当代经济科学2025，Vol.47Issue(4)：128-142,15.DOI:10.20069/j.cnki.DJKX.202504009
中国碳市场投资组合优化策略
Portfolio Optimization Strategies in China's Carbon Market:A Study Based on the Possibility Mean-Semi-Absolute Deviation Model
摘要
Abstract
Current research on carbon markets primarily focuses on carbon emission reduction effects and economic impact assessments,with relatively limited research on carbon market investment.Carbon emissions trading is an important tool for addressing climate change and promoting low-carbon transformation.Investment in the carbon market can promote optimal resource allocation,balance risk and return,and improve investment efficiency.Therefore,research on portfolio optimization in the carbon market is not only a means of risk management,but also an important approach to promote carbon market maturity and achieve sustainable investment goals. This paper focuses on portfolio optimization in China's carbon market.First,based on the carbon price data from seven carbon emissions trading pilot regions in China from 2017 to 2021,a possibility mean-semi-absolute deviation portfolio optimization model is constructed considering realistic constraints.The model introduces trapezoidal fuzzy numbers to address asset uncertainty,measuring expected returns by possibility mean and risk by possibility semi-absolute deviation.Second,an improved artificial bee colony algorithm(IABC)is designed to solve the constructed model and enhance solution efficiency.Finally,the empirical study conducts both in-sample analysis and out-of-sample testing.The in-sample analysis explores optimal carbon asset allocation strategies for investors under different expected returns and risk preferences,while out-of-sample testing employs a rolling window method to compare the performance of the proposed model with the classical mean-variance model in terms of Sharpe ratio,downside risk,Sortino ratio,and other metrics,verifying the effectiveness and robustness of the model.The results show significant differences in returns,volatility,skewness,and other factors among China's seven carbon emissions trading pilot markets.As expected returns increase,investment risk rises synchronously,and the allocation proportion to high volatility carbon market increases.When risk aversion level rises,funds flow more toward carbon markets with stable returns.Investors should dynamically adjust their asset allocation structure according to risk appetite and expected returns.Out-of-sample tests demonstrate that the model and algorithm have significant advantages in reducing portfolio downside risk and enhancing investment robustness. Compared with previous literature,this paper contributes in the following three aspects:First,through the portfolio optimization model,investors can effectively allocate capital and choose appropriate carbon emissions exchanges for investment.This optimized investment approach can guide more capital into the carbon trading market,supporting financing needs of low-carbon and green projects and providing stronger capital support for low-carbon economic development.Second,carbon markets have different risk and return characteristics due to policy,market fluctuations,and other factors.Through portfolio optimization,investments can be diversified across different carbon emission exchanges to effectively control overall risk.Finally,research on carbon market portfolio optimization can promote financial innovation in the carbon market and encourage the introduction of more carbon financial products,such as carbon index funds,carbon futures and carbon bonds,to meet investors'diverse needs. This study provides theoretical support for optimal portfolio research in the carbon market,offers decision-making reference for investors participating in the carbon market,and contributes to the healthy development of China's carbon market.关键词
碳市场/碳排放权交易/投资组合/人工蜂群算法/可能性均值—半绝对偏差模型Key words
carbon market/carbon emissions trading/investment portfolios/artificial bee colony algorithm/possibility mean-semi-absolute deviation model引用本文复制引用
董馨月,吕亚男,张金良..中国碳市场投资组合优化策略[J].当代经济科学,2025,47(4):128-142,15.基金项目
国家自然科学基金资助项目"发电企业碳减排的市场型政策工具组合优化研究"(71774054) （71774054）
中央高校基本科研业务费专项资金资助项目"多种市场型碳减排政策下的发电企业交易策略"(2023FR001) （2023FR001）
北京市社会科学基金项目"京津冀地区电力能源、经济、环境绿色协调发展机制与路径研究"(22JCC111). （22JCC111）
