基于DEA模型的股票型基金绩效评价研究

发布时间：2018-05-04 20:18

本文选题：股票型基金 + DEA模型　；参考：《上海师范大学》2013年硕士论文

【摘要】：本文将研究的对象放在开放式股票型基金的效率研究上，根据企业能力理论观点（企业的目标即在于通过其所拥有的特殊能力资源来赢得市场竞争中的优势地位，从而获取超额利润或经济租金的最大化），认为影响基金效绩的因素主要是基金的运营效率即运行有效,它反映着组织效率和服务效率，通过加入计量经济模型，对基金绩效进行量化分析。本文主要使用DEA模型以及超效率DEA模型对基金绩效进行评价，通过将能反映基金内部基金运行效率的指标作为输入产出指标，同时对其进行了降维处理。然后再运用DEA模型对降维前后的数据进行评估，得出绩效评价结果，通过比较分析得出结论。接着将数据带入超效率DEA模型进行评估。分析基金的绩效，并对基金绩效影响因素进行分析。本文从分析基金绩效评价方法、基金绩效评价体系和基金运作情况入手，借鉴了相关的理论和研究成果，运用DEA和超效率DEA方法评价了基金的绩效，通过研究和实证得到以下主要结论: 1、本文首先运用了DEA方法对基金绩效进行评价。再根据输入指标和产出指标选取不宜过多的原则，对六个指标进行了降维处理，得到三个指标，将其中两个作为输入指标一个作为产出指标，再使用模型对其绩效进行评估。最终得出结论，虽然经过降维处理过后的有效单元个数有所减少，但也因为主成分主法的局限性，导致一些决策单元效率值的大幅变化。从而，本文认为在指标个数不够大，指标所包括的信息量不够多的情况下，不宜采用主成分分析方法对指标进行降维处理。 2、运用超效率DEA对样本进行了分析，分别得出了它们的效率值，并能够很好的对其进行排名。超效率DEA模型是在DEA模型基础上通过删除估计的决策单元本身的约束条件所得到的，故其得出的效率值可以大于1，因而能够对决策单元进行排名，因而本文认为，在指标个数不够大的情况下，我们不需要采用主成分分析对数据进行预先处理，，而直接通过超效率DEA模型我们就能对样本进行很好的评估。
[Abstract]:In this paper, the research object is put on the efficiency research of open-end equity fund. According to the theory of enterprise capability (the goal of enterprise is to win the advantage position in the market competition through the special ability resources of the enterprise, the goal of the enterprise is to win the advantage position in the market competition through the special ability resource of the enterprise. In order to obtain the maximum of excess profit or economic rent, it is considered that the main factor affecting the fund performance is that the fund's operational efficiency is effective, which reflects the organizational efficiency and service efficiency, and by adding the econometric model, Quantitative analysis of fund performance. This paper mainly uses the DEA model and the super-efficiency DEA model to evaluate the performance of the fund. By taking the index which can reflect the efficiency of the fund's internal fund operation as the input and output index, the paper also deals with the dimensionality reduction. Then the DEA model is used to evaluate the data before and after dimensionality reduction, and the results of performance evaluation are obtained. Then the data is brought into the super-efficient DEA model for evaluation. This paper analyzes the performance of the fund, and analyzes the influencing factors of the performance of the fund. This paper starts with the analysis of fund performance evaluation method, fund performance evaluation system and fund operation, draws lessons from relevant theories and research results, and evaluates the fund performance by using DEA and super efficient DEA methods. The main conclusions are as follows: 1. Firstly, this paper uses DEA method to evaluate fund performance. Then according to the principle that the input index and output index should not be too much, the dimensionality reduction treatment of the six indexes is carried out, and three indexes are obtained, two of which are taken as input index and one as output index, and then the performance is evaluated by using the model. Finally, it is concluded that although the number of effective units after dimensionality reduction has been reduced, the efficiency of some decision making units has been greatly changed due to the limitation of principal component principal method. Therefore, this paper holds that the principal component analysis method should not be used to reduce the dimension of the index when the number of indicators is not large enough and the amount of information included in the index is not enough. 2. The super-efficiency DEA is used to analyze the samples, and their efficiency values are obtained, and they can be ranked well. The super-efficiency DEA model is obtained by deleting the constraints of the estimated decision unit itself on the basis of the DEA model, so its efficiency value can be greater than 1, so it can rank the decision making unit. When the number of indicators is not large, we do not need to use principal component analysis to pre-process the data, but directly through the super-efficient DEA model we can do a good evaluation of the sample.
【学位授予单位】：上海师范大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F224;F832.51

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