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A Multi-Objective Portfolio Selection Formulation of Corporate Social Responsibility and Optimization Algorithms

机译:企业社会责任和优化算法的多目标投资组合选择制定

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There is a rapidly growing interest in corporate social responsibility (CSR), especially in the current global financial crisis. We briefly review the development of CSR and point out in China the research is quite frequently immature and heavily qualitative. To facilitate the development, we propose a quantitative way to measure CSR and formulate CSR in a multiple objective portfolio selection model as an extension of traditional Markowitz' portfolio selection model. Based on Chinese stocks by industries, we calculate the stocks' CSR measurements and perform model optimization by computing the efficient portfolios. Comparing with major indexes of Chinese stock markets as benchmarks by t-tests, some efficient portfolios outperform the indexes and therefore can justify our approach. Moreover, our methodology stems from established measurements of CSR and latest enrichments of programming methodology and finance and therefore can be applicable to CSR research worldwide. At the early stage of research by the intersection of programming methodology and finance, more important and inspiring questions are raised than answered. Consequently, as the frontier is being pushed, definitely being counted are more promising results.
机译:对企业社会责任(CSR)的兴趣迅速增长,特别是在目前的全球金融危机中。我们简要介绍了CSR的发展,并指出,中国的研究是非常不成熟和严重的。为了促进发展,我们提出了一种定量的方法来测量CSR并在多目标组合选择模型中制定CSR,作为传统的Markowitz'组合选择模型的扩展。根据工业的中国股票,我们计算股票的CSR测量,并通过计算有效的投资组合来执行模型优化。与T-Tests的基准相比,与中国股票市场的主要指标相比,一些有效的投资组合优于指标,因此可以证明我们的方法。此外,我们的方法源于CSR的既定测量和节目方法和金融的最新丰富,因此可以适用于全球的CSR研究。在通过编程方法和金融的交叉口的研究的早期阶段,提出了比回答更重要和鼓舞人心的问题。因此,随着前沿被推动,肯定被计算出更有前途的结果。

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