论文标题
使用优化的LSTM型号的强大投资组合设计和股票价格预测
Robust Portfolio Design and Stock Price Prediction Using an Optimized LSTM Model
论文作者
论文摘要
准确预测股票的未来价格是一项艰巨的任务。更具挑战性的是设计优化的投资组合，其权重分配给了股票，以优化其回报和风险。本文为印度四个关键的经济部门建立两种类型的投资组合，最佳风险和特征。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。部门投资组合是根据其十个最重要的股票建立的。 LSTM型号还旨在预测未来的股票价格。投资组合建设后六个月，即2021年7月1日，计算实际收益和LSTM预测的收益。对预测和实际收益的比较表明LSTM模型的高精度水平。
Accurate prediction of future prices of stocks is a difficult task to perform. Even more challenging is to design an optimized portfolio with weights allocated to the stocks in a way that optimizes its return and the risk. This paper presents a systematic approach towards building two types of portfolios, optimum risk, and eigen, for four critical economic sectors of India. The prices of the stocks are extracted from the web from Jan 1, 2016, to Dec 31, 2020. Sector-wise portfolios are built based on their ten most significant stocks. An LSTM model is also designed for predicting future stock prices. Six months after the construction of the portfolios, i.e., on Jul 1, 2021, the actual returns and the LSTM-predicted returns for the portfolios are computed. A comparison of the predicted and the actual returns indicate a high accuracy level of the LSTM model.
