Nonparametric modeling of carbon prices

► This paper constitutes the first exercise of nonparametric modeling applied to BlueNext spot and ECX futures carbon prices in daily frequency from April 2005 to April 2010. ► We document the presence of strong nonlinearities in the conditional mean functions. ► 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. ► Nonparametric modeling allows reducing the prediction error by almost 15% compared to linear AR models, as confirmed by the Diebold-Mariano pairwise test statistic.