On Carbon Emission Credits Options Pricing

Abstract

The effect of adverse climate change is of major concern worldwide and several approaches are being developed to mitigate against anticipated economic and social disaster. Carbon emissions has been identified as a major contributor to the adverse climate change and following the Kyoto protocol , European countries have , through a caucus, effected a market to reward or fine members depending on their compliance position. The commodity for the market is the carbon emission credits. Stochastic models for pricing of options on these credits are considered in this paper. In particular, we determine the price basing on the Normal Inverse Gaussian and the Brownian Motion models. Maximum Likelihood Estimation is applied to determine model parameter estimates in each case. It is shown that the Normal Inverse Gaussian model has a better fit to the data but gives higher prices for a given strike price , compared to the Brownian Motion model.