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      Want to Make Money with Stocks?Never Listen to Analysts

      2018-10-31 05:30:30By
      英語世界 2018年10期
      關鍵詞:認知科學代表性群組

      By

      Investors probably expect that following the suggestions of stock analysts1analyst分析師。would make them better off2better off經(jīng)濟狀況更好。than doing the exact opposite.Nevertheless,recent research by Nicola Gennaioli and colleagues shows that the best way to gain excess returns3excess return超額回報。would be to invest in the shares least favored by analysts.They compute that, during the last 35 years, investing in the 10 percent of U.S.stocks analysts were most optimistic about would have yielded4yield產(chǎn)生收益。on average 3 percent a year.By contrast, investing in the 10 percent of stocks analysts were most pessimistic about would have yielded a staggering 15 percent a year.

      投資者可能以為,聽從股票分析師的建議會比不聽賺更多的錢。但是,妮古拉·真納約利及其同事近期的研究顯示,要想獲得超額回報,最好的辦法就是投資最不被分析師看好的股票。他們測算發(fā)現(xiàn):過去35年,投資于分析師最看好的10%的美國股票,獲得平均3%的年收益率;對比而言,投資于分析師最看衰的10%的股票,竟獲得驚人的15%的年收益率。

      [2]Gennaioli and colleagues shed light on5shed light on闡明,解釋。this puzzle with the help of cognitive sciences6cognitive science認知科學。and Kahneman and Tversky’s concept of representativeness7representativeness代表性理論,指代表性偏差認知傾向。.Deci-sion makers, according to this view,overweight the representative features of a group or a phenomenon.These are defined as the features that occur more frequently in that group than in a baseline reference group8baseline reference group基準參照群組。.

      [2]真納約利及其同事用認知科學和卡尼曼與特沃斯基的“代表性”理論來解釋這一謎題。該理論認為,決策者會過于重視某群組或某現(xiàn)象的“代表性特征”?!按硇蕴卣鳌敝傅氖窃撊航M比基準參照群組更為常見的那些特征。

      [3]After observing strong earnings growth, the explanation goes,analysts think that the firm may be the next Google.“Googles” are, in fact,more frequent among firms experiencing strong growth, which makes them representative.The problem is that“Googles” are very rare in absolute terms.As a result, expectations become too optimistic, and future performance disappoints.A model of stock prices in which investor beliefs follow this logic can account both qualitatively and quantitatively for9account for說明……原因,對……做出解釋。qualitatively and quantitatively定性地和定量地。the beliefs of analysts and the dynamics of stock returns.

      [3]分析師們觀察到某一公司收益增長強勁后,就會開始解讀,認為該公司或許將成為下一個谷歌。確實,增長強勁的公司中更容易出現(xiàn)“谷歌類公司”,這使它們更具代表性。但問題是,從絕對數(shù)量來說,“谷歌類公司”是非常稀少的。結果,對這類公司的期望會過于樂觀,其未來績效則會令人失望。依據(jù)投資者這一判斷邏輯建立的股價模型,可以定性和定量地解釋分析師的觀點和股票回報問題。

      In related work, the authors show that the same model can account for boom-and-bust cycles10boom-and-bust cycle繁榮和衰退周期,漲跌周期。in the volume of credit11volume of credit信貸量。and interest rate spreads12interest rate spread利率差。.

      在相關研究中,研究者都證明:同樣的模型可以用來解釋信貸量以及利率差的漲跌周期。

      [4]These works are part of a research project aimed at taking robust insights from cognitive sciences and at incorporating them into economic models.Kahneman and Tversky’s concept of representativeness lies at the heart of this effort.“In a classical example, we tend to think ofirishmen as redheads because red hair is much more frequent among Irishmen than among the rest of the world,” Prof.Gennaioli says.“Nevertheless, only 10 percent ofirishmen are redheads.In our work, we develop models of belief formation that embody this logic and study the implication of this important psychological force in different domains13domain領域。.”

      [4]這些研究屬于一個科研項目。該項目旨在從認知科學中借鑒強有力的洞見,并將其整合到經(jīng)濟模型中??崧c特沃斯基的“代表性理論”是該項目的核心?!芭e個典型的例子,人們往往認為愛爾蘭人是紅頭發(fā)的,因為愛爾蘭紅頭發(fā)的人比別的國家多,”真納約利教授說,“但是,其實只有10%的愛爾蘭人頭發(fā)是紅的。在研究中,我們會建立認知形成模型,體現(xiàn)(代表性偏差)這種邏輯的影響,并分析這一重要的心理因素在不同領域的意義?!?/p>

      [5]Representativeness helps describe expectations and behavior in different domains, not only in financial markets.One such domain is the formation of stereotypes14stereotype刻板印象,成見。about social groups.In a recent experimental paper15experimental paper實驗論文。, Gennaioli and colleagues show that representativeness can explain self-confidence,and in particular the unwillingness of women to compete in traditionally male subjects, such as mathematics.A slight prevalence of exceptional male math ability in the data is enough to make math ability un-representative for women, driving their exaggerated16exaggerated夸大的,夸張的,擴大的。underconfidence in this particular subject.

      [5]“代表性理論”不僅可用于金融市場分析,還有助于描述不同領域的期望與行為問題,比如對社會群體的成見的形成。在最近的一篇實驗性論文中,真納約利及其同事說明,“代表性理論”可以解釋自信心問題,尤其是女性為什么不愿意參與數(shù)學這類傳統(tǒng)的男性學科領域的競爭。數(shù)據(jù)顯示,男性數(shù)學能力比女性略勝一籌,這一點點優(yōu)勢就足以使人認為,數(shù)學能力不是女性的代表性能力,使女性對該學科的不自信嚴重加劇。

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