Journal of Economic Perspectives—Volume21,Number2—Spring2007—Pages129–151 Investor Sentiment in the Stock Market Malcolm Baker and Jeffrey Wurgler
T he history of the stock market is full of events striking enough to earn their own names:the Great Crash of1929,the’Tronics Boom of the early1960s,
吉西他滨the Go-Go Years of the late1960s,the Nifty Fifty bubble of the early1970s, the Black Monday crash of October1987,and the Internet or Dot bubble of the1990s.Each of these events refers to a dramatic level or change in stock prices that seems to defy explanation.The standardfinance model,in which unemotional investors always force capital market prices to equal the rational present value of expected future cashflows,has considerable difficultyfitting these patterns.Re-searchers in behavioralfinance have therefore been working to augment the standard model with an alternative model built on two basic assumptions.
Thefirst assumption,laid out in Delong,Shleifer,Summers,and Waldmann (1990),is that investors are subject to sentiment.Investor sentiment,defined broadly,is a belief about future cashflows and investment risks that is not justified by the facts at hand.The second assumption,emphasized by Shleifer and Vishny (1997),is that betting against sentimental investors is costly and risky.As a result, r
ational investors,or arbitrageurs as they are often called,are not as aggressive in forcing prices to fundamentals as the standard model would suggest.In the language of modern behavioralfinance,there are limits to arbitrage.Recent stock market history has cooperated nicely,providing the Internet bubble and the ensuing Nasdaq and telecom crashes,and thus validating the two premises of behavioralfinance.A period of extraordinary investor sentiment pushed the prices
y Malcolm Baker is Associate Professor of Finance,Harvard Business School,Boston, Massachusetts.Jeffrey Wurgler is Associate Professor of Finance,Stern School of Business,New York University,New York,New York.Both authors are Faculty Research Fellows,National Bureau of Economic Research,Cambridge,Massachusetts.Their e-mail addresses are ͗mbaker@hbs.edu͘and͗u.edu͘,respectively.
哈尔滨工程大学学报130Journal of Economic Perspectives
of speculative and difficult-to-value technology stocks to unfathomable levels in the late1990s.Instead of creating opportunity for contrarian arbitrageurs,the period forced many such arbitrageurs out of business,as prices that were merely high went higher still before an eventual crash.
Now,the question is no longer,as it was a few decades ago,whether investor sentiment affects stock prices,but rather how to measure investor sentiment and quantify its effects.One approach is“bottom up,”using biases in individual investor psychology,such as overconfidence,representativeness,and conservatism,to ex-plain how individual investors underreact or overreact to past returns or funda-mentals.1A related class of models,discussed by Hong and Stein in this issue,or Shefrin(2005),relies on differences of opinion across investors,sometimes com-bined with short sales constraints,to generate misvaluation.When aggregated, these models make predictions about patterns in marketwide investor sentiment, stock prices,and volume.
The investor sentiment approach that we develop in this paper is,by contrast, distinctly“top down”and macroeconomic.The starting point for this approach is that many of the bottom-up models lead to a similar reduced form of variation over time in mass psychology;and it is certain that none of the models is uniquely true. Real investors and markets are too complicated to be neatly summarized by a few selected biases and trading frictions.The top-down approach focuses on the measurement of reduced-form,aggregate sentiment and traces its effects to market returns and individual stocks.The new directions in this top-down approach build on the two broader and more irrefutable assumptions of behavioralfinance—sentiment and limits to arbitrage—to explain which stocks are likely to be most
affected by sentiment,rather than simply pointing out that the level of stock prices in the aggregate depends on sentiment.2
磷脂酰肌醇信号通路In particular,stocks of low capitalization,younger,unprofitable,high-volatility, non–dividend paying,growth companies or stocks offirms infinancial distress are likely to be disproportionately sensitive to broad waves of investor sentiment.As the reader will recall,small startupfirms represented a majority of the excitement and subsequent carnage of the Internet bubble,so this statement may ring true already. Theoretically,it follows because1)these categories of stocks tend to be harder to arbitrage(for example,they have higher transaction costs)and2)they are more difficult to value,making biases more insidious and valuation mistakes more likely. The remainder of the paper develops these theoretical predictions in more detail,shows how one might measure investor sentiment explicitly,andfinally explains how to use the sentiment measures to validate the key predictions of the top-down approach.Certainly,both the bottom-up and top-down approaches to investor sentiment deserve continued attention.The advantage of the top-down 1See Barberis,Shleifer,and Vishny(1998)and Daniel,Hirshleifer,and Subrahmanyman(1998)for models of this sort.
