This paper proposes a new methodology for carbon price forecasting. It posits a finite distributed lag (FDL) model and then applies a GA-ridge algorithm to determine a set of proper predictors with coefficient estimates. An empirical study was conducted in the European Union Greenhouse Gas Emissions Trading market, revealing that our methodology not only yields good forecasting results but also provides some interesting analysis on the carbon price market. It turns out that the combination of the FDL model and GA-ridge algorithm is desirable for forecasting and analyzing the complicated carbon price market because of its capability of selecting proper predictors from a class of predictors of itself.
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© 2014 Wiley Publishing Ltd.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Theoretical Computer Science
- Computational Theory and Mathematics
- Artificial Intelligence