Abstract: The EU Emission Trading System (EU ETS) was created to reduce the CO2 and other greenhouse gas emissions at the lowest economic cost. In reality market participants are faced with considerable uncertainty due to price changes and require price and volatility estimates and forecasts for appropriate risk management, asset allocation and volatility trading. Although the simplest approach to estimate volatility is to use the historical standard deviation, realized volatility is a more accurate measure for volatility, since it is based on intraday data. Besides the stylized facts commonly observed in financial time series, we observe long-memory properties in the realized volatility series, which motivates the use of Heterogeneous Autoregressive (HAR) class models. Therefore, we propose to model and forecast the realized volatility of the EU ETS futures with HAR class models. The HAR models outperform benchmark models such as the standard long-memory ARFIMA model in terms of model fit, in-sample and out-of-sample forecasting. The analysis is based on intraday data (May 2007-April 2012) for futures on CO2 certificates for the second EU-ETS trading period (expiry December 2008-2012). The estimation results of the models allow to explain the volatility drivers in the market and volatility structure, according to the Heterogeneous Market Hypothesis as well as the observed asymmetries. We see that both speculators with short investment horizons as well as traders taking long-term hedging positions are active in the market. In a simulation study we test the suitability of the HAR model for option pricing and conclude that the HAR model is capable of mimicking the long-term volatility structure in the futures market and can be used for short-term and long-term option pricing.





Key Words: EU ETS, Realized Volatility, HAR, Volatility Forecasting, Intraday Data, CO2 Emission Allowances, Emissions Markets, Asymmetry, SHAR, HARQ, MC Simulation