2As an analogy,aggregate risk aversion is another one-dimensional variable that will affect all stocks to some degree but will also affect some more than others.
Malcolm Baker and Jeffrey Wurgler131 approach is its potential to encompass bubbles,crashes,and more everyday pat-terns in stock prices in a simple,intuitive,and comprehensive way.The advantage of the bottom-up model is in providing microfoundations for the variation in investor sentiment that the top-down model takes as exogenous.
Theoretical Effects of Investor Sentiment on Stocks
A pioneering and well-known set of studies of sentiment and aggregate stock returns appeared in the1980s.They were largely atheoretical,testing in various ways whether the stock market as a whole could be mispriced.Authors looked for: the tendency of aggregate returns to mean revert;volatility in aggregate stock index returns that could not be justified by volatility in fundamentals,which is in fact another way of characterizing mean reversion in returns;or predictability of aggregate returns using simple valuation ratios like the ratio of aggregate dividends to stock market value.3
In these studies,the role of sentiment was left implicit,and the statistical evidence was not usually ver
y strong.Practically speaking,it is hard to distinguish a random walk from a long-lived bubble,especially in a short time series containing at best a few bubbles.Even when statistical inferences seemed robust,the economic interpretation was still unclear.Predictability of stock returns could reflect the correction of sentiment-induced mispricings or,arguably,time-varying risk or risk aversion that causes time variation in expected stock returns.
More recent studies,such as Baker and Wurgler(2006),utilize interim ad-vances in behavioralfinance theory to provide sharper tests for the effects of sentiment.In particular,in the many behavioral models of securities markets inspired by DeLong,Shleifer,Summers,and Waldmann(1990),investors are of two types:rational arbitrageurs who are sentiment-free and irrational traders prone to exogenous sentiment.They compete in the market and set prices and expected returns.But rational arbitrageurs are limited in various ways.These limits come from short time horizons or from costs and risks of trading and short selling.As a result,prices are not always at their fundamental values.In such models,mispricing arises out of the combination of two factors:a change in sentiment on the part of the irrational traders,and a limit to arbitrage from the rational ones.
The key predictions of this framework come from its two moving parts. Considerfirst the possibility that sentiment-based demand shocks vary acrossfirms, while arbitrage is equally difficult acrossfirms.
For example,suppose one thinks about investor sentiment as the propensity to speculate by the marginal investor, akin to a propensity to play the lottery;then sentiment almost by definition is a higher demand for more speculative securities.So when sentiment increases,we expect such“speculative”stocks to have contemporaneously higher returns.
3See Shiller(1981)on excess volatility;Fama and French(1988)and Poterba and Summers(1988)on mean reversion;and Campbell and Shiller(1988)and Fama and French(1989)on valuation ratios.
132Journal of Economic Perspectives
What makes some stocks more speculative than others?We believe that the crucial characteristic is the difficulty and subjectivity of determining their true values.For instance,in the case of a young,currently unprofitable,but potentially extremely profitable growthfirm,the combination of no earnings history and a highly uncertain future allows investors to defend valuations ranging from much too low to much too high,as befits their prevailing sentiment.During a bubble, when the propensity to speculate is high,investment bankers can join the chorus arguing for high valuations.By contrast,the value of afirm with a long earnings history,tangible assets,and stable dividends is much less subjective,and thus its stock is likely to be less sensitive to sentiment.One could appeal to psyc
hological foundations here.Uncertainty means that the effect of overconfidence(Daniel, Hirshleifer,and Subrahmanyman,1998),representativeness,and conservatism (Barberis,Shleifer,and Vishny,1998)is more pronounced.Further,differences of opinion(Miller,1977),even when investors have the same basic information,can be large.The changes over time in these biases are what we would call shifts in the propensity to speculate.
