Detecting and modelling the jump risk of CO2 emission allowances and their impact on the valuation of option on futures contracts

Modelling CO₂ emission allowance prices is important for pricing CO₂ emission allowance linked assets in the emissions trading scheme (ETS). Some statistical properties of CO₂ 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 CO₂ 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 CO₂ emission allowance prices. We establish a general framework for pricing CO₂ emission allowance options on futures contracts with these properties and find that the jump risk significantly affects the value of the CO₂ emission allowance option on futures contracts. More importantly, we demonstrate that the dynamic jump ARMA–GARCH model can provide more accurate valuations of the CO₂ emission allowance options on futures than other models in terms of pricing error.