Carbon Trading in Indian Derivative Market: An Econometric Validation

Abstract

Global climate change has already had observable effects on the environment. Glaciers have shrunk, ice on rivers and lakes is breaking up earlier, plant and animal ranges have shifted and trees are flowering sooner. According to Intergovernmental Panel on Climate Change the net damage cost of climate change are likely to be significant and is likely to be increase over overtime.Carbon dioxide is a big cause of global panic as its concentration has been rising alarmingly in the atmosphere. On the other side it has created a global carbon market also. Hence with growing concerns owing to Kyoto Protocol amongst countries to curtail pollution levels along with sustaining their economic growth, the Emission Trading (ET) industry has started actively providing support to bring down green house gas emission by allocating a monetary value and is expected to come forward as a massive market of global emission trading. The developed countries are supposed to meet certain carbon emission targets fixed by their respective governments. Conversely if they are unable to do so they have an option of buying these in the market from those companies which have surplus of them. This practice is known as carbon trading. Even for developing nations it is a very lucrative as it endow them with fiscal gains for swapping carbon credits with latest technology. This modified technology ultimately facilitates them to condense carbon emanation. In India it's trading started in Multi Commodity Exchange of India from the month of April, 2008. The main objective of the paper is to discuss information spillover in the carbon emissions derivative market in India under the VAR framework and to understand volatility spillover in the future and spot market by using bivariate E-GARCH model. The results reveal that there is a co-integrating relationship between future and spot prices of Carbon Emission Reduction (CER), traded on MCX. The error correction mechanism exhibits bi-lateral adjustments to attain equilibrium with more adjustments in future prices is seen, and to add robustness in the results of VECM, Variance Decomposition and Impulse response were also conducted. To understand the direction of causality, Granger causality test was done, the results of which show bi-lateral causality in the price pairs. The results signify that this market is informationally efficient with the lead role of spot market. Volatility dynamics also show bilateral spillover i.e. from future to spot market and vice versa. Generally, our findings demonstrate numerous imperative inferences for portfolio hedgers in creating optimal portfolio allotment, appealing in risk management and forecasting Carbon market potential volatility.