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題名：Intraday Evidence on Relationships among Great Events, Herding Behavior, and Investors' Sentiments
書刊名：交大管理學報
作者：張志向 引用關係／蔡佳靜／黃一祥 引用關係／黃旭輝 引用關係
作者(外文)：Chang, Chih-hsiang／Tsai, Chia-ching／Huang, I-hsiang／Huang, Hsu-huei
出版日期：2012
卷期：32:1
頁次：頁61-106
主題關鍵詞：日內資料；投資人情緒；重大事件；從眾行為；領先落後關係；Intraday data；Investors' sentiments；Great events；Herding behavior；Lead-lag relationship
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  • 被引用次數被引用次數:期刊(4) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:4
  • 共同引用共同引用:0
  • 點閱點閱:54
本研究昌在探討2005－2008期間內三項重大事件發生時投資人交易行為與情緒的日內從眾傾向。相較於早期相關文獻，本研究至少具有下列四點特色：首先，本研究分別採用1分鐘、5分鐘與10分鐘的日內資料來深入地調查投資人的日內從眾現象。其次，本研究探討2005-2008期間內三項重大事件對投資人交易行為與情緒之日內從眾傾向的影響。再者，本研究檢查投資人交易行為、投資人情緒與股票報酬的日內領先落後關係。最後，為了強化研究結果的正確性，我們分別使用絕對與相對的委買（賣）量來做為投資人交易行為的代理變數。三種頻率日內資料與兩種投資人交易行為代理變數的實證結果均指出「投資人情緒」領先「投資人交易行為」；而且當研究模式納入重大事件的虛擬變數時，投資人情緒與投資人交易行為都具有明顯的從眾傾向。另外，重大事件也顯著地影響投資人情緒的條件波動性。
This study investigates the intraday herding tendency of investors' trading behavior and sentiments around the three great events that happened during 2005-2008. In comparison with previous literature, this study contains at least four important aspects. First, this study applies l-minute, 5-minute, and 10-minute intraday data to closely examine the intraday herding of investors. Second, the influence of the three great events that happened during 2005-2008 on the herding tendency of investors' trading behavior and sentiments is explored in this study. Third, we look further into the intraday lead-lag relationships among investors' trading behavior, investors' sentiments, and stock returns. Finally, in order to improve the robustness of empirical findings, both the absolute and relative bid/ask volumes are adopted by this study as proxies of investors' trading behavior. The empirical results of the three-frequency intraday data and those of the two investor trading behavior proxies both show that investors' sentiments lead investors' trading behavior, and both of them exhibit pronounced herding tendency for the models with dummy variables of great events. In addition, the three great events have a significant impact on the conditional volatility of investors' sentiments.
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