lampung, Indonesia)

  • Fajrin Satria Dwi Kesuma

    (Department of Management, Faculty of Economics and Business, Universitas Lampung, Indonesia)

  • Widya Rizki Eka Putri

    (Department of Accounting, Faculty of Economics and Business, Universitas Lampung, Indonesia)

  • Rian Andri Prasetya

    (Universitas Lampung)

Abstract

Carbon is a waste that becomes a new economic commodity. It has been traded like stock prices in commodity markets. Owing to its new status, research on carbon price movements as a new economic commodity linked to gas has gained a considerable amount of interest. A deeper observation of the future of world gas prices can also be an indicator of the stability of this commodity. We use the state-space model as a statistical basis for modeling the daily movement of carbon values ??and gas prices. As a result, as we have calculated, the state-space model is able to predict and provide in-depth observational information on the relationship between carbon and gas. The economic implications show that carbon is not only good for the environment; its trading in the stock exchange also indicates that it can be a new stable and sustainable economic commodity.

Suggested Citation

  • Rialdi Azhar & Febryan Kusuma Wisnu & Fajrin Satria Dwi Kesuma & Widya Rizki Eka Putri & Rian Andri Prasetya, 2022. "State-space Implementation in Forecasting Carbon and Gas Prices in Commodity Markets," International Journal of Energy Economics and Policy, Econjournals, vol. 12(3), pages 280-286, May.
    • Handle: RePEc:eco:journ2:2022-03-30
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    References listed on IDEAS

    as
    1. Ross Garnaut & Stephen Howes & Frank Jotzo & Peter Sheehan, 2008. "Emissions in the Platinum Age: the implications of rapid development for climate-change mitigation," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 24(2), pages 377-401, Summer.
    2. Chevallier, Julien, 2011. "Detecting instability in the volatility of carbon prices," Energy Economics, Elsevier, vol. 33(1), pages 99-110, January.
    3. Ernie Hendrawaty & Rialdi Azhar & Fajrin Satria Dwi Kesumah & Sari Indah Oktanti Sembiring & Mega Metalia, 2021. "Modelling and Forecasting Crude Oil Prices during COVID-19 Pandemic," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 149-154.
    4. Ambya Ambya & Toto Gunarto & Ernie Hendrawaty & Fajrin Satria Dwi Kesumah & Febryan Kusuma Wisnu, 2020. "Future Natural Gas Price Forecasting Model and Its Policy Implication," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 64-70.
    5. Dhani Setyawan & Rakhmin Dyarto & Hadi Setiawan & Rita Helbra Tenrini & Sofia Arie Damayanty, 2020. "Examining the Driving Forces Affecting Energy Intensity during Financial Crisis: Evidence from ASEAN-6 Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 71-81.
    6. repec:dau:papers:123456789/5110 is not listed on IDEAS
    7. Batten, Jonathan A. & Maddox, Grace E. & Young, Martin R., 2021. "Does weather, or energy prices, affect carbon prices?," Energy Economics, Elsevier, vol. 96(C).
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    Cited by:

    1. Ayi Ahadiat & Fajrin Satria Dwi Kesumah & Rialdi Azhar & Febryan Kusuma Wisnu, 2023. "Strategic Decision-Making on Mining Sector Company Stock Prices and Economic Variable (State Space Model Application)," International Journal of Energy Economics and Policy, Econjournals, vol. 13(3), pages 177-184, May.

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    More about this item

    Keywords

    Commodity Markets; Forecasting; State Space Model; Carbon; Natural Gas;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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