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

Sharon S. Yang, Jr-Wei Huang and Chuang-Chang Chang

Quantitative Finance, 2016, vol. 16, issue 5, 749-762

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.

Date: 2016
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DOI: 10.1080/14697688.2015.1059953

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