An Empirical Test on Analysts' Recommendations: Private Information and Mutual Benefit

傳統探討分析師推薦資訊價值的研究多採用累積超額報酬的方式，近年來研究顯示個別投資人的績效顯著低於機構投資人，因此是否分析師推薦能夠幫助提升個別投資人的福利。本論文的第一個貢獻在檢定是否個別投資人能夠獲取分析師推薦的資訊價值，為區分推薦資訊分別對於個別與機構投資人的價值為何，本研究採用的每種投資人實際的交易利潤作為衡量指標。 研究結果顯示所有投資人都可以透過買入推薦獲取顯著的正報酬，但在賣出推薦上，僅外資與共同基金仍能維持獲取正的報酬。同時發現在推 薦事件期間，專業機構投資人的利潤顯著高於一般散戶的獲利。 進一步，本論文的第二的主題在探討此推薦的資訊價值對於不同投資人的差異，是否肇因於推薦券商所提供的私有資訊，因此進一步將各類投資人分成推薦券商的客戶與非客戶。結果顯示國內機構投資人的利潤在客戶的身上顯著高於非客戶的獲利，顯示推薦券商在對外公佈推薦資訊前的確提供私有資訊給其國內機構客戶，但此現象在賣出推薦並不存在。 第三，本論文進一步分析是否拿到推薦券商所提供私有資訊的客戶也是推薦券商的經紀業務收益的主要貢獻者。在比較推薦券商與非推薦券商在被推薦股票上的相對交易量(金額)中，發現推薦券商的確因為買入推薦股票而增加經紀業務量，但很驚訝的發現貢獻最多交易量的是個別投資人，而非拿到最多好處的機構投資人。 最後，本研究透過迴歸分析探討不同投資人的交易利潤與推薦券商所獲得的經紀業務量的關係。在控制推薦類型、推薦評等與被推薦股票之股票特性後，發現投資人的交易利潤與推薦券商的經紀業務收益成正相關，再次顯示券商推薦與其各項業務收益間的關係。Traditionally, information value of analysts’ recommendations has been well-recognized by cumulative abnormal returns. Recent studies show that individuals are underperformed, and therefore, it is a critical issue on if analysts’ recommendations are helpful to individuals’ welfares. The first contribution of this dissertation to the literature is to examine whether individual investors are capable of capturing the information value. To classify the information value of recommendations for individuals and institutions, respectively, I, thus, use a direct measure to calculate the actual trading profits of types of traders. To our best knowledge, this is the first paper that demonstrates the information value for types of investors. Our results indicate that, all investors get positive and significant profits in brokerages’ buy recommendations, no matter what types of investors are measured. As to sell recommendations, only foreign investors and mutual funds have positive returns. We also find that professional institutions earn more profits than retail investors during the recommendation event periods. Further, the second objective of this dissertation is to test whether the information values are caused by private information from brokerages’ houses, we separate the profits of types of investors into customers and non-customers based. The findings are that only domestic institutional customers of recommending brokerages are more beneficial than those of non-recommending brokerages in buy recommendations, which implies that brokerage houses may reveal private information to their own institutional customers before buy recommendations make public. This does not hold for sell recommendations. Third, we are interested in analyzing whether the private information that recommending brokerages provide to their own customers may, indeed, contribute to brokerages’ commission revenues. By comparing the trading volume of recommending brokerages and non-recommending brokerage for the covered stocks, we find that the volumes of covered stocks issued in the recommending brokerages are increased for buy recommendations. Particularly, we find that the main contribution of trading volume is from individuals. Furthermore, we run regressions to study the relationship between trading profits of types of investors and trading volume of recommending brokerages. After controlling recommendation types, consensus rating of recommendations, and stock characteristics, our results indicate that trading profits of all types of investors are positively related to commission revenues of brokerages. This may justify the importance of brokerage recommendations on their business relationships