目前從眾行為的研究多半著重在基金經理人的投資決策上,而較少關於類股間從眾行為的研究,加上近期以高科技類股為主的Nasdaq指數,其急漲又急跌的走勢,引發本研究對高科技類股的研究動機,故本研究的目的是探討高科技類股的從眾行為。 由於Christie and Huang (1995)利用個股報酬與該產業投資組合報酬之橫斷面標準差,作為判斷該產業的從眾程度,不過此模型的假說認為若有從眾行為的現象,則產業中的個股應為齊漲或齊跌,因此個股報酬和產業報酬的差距將會縮小,但本研究認為此假說缺乏嚴謹的理論基礎,故根據Lakonishok et al. (1992)的模型,重新建構一個用來衡量產業間從眾行為的模型,另外再進一步研究類股從眾程度與市場報酬率、市場成交量之間的關聯性。實證結果如下: 一、Christie and Huang (1995)的假說的確有令人質疑之處。 二、高科技類股的從眾程度大於傳統類股。 三、在探討從眾指標與大盤報酬率的關係方面,以原始報酬為衡量的從眾指標之結果發現,各類股皆有顯著的正相關,至於以超額報酬為衡量之結果則發現高科技類股有較顯著的正相關,而傳統類股大多是較不顯著的正相關,另外兩種從眾指標都顯示當大盤出現極端報酬時,從眾行為有不對稱的情形。 四、在探討從眾指標與大盤成交量的關係方面,不論是以原始報酬或超額報酬為衡量的從眾指標,皆顯示高科技類股的從眾程度和成交量有顯著的正相關,而傳統類股方面,以原始報酬為衡量的從眾指標也和成交量有顯著的正相關,但以超額報酬為衡量的從眾指標和成交量的關係呈現顯著正相關的,只有少數產業,如食品業、塑化業,和公共設施業。 五、在探討從眾指標與大盤報酬率、大盤成交量的關係方面,以原始報酬為衡量的從眾指標之結果發現有顯著的正相關,但以超額報酬為衡量的從眾指標之結果則較為凌亂,且不論高科技類股或傳統類股皆有零星的負相關,不過都不顯著。 本研究以美國股市為主,至於台灣與大陸股市則另闢一小節討論。其中台灣股市則有類似的結果,不過從眾程度較美國股市為大;而大陸股市的研究動機是由於在2001年2月19日中共證監會開放大陸境內居民可投資B股,因此本研究以當天為事件日,探討事件前後A、B股從眾程度之差異。結果發現事件日前A股的從眾程度大於B股,而事件日後B股的從眾程度則大於A股。
This paper examine the evidences of herd behavior within high-tech stocks, regarding in comparison with traditional stocks in the US and Taiwan market over the period from 1996 to 2000. We find more significant evidence of herding on High-tech stocks than traditional stocks. Several papers use a statistical measure of herding due to Lakonishok, Shleifer, and Vishny (1992). It defines and measures herding as the average tendency of a group of money managers to buy (sell) particular stocks at the same time, relative to what could be expected if money managers traded independently. While it is called a herding measure, it really assesses the correlation in trading patterns for a particular group of traders and their tendency to buy and sell the same set of stocks. In a recent empirical study, Christie and Huang (1995) examine the investment behavior of market participants in the US equity market. By utilizing the cross-sectional standard deviation of returns (CSSD) as a measure of the average proximity of individual asset returns to the realized market average, they develop a test of herd behavior. According to Lakonishok et al. (1992) and Christie and Huang (1995), we develop a measure to identify the presence of herd behavior in an industry from equity performances. Differences between our herding measure and equity return dispersion are clarified. Our empirical results demonstrate more significant evidences of herd behavior and greater return dispersion in high-tech industries. In particular, we examine the herd behavior under various market conditions. Extreme market performances also lead to aggressive herd behavior, while our asymmetric results suggest more evidences of herd behavior in the extreme up market than the down market. We also find positive relationship between herd behavior and trading volume.