Modeling and Explaining the Dynamics of European Union Allowance Prices at High-Frequency

Abstract

In this paper we model the adjustment process of European Union Allowance (EUA) prices to the releases of announcements at high-frequency controlling for intraday periodicity, volatility clustering and volatility persistence. We find that the high-frequency EUA price dynamics are very well captured by a fractionally integrated asymmetric power GARCH process. The decisions of the European Commission on second National Allocation Plans have a strong and immediate impact on EUA prices. On the other hand, our results suggest that EUA prices are only weakly connected to indicators about the future economic development as well as the current economic activity.

Modeling persistence of carbon emission allowance prices

“…On the other hand, only a few papers have examined the time series properties of CO 2 emission allowance prices using daily data (Paolella and Taschini, 2008;Seifert et al, 2008;Daskalakis et al, 2009;Benz and Trück, 2009;Conrad et al, 2012;Hitzemann andUhrig-Homburg, 2013 andBenschop andLópez, 2014 Our paper also uses daily data on CO 2 emission allowance prices and extends the previous literature in two directions. Firstly, by using standard long memory and I(d) techniques, and then, by extending this approach to the case of structural breaks and non-linear deterministic trends.…”

“…However, instead of using previous models or approaches already used in the literature such as mixed GARCH models (Paolella and Taschini, 2008), Markov switching and GARCH (Benz and Trück, 2009), fractionally integrated asymmetric power GARCH (Conrad et al, 2012), or Markov switching GARCH models (Benschop and López, 2014), we use other recently developed methodologies based on the concept of long run dependence or long memory processes in the context of non-linearities and structural breaks.…”

“…Some papers that analyze price drivers of CO 2 emission allowance prices are Alberola et al (2007Alberola et al ( , 2008a, Chevallier (2009), Hintermann (2010, Kim and Koo (2010), Hitzemann and Uhrig-Homburg (2013), Wang et al (2013) andHammoudeh et al (2014a,b) among many others. Price drivers of CO 2 emission allowances are temperature (Alberola et al, 2008a;Hinterman, 2010), prices of fuel, crude oil, coal and natural gas (Alberola et al, 2008a;Hintermann, 2010;Kim and Koo, 2010;Hammoudeh et al, 2014c), macroeconomic variables, production structures change and population growth (Chevalier, 2009;Conrad et al, 2012;Wang et al, 2013).…”

Forecasting volatility in oil prices with a class of nonlinear volatility models: smooth transition RBF and MLP neural networks augmented GARCH approach

“…Accordingly, the obtained model possesses such dynamics that both the conditional mean and the conditional variance follows nonlinear dynamics restricted to have two regimes between which the transition is defined by a smooth and continuously differentiable logistic function. The obtained model is defined as the logistic smooth transition asymmetric power GARCH model in which d represents the asymmetric power parameter to be estimated by nonlinear least squares or maximum likelihood methods as in the APGARCH methodology of Conrad et al (2010). The estimation of the threshold parameter n and the c parameter that defines the speed of transition is conducted through a grid search following the Terasvirta (1994).…”

“…The obtained model is defined as the logistic smooth transition fractionally integrated asymmetric power GARCH(LST-FIAPGARCH) model in which d represents the asymmetric power parameter to be estimated (Conrad et al 2010;Bildirici and Ersin 2013).…”