Advances in International Finance
Advances in International Finance. 2024; 6: (1) ; 10.12208/j.aif.20240004 .
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暨南大学 广东广州
*通讯作者: 王峣,单位:暨南大学 广东广州;
本研究通过分析中国股市投资者情绪波动,构建了一个包含宏观经济指标和情感分析的综合情绪指数,并利用LSTM和BiLSTM等机器学习模型预测股票收益率。结果显示,该模型在市场波动时能快速反映情绪变化,为投资者提供准确预测,增强了市场情绪与股票收益关系的理解和投资决策的科学性。
This study analyzes the fluctuations in investor sentiment in the Chinese stock market and constructs a comprehensive investor sentiment index that includes macroeconomic indicators and sentiment analysis. Machine learning models such as LSTM and BiLSTM are utilized to predict stock returns. The results indicate that the model can quickly reflect sentiment changes during market volatility, providing accurate forecasts for investors and enhancing the understanding of the relationship between market sentiment and stock returns, as well as the scientific nature of investment decisions.
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