Economics at your fingertips  

Nonparametric modeling of carbon prices

Julien Chevallier

Energy Economics, 2011, vol. 33, issue 6, 1267-1282

Abstract: This paper constitutes the first exercise of nonparametric modeling applied to carbon markets. The framework of analysis is carefully detailed, and the empirical application unfolds in the case of BlueNext spot and ECX futures prices. The data is gathered in daily frequency from April 2005 to April 2010. First, we document the presence of strong nonlinearities in the conditional mean functions. Second, the conditional volatility functions reveal an asymmetric and heteroskedastic behavior which is dramatically different between carbon spot and futures logreturns. The results for spot prices are also robust to subsamples' decomposition. Third, we show in an out-of-sample forecasting exercise that nonparametric modeling allows reducing the prediction error by almost 15% compared to linear AR models. This latter result is confirmed by the Diebold–Mariano pairwise test statistic.

Keywords: Carbon prices; Nonparametric modeling; Conditional volatility modeling; Out-of-sample forecasting (search for similar items in EconPapers)
JEL-codes: C32 G12 G15 Q43 (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10) Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this article

Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant

More articles in Energy Economics from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().

Page updated 2019-11-24
Handle: RePEc:eee:eneeco:v:33:y:2011:i:6:p:1267-1282