Carbon Price Forecasting: Which Driven Factors Can Help

40 Pages Posted: 30 Jul 2019

See all articles by Xiaohang Ren

Xiaohang Ren

University of Southampton

Kun Duan

University of Southampton - Southampton Business School

Lizhu Tao

University of Warwick - Department of Statistics

Yukun Shi

University of Glasgow; University of Leicester

Cheng Yan

Durham Business School

Date Written: July 26, 2019

Abstract

This paper proposes two dimension-reduction and forecasting quantile methods (i.e., the quantile group lasso and the quantile group SCAD models) to predict carbon futures returns and investigate the predictability of a comprehensive group of factors including market fundamental variables and technical variables. In terms of the predictive performance, the two proposed models outperform a series of popular competing models. In terms of robustness, the employed quantile method outperforms the mean shrinkage models, especially in the case of our empirical dataset with a non-normal distribution. Through the predictor selection process, the most powerful predictors of carbon futures returns are selected through the dimension-reduction mechanism of the two employed models, while the possible difference of the selected predictors for different quantiles of carbon returns are carefully considered. Moreover, the impacts of those selected predictors are eventually estimated on the quantiles of carbon returns through a quantile regression. We find that the Brent price is the key factor of carbon returns at different quantile levels. The crude oil closing stock and the natural gas futures in the UK significantly influence the carbon futures returns at lower and higher quantile levels. Our research shows that appropriate predictors for carbon futures returns and their impacts hinge on carbon market conditions.

Keywords: Carbon futures price prediction; Quantile group Lasso; Quantile group SCAD; Variable selection

JEL Classification: C31, C33, Q41, R41

Suggested Citation

Ren, Xiaohang and Duan, Kun and Tao, Lizhu and Shi, Yukun and Yan, Cheng, Carbon Price Forecasting: Which Driven Factors Can Help (July 26, 2019). Available at SSRN: https://ssrn.com/abstract=3427183 or http://dx.doi.org/10.2139/ssrn.3427183

Xiaohang Ren (Contact Author)

University of Southampton ( email )

University Rd.
Southampton SO17 1BJ, Hampshire SO17 1LP
United Kingdom

Kun Duan

University of Southampton - Southampton Business School ( email )

Southampton, SO17 1BJ
United Kingdom

Lizhu Tao

University of Warwick - Department of Statistics ( email )

Coventry CV4 7AL
United Kingdom

Yukun Shi

University of Glasgow ( email )

Adam Smith Business School
Glasgow, Scotland G12 8LE
United Kingdom

University of Leicester ( email )

University Road
Leicester, LE1 7RH
United Kingdom

Cheng Yan

Durham Business School ( email )

Mill Hill Lane
Durham, Durham DH1 3LB
United Kingdom

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