基于优化LSTM模型的稳健投资组合设计与股票价格预测

Jaydip Sen, Saikat Mondal, G.Veerendra Nath
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引用次数: 9

摘要

准确预测股票的未来价格是一项艰巨的任务。更有挑战性的是设计一个优化的投资组合,将权重分配给股票,以优化其回报和风险。本文提出了一种系统的方法,以建立两种类型的投资组合,最优风险和特征,为印度的四个关键经济部门。这些股票的价格是从2016年1月1日至2020年12月31日的网络价格中提取出来的。行业明智的投资组合是基于他们最重要的10只股票。本文还设计了LSTM模型来预测未来的股票价格。在投资组合构建六个月后,即2021年7月1日,计算投资组合的实际收益和lstm预测收益。与实际收益的比较表明,LSTM模型具有较高的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Portfolio Design and Stock Price Prediction Using an Optimized LSTM Model
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 l, 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.
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