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Volatility in CO2 EUAs returns: a FIGARCH approach

Authors: Belbute, José;

Volatility in CO2 EUAs returns: a FIGARCH approach

Abstract

This paper models volatility in CO2 EUA’s emission returns using a FIGARCH approach. Our findings overwhelmingly suggest that conditional variance in CO2 emissions allowance returns is stationary and mean reverting, but with autocorrelations decaying at a hyperbolic rate, thereby a shock to forecast of future conditional variance will be temporary but it last longer. Our results have important policy implications since the knowledge of the stochastic properties of the conditional variance is of particular relevance for investment decisions in abatement activities, for the design of arbitrage strategies to take advantage of momentary opportunities in energy markets. Moreover, our results also suggest the importance of accounting for the interactions of volatility in EUA’s CO2 emissions market with energy sectors, the economy, and climate both in terms of modeling and forecasting

Country
Portugal
Related Organizations
Keywords

volarility, CO2 emission prices, volatility, CO2emissions prices, FIGARCH

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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