首页> 外文会议>International Conference on Computing Communication Control and Automation >Portfolio Generation for Indian Stock Markets using Unsupervised Machine Learning
【24h】

Portfolio Generation for Indian Stock Markets using Unsupervised Machine Learning

机译:使用无监督机器学习的印度股票市场投资组合

获取原文

摘要

Portfolio Management is a concept of selecting the proportions of various assets that is to be held in a portfolio to have a good return without a significant risk exposure. Portfolio optimization is one important building block in financial management and investment banking. One possible strategy for minimisation of risk is by enlarging or varying its field of operation for the portfolio. Constructing an optimal portfolio by judging and selecting the best possible combinations of different portfolio is a computationally challenging problem since it comes up with an exponential complexity. Here, we have proposed a simple k-means based clustering strategy for an optimal portfolio. BSE100 stocks are represented by their fundamental financial ratios. Clustering is performed, and a prototype stock is selected from each of the clusters. An equal investment strategy demonstrates superior return as compared to the indices as well as top mutual funds. The classification is done by considering a host of investment parameters. We compare the rate of return of these stocks to the benchmark of Indian Stock Exchange.
机译:投资组合管理是选择要在投资组合中举行的各种资产比例的概念,以在没有重大风险暴露的情况下具有良好的回报。投资组合优化是财务管理和投资银行中的一个重要构建块。最小化风险的一个可能的策略是通过扩大或改变其对投资组合的操作领域。通过判断和选择不同投资组合的最佳组合构建最佳组合是一个计算上具有挑战性的问题,因为它提出了指数复杂性。在这里,我们提出了一种基于K-Means的基于群组的聚类策略,可获得最佳组合。 BSE100股票由其基本财务比率表示。进行聚类,并且从每个簇中选择原型库存。与指数相比,平等的投资策略展示了卓越的回报,以及最高的共同基金。分类是通过考虑一系列投资参数来完成的。我们将这些股票的回报率与印度证券交易所的基准进行比较。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号