论文标题
Nifty 50股票的分层风险奇偶校验组合和特征投资组合的比较研究
A Comparative Study of Hierarchical Risk Parity Portfolio and Eigen Portfolio on the NIFTY 50 Stocks
论文作者
论文摘要
投资组合优化一直是一个研究领域，吸引了研究人员和财务分析师的很多关注。设计最佳投资组合是一项复杂的任务，因为它不仅涉及对未来股票收益和风险的准确预测，而且还需要优化它们。本文使用两种方法（分层风险平等算法和印度股票市场的七个领域的特征算法）提出了一种系统的投资组合优化方法。该投资组合是根据从2016年1月1日到2020年12月31日的两种历史股票价格的方法来构建的。投资组合的性能是根据2021年1月1日至2021年11月1日的测试数据进行评估的。投资组合的进行了回测的结果。对HRP Portfolio的表现表明，对其EIGEN的培训和测试的培训都优越。
Portfolio optimization has been an area of research that has attracted a lot of attention from researchers and financial analysts. Designing an optimum portfolio is a complex task since it not only involves accurate forecasting of future stock returns and risks but also needs to optimize them. This paper presents a systematic approach to portfolio optimization using two approaches, the hierarchical risk parity algorithm and the Eigen portfolio on seven sectors of the Indian stock market. The portfolios are built following the two approaches to historical stock prices from Jan 1, 2016, to Dec 31, 2020. The portfolio performances are evaluated on the test data from Jan 1, 2021, to Nov 1, 2021. The backtesting results of the portfolios indicate that the performance of the HRP portfolio is superior to that of its Eigen counterpart on both training and test data for the majority of the sectors studied.
