论文标题
使用LSTM型号的优化投资组合设计的精确股票价格预测
Precise Stock Price Prediction for Optimized Portfolio Design Using an 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股票组合，并确定适当的分配权重，以实现回报和风险的优化值。我们根据印度经济的七个部门提出了优化的投资组合。股票的过去价格从2016年1月1日至2020年12月31日从网络中提取。最佳投资组合是在选定的七个领域设计的。 LSTM回归模型还旨在预测未来的股票价格。投资组合建设后的五个月，即2021年6月1日，计算每个投资组合的实际收益和风险。预测和实际回报表明LSTM模型的准确性很高。
Accurate prediction of future prices of stocks is a difficult task to perform. Even more challenging is to design an optimized portfolio of stocks with the identification of proper weights of allocation to achieve the optimized values of return and risk. We present optimized portfolios based on the seven sectors of the Indian economy. The past prices of the stocks are extracted from the web from January 1, 2016, to December 31, 2020. Optimum portfolios are designed on the selected seven sectors. An LSTM regression model is also designed for predicting future stock prices. Five months after the construction of the portfolios, i.e., on June 1, 2021, the actual and predicted returns and risks of each portfolio are computed. The predicted and the actual returns indicate the very high accuracy of the LSTM model.
