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Detecting and modelling the jump risk of CO 2 emission allowances and their impact on the valuation of option on futures contracts

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  • Sharon S. Yang
  • Jr-Wei Huang
  • Chuang-Chang Chang

Abstract

Modelling CO 2 emission allowance prices is important for pricing CO 2 emission allowance linked assets in the emissions trading scheme (ETS). Some statistical properties of CO 2 emission allowance prices have been discovered in the literature ignoring price jumps. By employing real data from the ETS, this research first detects the jump risk using a jump test and then verifies jump effects in modelling CO 2 emission allowance prices by comparing the in-sample and out-of-sample model performance. We suggest a model which can capture the statistical properties of autocorrelation, volatility clustering and jump effects is more appropriate for modelling CO 2 emission allowance prices. We establish a general framework for pricing CO 2 emission allowance options on futures contracts with these properties and find that the jump risk significantly affects the value of the CO 2 emission allowance option on futures contracts. More importantly, we demonstrate that the dynamic jump ARMA--GARCH model can provide more accurate valuations of the CO 2 emission allowance options on futures than other models in terms of pricing error.

Suggested Citation

  • Sharon S. Yang & Jr-Wei Huang & Chuang-Chang Chang, 2016. "Detecting and modelling the jump risk of CO 2 emission allowances and their impact on the valuation of option on futures contracts," Quantitative Finance, Taylor & Francis Journals, vol. 16(5), pages 749-762, May.
    • Handle: RePEc:taf:quantf:v:16:y:2016:i:5:p:749-762
    DOI: 10.1080/14697688.2015.1059953
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    2. Tang, Ling & Wang, Haohan & Li, Ling & Yang, Kaitong & Mi, Zhifu, 2020. "Quantitative models in emission trading system research: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).

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