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Multi-stage emissions management of a steel company

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    0502673 - ÚTIA 2021 RIV US eng J - Journal Article
    Zapletal, F. - Šmíd, Martin - Kopa, M.
    Multi-stage emissions management of a steel company.
    Annals of Operations Research. Roč. 292, č. 2 (2020), s. 735-751. ISSN 0254-5330. E-ISSN 1572-9338
    R&D Projects: GA ČR(CZ) GA16-01298S
    Institutional support: RVO:67985556
    Keywords : Multiperiod CVaR * Multi-stage model * Stochastic programming * Emission allowance * Steel company
    OECD category: Statistics and probability
    Impact factor: 4.854, year: 2020
    Method of publishing: Limited access
    http://library.utia.cas.cz/separaty/2019/E/smid-0502673.pdf https://link.springer.com/article/10.1007/s10479-019-03192-4

    We present a multi-stage model for determining the optimal production and emissions coverage for an industrial company participating in the European Emissions Trading System. This model is adapted for a real-life European steel company. A mean-multiperiod CVaR is used as a decision criterion. There are two stochastic parameters-market demand for products and emissions allowance price. The aim of this paper is to explore the costs and risk of a company caused by emissions trading. The presented model is solved for various values of the risk aversion parameters and initial price of the allowance. As a result, it is found that the production is little influenced by the price of allowances and it nearly does not depend on risk-aversion. The probability of the company’s default, on the other hand, is significantly influenced by the emission prices. Futures on allowances as well as banking (i.e., transferring allowances between periods) are used to reduce the risks of the emissions trading. We further exploit the same situation under different settings, namely, given random price margins, and time-dependent, deterministic and positively contaminated distributions of demand. In all these cases, the results follow patterns similar to those given the original setting.
    Permanent Link: http://hdl.handle.net/11104/0295686

     
     
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