论文标题
使用LSTM模型对Nifty主题部门股票进行投资组合优化
Portfolio Optimization on NIFTY Thematic Sector Stocks Using an LSTM Model
论文作者
论文摘要
投资组合优化一直是定量和统计财务研究人员和财务分析师的广泛而浓厚的兴趣领域。设计股票投资组合以达到回报和风险的优化值是一项具有挑战性的任务。本文提出了一种针对印度NSE的五个主题领域设计最佳风险和特征投资组合的算法方法。股票的价格从2016年1月1日至2020年12月31日从网络中提取。每个行业的最佳风险和特征组合都是基于该行业的十个关键股票而设计的。 LSTM型号旨在预测未来的股票价格。投资组合成立七个月后，于2021年8月3日，将投资组合的实际收益与LSTM预测的收益进行了比较。预测和实际收益表明LSTM模型的高级精度。
Portfolio optimization has been a broad and intense area of interest for quantitative and statistical finance researchers and financial analysts. It is a challenging task to design a portfolio of stocks to arrive at the optimized values of the return and risk. This paper presents an algorithmic approach for designing optimum risk and eigen portfolios for five thematic sectors of the NSE of India. The prices of the stocks are extracted from the web from Jan 1, 2016, to Dec 31, 2020. Optimum risk and eigen portfolios for each sector are designed based on ten critical stocks from the sector. An LSTM model is designed for predicting future stock prices. Seven months after the portfolios were formed, on Aug 3, 2021, the actual returns of the portfolios are compared with the LSTM-predicted returns. The predicted and the actual returns indicate a very high-level accuracy of the LSTM model.
