International Review of Financial Analysis ( IF 7.5 ) Pub Date : 2021-08-03 , DOI: 10.1016/j.irfa.2021.101858
Hao Fang, Chien-Ping Chung, Yang-Cheng Lu, Yen-Hsien Lee, Wen-Hao Wang
This study uses fintech approaches, including web crawler technology with distributed architecture to select internet news messages largely and efficiently and a dictionary-based linguistic text mining to create sentiment variables, to explore the respective impacts of investors' optimism and pessimism on stock returns. The construction of sentiment variables in network- and dictionary-based messages is more precise and variable than that in traditional-based messages. Our results show that firms with investors' optimistic sentiments have significantly higher stock returns in the current month, whereas those with pessimistic sentiments have significantly opposite effects. The effect of both investors' optimism and pessimism on stock returns subsequently reverses. Then, the negative impacts of investors' largely pessimistic sentiments on stock returns are larger than the positive impacts of their largely optimistic sentiments within a quarter. Next, investors' optimistic sentiments significantly raise stock return volatility by approximately a quarter, but their pessimistic sentiments have the opposite effects. Furthermore, investors' high optimism more significantly and persistently raises stock return volatility than their general optimism, but the negative effects of their high pessimism on volatility become smaller and the persistence is shorter than general pessimism. In addition to the advantage of our methodology in creating sentiment variables, the simultaneous consideration of investors' optimism and pessimism to analyze the effects on the returns and the volatility of individual stocks in this study is more complete than previous related studies.
中文翻译:
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使用金融科技方法研究投资者情绪对股票收益的影响
本研究使用金融科技方法,包括具有分布式架构的网络爬虫技术来大量有效地选择互联网新闻消息,以及基于字典的语言文本挖掘来创建情绪变量,以探讨投资者乐观和悲观对股票回报的各自影响。基于网络和字典的消息中情感变量的构建比基于传统的消息更精确和可变。我们的研究结果表明,投资者情绪乐观的公司当月股票回报显着提高,而悲观情绪的公司则具有显着相反的效果。投资者的乐观和悲观对股票回报的影响随后发生逆转。那么,投资者的负面影响 在一个季度内,对股票回报的基本悲观情绪大于其基本乐观情绪的积极影响。其次,投资者的乐观情绪显着将股票回报波动率提高了大约四分之一,但他们的悲观情绪会产生相反的效果。此外,投资者的高乐观情绪比普遍乐观情绪更显着、持续地提高股票收益波动率,但高悲观情绪对波动率的负面影响比普遍悲观情绪更小,持续时间更短。除了我们的方法在创建情绪变量方面的优势之外,同时考虑投资者的