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Journal of Banking & Finance · Vol.73,DECEMBER 2016
股票收益可预测性与投资者情绪:基于高频视角
作者:Licheng Sun (Old Dominion University), Mohammad Najand (Old Dominion University), Jiancheng Shen (Regent University)
摘要:我们探讨高频投资者情绪与股市收益之间的预测关系。我们的结果是基于高频投资者情绪的专有数据集,该数据集是根据新闻线、互联网新闻和社交媒体的综合文本分析计算所得。大量证据表明,日内标普500指数回报是可以使用滞后半小时的投资者情绪进行预测的。在其他股票和债券指数ETF中也发现了预测能力。我们发现,这种情绪效应与基于滞后半小时收益的日内动量效应无关。虽然日内动量效应仅仅存在于最后的半小时,但情绪效应至少在交易日的最后两个小时内持续。从投资角度来看,高频投资者情绪在通过市场时机交易策略进行评估时,似乎也具有显著的经济价值。我们发现,有证据表明收益的可预测性最有可能是由噪音交易者的交易活动所驱动的。
关键词:日内,投资者情绪,高频,股票收益可预测性,噪声交易
Stock return predictability and investor sentiment: A high-frequency perspective
Licheng Sun (Old Dominion University), Mohammad Najand (Old Dominion University), Jiancheng Shen (Regent University)
ABSTRACT
We explore the predictive relation between high-frequency investor sentiment and stock market returns. Our results are based on a proprietary dataset of high-frequency investor sentiment, which is computed based on a comprehensive textual analysis of sources from news wires, internet news sources, and social media. We find substantial evidence that intraday S&P 500 index returns are predictable using lagged half-hour investor sentiment. The predictive power is also found in other stock and bond index ETFs. We document that this sentiment effect is independent of the intraday momentum effect, which is based on lagged half-hour returns. While the intraday momentum effect only exists in the last half hour, the sentiment effect persists in at least the last two hours of a trading day. From an investment perspective, high-frequency investor sentiment also appears to have significant economic value when evaluated with market timing trading strategies. We find evidence that the return predictability is most likely driven by the trading activities of noise traders.
Keywords: Intraday, Investor sentiment, High frequency, Stock return predictability, Noise trading
原文链接:
http://www.sciencedirect.com/science/article/pii/S0378426616301595
翻译:贾梦悦
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