印度共同基金绩效基准的数据包络分析方法
A Data Envelopment Analysis Approach to Benchmark the Performance of Mutual Funds in India
摘要：
随着印度经济的数字化增长和金融包容性的增强，越来越多的投资者开始投资印度资本市场。与印度共同基金计划合作的零售和机构投资者数量连续第74个月持续增长。这项研究考虑了139个共同基金计划（98个股票计划），旨在确定散户和机构投资者继续依赖的各种指标和参数，以提出投资建议。我们将这些结果与数据分析模型的结果进行比较，该模型基于最佳风险，成本和回报权衡生成效率边界。我们进一步提出了一个迭代的DEA模型，不仅考虑风险，成本和回报的特点，但也纳入指标，如信息比率持有意义的散户和机构投资者。我们将这些结果与传统的指标和成熟的行业评级机构发布的基金排名进行比较。
英文摘要：
As the Indian economy grows digitally and becomes more financially inclusive, more and more investors have started to invest in the Indian capital markets. The number of retail and institutional folios with Indian mutual fund schemes have continued to rise for the 74th consecutive month. This study considers 139 mutual fund schemes (98 equity schemes) and aims to ascertain the various metrics and parameters, retail and institutional investors continue to rely on to make investment recommendations. We compare these with the results from a data envelopment analysis model that generates an efficiency frontier based on an optimal risk, cost, and return trade-off. We further put forth an iteration of the DEA model, not only considering risk, cost, and return characteristics but also incorporating metrics such as the information ratio which hold significance for retail and institutional investors. We compare these results with traditional metrics and fund rankings published by established industry rating agencies.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
