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论文编号：	15471
作者编号：	1120211194
上传时间：	2025/6/12 11:28:48
中文题目：	包含ESG投资的多目标投资组合选择模型的建立之论证和优化研究
英文题目：	Research on Justification and Optimization of Establishing Multiple-objective Portfolio Selection for ESG Investment
指导老师：	齐岳
中文关键字：	ESG投资；多目标投资组合选择；多目标优化；投资组合选择模型
英文关键字：	ESG investment; Multiple-objective portfolio selection; Multiple-objective optimization; Portfolio selection model
中文摘要：	在“双碳”目标背景下，党的二十大报告明确提出“加快发展方式绿色转型”和“完善支持绿色发展的财税、金融、投资、价格政策和标准体系”。环境（E）、社会（S）和公司治理（G）作为贯彻绿色可持续发展的重要抓手，已经成为国家政策与企业实践深度融合的核心议题。ESG投资受到投资者和学者越来越多的关注，而在复杂的股票市场中如何选择ESG表现良好的上市公司进行科学合理的投资就显得尤为重要。因此，将ESG因素纳入投资组合选择模型是市场实践需求的直接体现。在此背景下，如何将企业ESG表现的量化结果融入投资组合选择过程，进而为投资者提供资产优化配置的科学方案，已成为中国情境下投资组合理论与实践的核心问题。 国内外学者已围绕ESG投资和投资组合选择进行了学术研究，但传统的投资组合选择模型在均值-方差框架下仅考虑风险和收益两个目标维度，在面对ESG的投资需求时已显现理论局限。本文在前人研究的基础上，将投资组合选择模型扩展为包含ESG投资的多目标投资组合选择模型，为投资者提供一种既考虑风险和回报又兼顾ESG因素的投资思路。然而，在多目标投资组合选择模型的合理性论证和优化求解等方面的研究尚有不足。本文的核心研究内容之一是在期望效用框架下，分别从二次效用函数和独立的多元正态分布的角度，聚焦于对包含ESG投资的多目标投资组合选择模型的合理性的理论论证，证明了期望效用最大化与多目标投资组合选择模型的一致性，丰富了多目标投资组合的基础理论研究。本文的核心研究内容之二是研究包含ESG投资的多目标投资组合选择模型的解析求解与解集性质，并重点分析等式约束下多目标投资组合优化的解析捷径，证明了多目标投资组合选择模型的有效集中非负子集的可能存在性，从理论上加强了多目标优化的解析方法的运用。 本文的研究创新及贡献为： 第一，在期望效用框架下，基于独立的多元正态分布的假设，通过证明期望效用最大化模型和多目标投资组合选择模型的一致性，展开对多目标投资组合选择模型的合理性的理论论证。具体地，首先，本文首次从扩展效用函数的视角，研究了含有投资组合收益和ESG表现的效用函数的泰勒级数展开及其一致收敛性。其次，本文创新地在独立的多元正态分布的假设下，将包含ESG的期望效用表示为含有高阶矩的表达式，并采用泰勒展开和六阶截断技术做近似处理。最后，本文的理论分析表明期望效用是关于期望的增函数和关于方差的减函数，并通过定理证明，得出期望效用最大化模型的最优解是多目标投资组合选择模型的一个有效解，进而阐明包含ESG的期望效用最大化模型和包含ESG投资的多目标投资组合选择模型的一致性，为论证多目标投资组合选择模型的合理性奠定了理论依据。 第二，通过研究等式约束下多目标投资组合选择模型的有效集中非负子集的可能存在性，创新地提供一种多目标投资组合优化的解析捷径，解决了等式约束下确定多目标投资组合的非负权重向量的优化问题。由于有效集的结构很少为人所知，且公共领域的计算软件甚至还未解决三个目标的投资组合优化问题，而研究人员仅解析求解了等式约束下的模型，因此，确定多目标投资组合选择模型的有效集的非负性的解析方法仍然是未知的。本文将解析方法扩展到非负约束下包含ESG投资的多目标投资组合选择模型，在理论上做出创新贡献。具体地，首先，本文证明了多目标投资组合选择模型的有效集的性质，即有效集中正元素和负元素的存在性。其次，本文首次证明了有效集的非负子集的可能存在性，从而可以绕过数学规划，解析并确定等式约束下投资组合中的非负权重向量。最后，本文创新并重点论述了多目标投资组合优化的解析捷径，进一步推广了包含ESG投资的 目标投资组合选择模型，从理论上加强并深化了多目标投资组合优化中解析方法的应用。 本文选取上证50指数成分股作为研究对象，结合中国股票市场的真实数据对模型进行实证分析，检验有效集中非负子集的存在性，并检验所构造的包含ESG投资的多目标投资组合选择模型的样本外表现。通过改变样本选取数量的方法，减少由于研究对象的样本量大小、样本的特殊性等因素所造成的偏差，使得检验结果科学可靠。基于40家样本公司的实证结果表明，包含ESG投资的多目标投资组合选择模型在ESG方面比市值权重下的ESG指数表现更好。本文丰富了ESG在投资组合领域的研究，不仅在多目标投资组合选择模型的论证与优化方面做出了理论创新贡献，也在实践上为投资者提供应对ESG的投资工具，实现从单一财务目标向绿色可持续发展目标的投资模式转换，同时也能反向激励上市公司提升ESG表现，从而进一步稳定股票市场，并形成可持续金融系统的一个正向良性循环。
英文摘要：	Against the backdrop of the "dual carbon" goal, the report of the 20th National Congress of the Communist Party of China clearly proposed "accelerating the green transformation of development patterns" and "improving fiscal, financial, investment, pricing policies, and standard systems supporting green development". Environment (E), Society (S), and Governance (G) have become core issues for the deep integration of national policies and corporate practices in implementing green and sustainable development. ESG investment has attracted more and more attention from investors and scholars. In the complex stock market, selecting listed companies with good ESG performance for scientific and reasonable investment is particularly crucial. Therefore, incorporating ESG factors into portfolio selection models directly reflects market practice demands. In this context, how to integrate the quantitative results of corporate ESG performance into the portfolio selection process, and then provide investors with scientific solutions for asset allocation, has become a core issue of portfolio theory and practice in the Chinese scenario. Scholars at home and abroad have conducted research on ESG investment and portfolio selection. However, traditional portfolio selection models based on the mean-variance framework only consider the two target dimensions of risk and return, which has shown theoretical limitations when addressing ESG investment demand. On the basis of previous research, this thesis extends the portfolio selection model to a multiple-objective portfolio selection model including ESG investment, providing investors with an investment idea that balances risk, return, and ESG considerations. However, there are still research limitations in the multiple-objective portfolio justification and optimization area. The first core research of this thesis is to focus on the theoretical justification of multiple-objective portfolio selection models including ESG investment under an expected utility framework, employing quadratic utility functions and independent multivariate normal distributions. It proves the consistency between expected utility maximization and multiple-objective portfolio selection models. It enriches the fundamental theoretical research and contributions of multiple-objective portfolios. The second core research involves investigating analytical solutions and solution set properties of multiple-objective portfolio