投资者情感指标与股票收益率的因果关系研究——以苹果公司股票为例
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摘要
随着行为金融学的不断发展,投资者情感指标研究日益受到股票研究者的关注。本文以成熟股市下的苹果公司股票为例,运用文本挖掘技术,在考虑情感相关度和影响度的基础上,引入情感指标B_RF,从网络媒体角度出发,探究网络情感与股票收益率之间的关系。运用granger因果关系检验的结果表明:成熟市场下网络媒体情感下的贬义情感指标和褒义情感指标分别在不同滞后阶数下表现出与股票收益率之间存在显著的granger因果关系,丰富了网络情感的指标测量体系。
With the continuous development of Behavioral Finance, the research of investor sentiment index has been paid more attention by stock researchers.Taking the Apple stock as an example, this paper uses text mining technology to explore the relationship between network sentiment and stock return rate. Based on sentiment correlation score and influence degree, this paper introduced B_RF sentiment index to measure this relationship.The results of Granger causality test in mature markets shows, there is a significant granger causality of the negative sentiment index and the positive sentiment index under different lag orders, which enriches the index measurement system of network sentiment.
With the continuous development of Behavioral Finance, the research of investor sentiment index has been paid more attention by stock researchers.Taking the Apple stock as an example, this paper uses text mining technology to explore the relationship between network sentiment and stock return rate. Based on sentiment correlation score and influence degree, this paper introduced B_RF sentiment index to measure this relationship.The results of Granger causality test in mature markets shows, there is a significant granger causality of the negative sentiment index and the positive sentiment index under different lag orders, which enriches the index measurement system of network sentiment.
引文
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[2]Duan J,Zeng J.Mining opinion and sentiment for stock return prediction based on Web-forum messages[C].2013 10th International Conference on Fuzzy Systems and Knowledge Discovery(FSKD),2013(4).
[3]Chen H, Chong T T L, She Y. A principal component approach to measuring investor sentiment in China[J]. Quantitative Finance, 2014(4).
[4]Ding C G, Wang H, Lee M, et al. How Does the Change in Investor Sentiment over Time Affect Stock Returns?[J]. Emerging Markets Finance&Trade, 2014(5).
[5]杜锐、朱艳辉、田海龙等.基于平滑SO-PMI算法的微博情感词典构建方法研究[J].湖南工业大学学报, 2015(5).
[6]Joshi K,Bharathi H N,Rao J.Stock Trend Prediction Using News Sentiment Analysis[J].International Journal of Computer Science&Information Technology, 2016(3).
[7]许启发、伯仲璞、蒋翠侠.基于分位数Granger因果的网络情绪与股市收益关系研究[J].管理科学,2017(3).
[8]陈影,王立夏,周智敏.投资者情绪对股票价格指数影响研究——以百度指数与微博指数为指标[J].价格理论与实践,2017(9).
[9]Chen, Y.-J., Y.-M. Chen, and C.L. Lu, Enhancement of stock market forecasting using an improved fundamental analysis-based approach. Soft Computing, 2017(13)
[10]孟志青、郑国杰、赵韵雯.网络投资者情绪与股票市场价格关系研究--基于文本挖掘技术分析[J].价格理论与实践, 2018(8).