摘要
“双碳”目标下投资者对碳风险的感知正在不断提升。为应对碳风险管理的挑战,探索更为丰富的绿色投资组合方法论,设计了对冲碳风险的绿色投资组合策略。该策略以多元化投资为主体思路,除了将资金投资于基准投资组合外,还将部分资金配置于碳风险的对冲工具——绿色资产中,致力于降低投资组合在碳风险较高时可能面临的损失。具体而言,策略以碳风险指标高低作为择时依据,通过1/N与MV模型两种方法配置基准投资组合与绿色资产的投资权重。在样本外的实证分析中,分别针对被动投资者与主动投资者检验了包含单一或多种绿色资产的对冲投资组合策略的投资绩效。结果表明,绿色债券是实现碳风险对冲的有效金融工具;相较于绿色股票,包含绿色债券的投资策略均展现出更佳的风险与收益表现;在本文投资策略中,基于MV模型配置权重的碳风险对冲投资策略效果最佳,该策略在碳风险较高时将多数资金配置于对冲碳风险的绿色债券中,往往能将基准投资组合的损失“转亏为盈”,因此在长期获得了良好的投资绩效。
Under the“Deuble Carbon”target,investors’perceptions of carbon risk are increasing.In order to cope with the challenge of carbon risk management and explore more abundant green portfolio strategies,green portfolio strategies are designed to hedge carbon risks.Based on diversified investment idea,the strategies not only invest in benchmark portfolio,but also invest in green assets(carbon risk hedging instruments)to mitigate potential losses that may occur when carbon risk is high.Specifically,the strategies take carbon risk indicator as timing basis,and apply both the 1/N and MV model to allocate weights between the benchmark portfolio and green assets.In out-of-sample empirical analysis,the investment performance of hedging investment strategies is evaluated containing either single or multiple green assets for both passive and active investors.The results indicate that,green bonds are effective financial instruments for hedging carbon risk.Compared to green equities,investment strategies that include green bonds consistently demonstrate superior investment performance.Among the proposed hedging investment strategies,the MV model-based strategies prove most effective.They allocate majority of funds to green bonds when carbon risk is high,which often turns potential losses into gains,resulting in better long-term investment performance.
作者
乔东
徐凤敏
卫丽君
李本初
QIAO Dong;XU Fengmin;WEI Lijun;LI Benchu(School of Economics and Finance,Xi’an Jiaotong University,Xi’an 710061,China)
出处
《统计与信息论坛》
CSSCI
北大核心
2024年第12期56-70,共15页
Journal of Statistics and Information
基金
国家自然科学基金面上项目“几类稀疏二次约束二次规划问题的理论、算法与绿色金融应用研究”(12471297)。