Carbon price forecasting with a hybrid Arima and least squares support vector machines methodology
B Zhu, J Chevallier, B Zhu, J Chevallier - Pricing and forecasting carbon …, 2017 - Springer
B Zhu, J Chevallier, B Zhu, J Chevallier
Pricing and forecasting carbon markets: Models and empirical analyses, 2017•SpringerThis chapter advances a hybrid forecasting model for the carbon market. The technology is
based on Least Squares Support Vector Machines augmented by particle swarm
optimization (PSO). This innovation reaches superior forecasting results in a horse-race
containing several combinations of ARIMA time series models.
based on Least Squares Support Vector Machines augmented by particle swarm
optimization (PSO). This innovation reaches superior forecasting results in a horse-race
containing several combinations of ARIMA time series models.
Abstract
This chapter advances a hybrid forecasting model for the carbon market. The technology is based on Least Squares Support Vector Machines augmented by particle swarm optimization (PSO). This innovation reaches superior forecasting results in a horse-race containing several combinations of ARIMA time series models.
Springer
