This article investigates temperature behavior to develop a temperature model. The proposed ARFIMA Seasonal GARCH model that allows for long memory effects and other important temperature properties provides better goodness of fits and forecasting accuracy using daily average temperatures in six U.S. cities. The effect of temperature behavior on pricing temperature derivatives is analyzed. We propose an equilibrium option pricing framework for HDD and CDD forward and option contracts under the ARFIMA Seasonal GARCH model. The investigation of temperature properties and the valuation framework in this study contributes to the development of a standardized temperature model for weather derivative markets.

No 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.

No abstract