Now suppose instead that we view investor sentiment as simply optimism or pessimism about stocks in general,and we allow the limits to arbitrage to vary across stocks.A large body of research shows that arbitrage tends to be particularly risky and costly for certain stocks:namely those that are young,small,unprofitable,or experiencing extreme growth.Such stocks tend to be more costly to buy and to sell short(D’Avolio,2002).Such stocks have a high degree of idiosyncratic variation in their returns,which makes betting on them riskier(Wurgler and Zhuravskaya, 2002).Such stocks’higher volatility may lead to second-guessing by the investors who provide funds to the arbitrageur,ultimately leading to withdrawals from contrarian arbitrageurs just when the mispricing is greatest(Shleifer and Vishny, 1997).By not paying dividends,such stocks’fundamentals remain far in the future and therefore subject to speculation(Pontiff,1996).Thus,again,we might expect that sentiment has a greater effect on such stocks.
The key point is that in practice,the same securities that are difficult to value also tend to be difficult to arbitrage.Therefore,we are left with a very robust and testable conclusion:The stocks most sensitive to investor sentiment will be those of com-panies that are younger,smaller,more volatile,unprofitable,non–dividend paying, distressed,or with extreme growth potential(or companies having analogous characteristics).Conversely,“bond-like”stocks will be less driven by sentiment. Again,note that this assessment does not depend on specifying afine definition of investor sentiment or rely on just one arbitrage mechanism such as short-sales constraints.
The Sentiment Seesaw
Figure1summarizes this perspective into a simple,unified view of the effects of sentiment on stocks.The x-axis orders stocks according to how difficult they are to value and arbitrage.Bond-like stocks,such as regulated utilities,are toward the left;stocks of companies that are newer,smaller,more volatile,distressed,or
extreme growth are toward the right.The y -axis measures prices,with P*denoting fundamental values,which,of course,can vary over time.The lines then illustrate the basic hypotheses about how stock valuations are affected by swings in sentiment.High sentiment should be associated with high
stock valuations,particularly for the stocks that are hardest to value and to arbitrage.Low sentiment works in the reverse direction.In the absence of sentiment,stocks are,on average,assumed to be correctly priced at P*.
十七届二中全会An empirical question that arises in the drawing of Figure 1is where to locate the crossing point of this seesaw.One case (not in Figure 1)is that no crossing point exists:the upward-sloping high-sentiment line lies entirely above the no-sentiment P *line,which in turn lies entirely above the downward-sloping low-sentiment line.That is,when sentiment increases,all stocks’prices go up,but some more than others.In this case,the aggregate effects of sentiment will be strong,because aggregate stock indexes are simply averages of the underlying stocks.
As drawn,Figure 1reflects the more complex case where the prices of particularly safe,easy-to-arbitrage stocks actually are inversely related to sentiment.This outcome could occur if sentiment fluctuations induce substantial changes in the demand for speculative securities,for example engendering “flights to quality”within the stock market.Such episodes may,controlling for any changes in funda-mentals,reduce the prices of speculative stocks and at the same time increase the prices of bond-like stocks.In this case,the effect of sentiment on aggregate returns will be muted because stocks are not all moving in the same direction.Figure 1
Theoretical Effects of Investor Sentiment on Different Types of Stocks
Safe, easy-to-
arbitrage
stocks Speculative,difficult-to-arbitrage
stocks
23456789V a l u a t i o n l e v e l
Note:Stocks that are speculative and difficult to value and arbitrage will have higher relative valuations when sentiment is high.
Investor Sentiment in the Stock Market 133
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