Tail Dependence Structure between Carbon Emission Allowances Returns Based on Copulas

Article Preview

Abstract:

This paper has focus on analyzing tail dependence structure between EUA spots returns and futures returns based on copula approach, which EUA spots negotiated on BlueNext and futures negotiated on European Climate Exchange within the European Union Emission Trading Scheme (EU ETS) during the Phase II. According to the generalized Pareto distribution (GPD) and different Copula functions, the research shows that Gumbel Copula based on the GPD marginal distribution can indicate the tail dependence structure of EUA spots returns and futures returns accurately, i.e. the dependence between upper-tails of EUA spot and Dec10 is stronger than that of lower-tails of them. In other words, EUA spots and futures are more likely to soar together than slump together during the Phase II.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

726-730

Citation:

Online since:

September 2013

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Yi-ming W., Kai W., Zhen-hua F., Rong-gang C., Carbon Finance and Carbon Market: Models and Empirical Analysis, (Science Publications, Beijing 2010), pp.9-55(In Chinese).

Google Scholar

[2] Ellerman A.D., Convery, F. & De Perthuis, C., Pricing Carbon: The European Union Emissions Trading Scheme, (Cambridge University Press, Cambridge 2010), pp.32-158.

DOI: 10.1017/cbo9781139042765

Google Scholar

[3] Chevallier J., Carbon futures and macroeconomic risk factors: A view from the EU ETS. Energy Economics, Vol. 4 (2009), pp.614-625.

DOI: 10.1016/j.eneco.2009.02.008

Google Scholar

[4] Alberola E., Chevallier J., Cheze B., Price drivers and structural breaks in European carbon prices 2005-2007. Energy Policy, Vol. 2 (2008), pp.787-797.

DOI: 10.1016/j.enpol.2007.10.029

Google Scholar

[5] Alberola E., Chevallier J., European carbon prices and banking restrictions: Evidence from phaseⅠ(2005-2007). The Energy Journal, Vol. 3 (2009), pp.51-80.

DOI: 10.5547/issn0195-6574-ej-vol30-no3-3

Google Scholar

[6] Chevallier J., Detecting instability in the volatility of carbon prices. Energy Economics, Vol. 1 (2011), pp.99-110.

DOI: 10.1016/j.eneco.2010.09.006

Google Scholar

[7] Daskalakis G., Psychoyios D., Markellos R. N., Modeling CO2 emission allowance prices and derivatives: Evidence from the European trading scheme. Journal of Banking & Finance, Vol. 7 (2009), pp.1230-1241.

DOI: 10.1016/j.jbankfin.2009.01.001

Google Scholar

[8] Zhen-hua F., Le-le Z., Yi-ming W., Carbon price volatility: Evidence from EU ETS. Applied Energy, Vol. 3 (2011), pp.590-598.

Google Scholar

[9] Kai W., Le-le Z., Yi-ming W., Analysis of carbon futures market price distribution in the EU ETS. Mathematics in Practice and Theory, Vol. 12 (2010), pp.61-67.

Google Scholar

[10] Paolella M. S., Taschini L., An econometric analysis of emission allowance prices. Journal of Banking &Finance, Vol. 10 (2008), p.2022-(2032).

DOI: 10.1016/j.jbankfin.2007.09.024

Google Scholar

[11] Benz E., Trück S., Modeling the price dynamics of CO2 emission allowances. Energy Economics, Vol. 1 (2008), pp.4-15.

DOI: 10.1016/j.eneco.2008.07.003

Google Scholar

[12] Sklar A., Fonctions de Repartition a n Dimensionset Leurs Marges. Publications de l' Institut de Statistiquede l' Universite de Paris, Vol. 8 (1959), pp.229-231.

Google Scholar

[13] McNeil A. J., Frey R., Embrechts, P., Quantitative Risk Management: Concepts, Techniques and Tools, (Princeton University Press, New Jersey 2005), pp.45-120.

DOI: 10.1017/s1748499500000300

Google Scholar

[14] Castillo J. D., Daoudi J., Estimation of the generalized Pareto distribution. Statistics & Probability Letters, Vol. 5 (2009), pp.684-688.

DOI: 10.1016/j.spl.2008.10.021

Google Scholar

[15] DuMouchel W. M., Estimating the Stable Index in Order to Measure Tail Thickness: A Critique. The Annals of Statistics, Vol. 11 (1983), pp.1019-1031.

DOI: 10.1214/aos/1176346318

Google Scholar

[16] Zivot E., Jiahui W., Modelling Financial Time Series with S-PLUS. (Springer-Verlag, Berlin and New York 2006), pp.140-223.

Google Scholar