De Bondt, W. F. M., & Thaler, R. H. (). Does the stock market overreact. Journal of finance, 40, DeBondt, W.F. and Thaler, R. () Does the Stock Market Overreact The Journal of Finance, 40, Werner F M De Bondt and Richard Thaler · Journal of Finance, , vol. link: :bla:jfinan:vyip
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From a different viewpoint, therefore, the results in Table I are likely to underestimate both the true magnitudeand statistical significance of the overreactioneffect. Harcourt Brace Jovanovich, reprintof debbondt edition. Empirical Tests The empirical testing proceduresare a variant on a design originally proposed by Beaver and Landsman  in a different context.
The PIE ratio is presumed to be a proxy for some omitted factor which, if included in the “correct”equilibrium valuation model, would eliminate the anomaly. Ohlson and Penman  have further suggestedthat the anr of security returns following stock splits may also be linked to overreaction.
The requirementthat 85 subsequent returns are available before any firm is allowed in the sample biases the selection towards large, established firms. De Bondt and Richard Thaler Source: JSTOR’s Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not abd an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only debondr your personal, non-commercial use.
In spite of the observedtrendiness of dividends, investors seem to attach disproportionate importanceto short-run economic developments.
But, if the effect under study can be shown to apply to them, the results are, if anything, more interesting. First, the overreaction effect is asymmetric;it is much larger for losers than for winners. Most importantly,the extraordinarilylarge positive excess returns earned by the loser portfolio in January.
However, this is not actually observed. The formation month for these portfolios is the month of Decemher in all uneven years hetween and The winner portfolio, on the other hand, gains value at the end of the year and loses some in January for more details, see De Bondt . Specifically, two hypotheses are suggested: Finally, the choice of December as the “portfolio formation month” and, therefore, of January as the “starting month” is essentially arbitrary.
Since, for any period t, the same constant market return Rlmt subtracted from all Rjt’s, the results are interpretablein terms of is raw dollar returns. A commonprocedureis to estimate the parametersof the market model see e.
An alternative behavioral explanation for the anomaly based on investor hypothesis e. This observation is in agreement with the naive version of the tax-loss selling hypothesis as explained by, e. A third hypothesis, advocated by Marsh and Merton , is that Shiller’sfindingsare a result of his misspecificationof the dividendprocess.
Our own findings raise new questions with respect to this hypothesis. Grether  has replicatedthis finding under incentive compatible conditions. We begin by describing briefly the individual and market behavior that piqued our interest. In Section I, it was mentioned that the use of market-adjustedexcess returns is likely to bias the researchdesign against the overreactionhypothesis.
Does the Stock Market In revising their beliefs, individuals tend to overweight recent information and underweightprior or base rate data.
De Bondt and Thaler,Does the Stock Market Overreact_百度文库
If stock prices systematically overshoot, then their reversal should be predictable from past return data alone, with no use of any accounting data such as earnings. Throughoutthe test period, the difference in ACAR for the experiment with a three-year formation period the upper curve exceeds the same statistic for the experiments based on two- and one-year formationperiods middle and lower curves. This systematic bias may be responsible for the earlier observed asymmetryin the return behavior of the extreme portfolios.
The overreactioneffect deserves attention because it represents a behavioralprinciple that may apply in many other contexts.
The choice of the data base, the CRSP Monthly Return File, is in part dbondt by 4Since this study concentrateson companiesthat experienceextraordinary returns,either positive or negative, there may be some concern that their attrition rate sufficiently deviates from the “normal” so as to cause a survivorship rate bias.
In order to judge whether, for any month t, the average residual return makes a contribution to either A CAR or ACARL,t, we can test whether it w,t is significantly different from zero. In order to estimate dbondt relevant residuals, an equilibrium model must be specified. An Applicationto the Size Effect.
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One of the earliest observations about overreactionin markets was made by J. North-Holland, reprint of edition. If there were a persistent tendency for the portfolios to differ on dimensions that may proxy for “risk,” then, again, we cannot be sure whetherthe empiricalresults support market efficiency or market overreaction.
We will now describe the basic research design used to form the winner and loser portfolios and the statistical test proceduresthat determine which of the two competing hypotheses receives more support from the data.
Thus, if many investorschoose to wait longer than six months before realizinglosses, the portfolio of small firms may still contain many “losers. The present empiricaltests are to our knowledgethe first attempt to use a behavioralprinciple to predict a new market anomaly. The problem is particularlysevere with respect to the winner portfolio.
Every Decemberbetween andwinner and loser portfolios are formed on the basis of residual return behaviorover the previous five years. At present, there is no evidence to support that claim, except for the persistent positive relationship between dividend yield a variable that is correlated with the PIE ratio and January excess returns Keim .
An easy way to generate more less extreme observations is to lengthen shorten the portfolio formationperiod;alternatively, for any given formation period say, two yearswe may compare the test period performance of less versus more extreme portfolios, e.