selection models including ESG investment, and focuses on analytical shortcuts of multiple-objective portfolio optimization under the equality constraint. It proves the possible existence of non-negative subsets in the efficient set of multiple-objective portfolio selection models. It theoretically strengthens the application of analytical methods in multiple-objective optimization. The research innovations and contributions of this thesis are as follows: 1. Under the expected utility framework and assuming independent multivariate normal distributions, the theoretical justification of the multiple-objective portfolio selection model is launched by proving the consistency between expected utility maximization and multiple-objective portfolio selection. Specifically, first, this thesis investigates the Taylor series expansion and its uniform convergence of utility functions containing portfolio returns and ESG performance from an extended utility function perspective for the first time. Second, under the assumption of independent multivariate normal distributions, the expected utility with ESG is expressed as an expression containing higher-order moments and approximated by the sixth-order truncated Taylor expansion technique. Finally, the theoretical analysis results indicate that expected utility is an increasing function of expectation and a decreasing function of variance. This thesis proves that the optimal solution of the expected utility maximization model is an efficient solution of the multiple-objective portfolio selection model. It clarifies the consistency between the expected utility maximization model and the multiple-objective portfolio selection model. It provides a fundamental theoretical basis for justifying the multiple-objective portfolio selection model. 2. By investigating the possible existence of non-negative subsets in the efficient set of the multiple-objective portfolio selection model under equality constraints, this thesis innovatively provides analytical shortcuts to multiple-objective portfolio optimization, which solves optimization problems for non-negative weight vectors. Since the efficient set's structure is barely known and public-domain software for even three objectives is absent, and researchers analytically resolve equality-constraint-only models, the analytical method to determine the non-negativeness of the efficient set of the multiple-objective portfolio selection model is still unknown. This thesis extends the analytical method to a multiple-objective portfolio selection model including ESG investment under non-negative constraints and makes innovative contributions in theory. Specifically, first, it proves the efficient set's properties of the multiple-objective portfolio selection model, namely the existence of positive and negative elements in the efficient set. Second, it proves the possible existence of nonnegative subsets of efficient sets for the first time, which bypasses mathematical programming, analytically resolves, and pinpoints some nonnegative weight vectors in portfolios under equality constraints. Finally, it innovatively focuses on analytical shortcuts to multiple-objective portfolio optimization and further generalizes the k-objective portfolio selection model including ESG investment, which theoretically strengthens the application of analytical methods in multiple-objective portfolio optimization. This thesis selects the Shanghai Stock Exchange 50 Index as the research object, combines the real Chinese market data, conducts empirical analysis, empirically verifies the existence of the non-negative subsets in the efficient set, and tests the effectiveness of multiple-objective portfolio selection models including ESG investment. By changing the number of sample selections, the bias caused by factors such as the sample size and specificity of the research object can be reduced, making the test results scientifically reliable. Empirical results based on 40 sample companies show that the multiple-objective portfolio selection model with ESG investment performs better than the ESG index under market capitalization weight in terms of ESG. This thesis enriches the research on ESG in portfolio management, not only makes theoretical innovation contributions to the justification and optimization of multiple-objective portfolio selection models but also provides ESG investment tools. It realizes the investment mode's transformation from a single financial goal to a sustainable development goal. At the same time, it can also reverse incentives for listed companies to improve ESG performance, thus further stabilizing the stock market and forming a positive virtuous circle of the sustainable financial system.
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