Nikot In spite of the observedtrendiness of dividends, investors seem to attach disproportionate importanceto short-run economic developments. There is no risk adjustmentexcept for movements of the market as a whole and the adjustment is identical for all stocks. Twelve months into the test period, the difference in performancebetween the extreme portfolios is a mere 5. As shown in-De Bondt [7], the use of market-adjusted excess returns xebondt the further advantage that it is likely to bias the research design against the overreaction hypothesis. Ohlson and Penman [20] have further suggestedthat the increasedvolatility of security returns following stock splits may also be linked to overreaction. An alternative behavioral explanation for the anomaly based on investor hypothesis e.

Author:Tygogor Mezijora
Language:English (Spanish)
Published (Last):25 September 2016
PDF File Size:1.3 Mb
ePub File Size:13.94 Mb
Price:Free* [*Free Regsitration Required]

Dagul Table I confirms the prediction of the overreaction hypothesis. The overreactioneffect deserves attention because it represents a behavioralprinciple that may apply in many other contexts. At present, there is no evidence to support that claim, except debodt the persistent positive relationship between dividend yield a variable that is correlated with the PIE ratio and January excess returns Keim [15].

However, for selected experiments,the portfolio formation and testing periods are one, two, and five years long. People seem to make predictions according to a simple matching rule: However, this is not actually observed. Thus, whenevera stock dropsout, the calculations involve an implicit rebalancing. The January phenomenon is usually explained by tax-loss selling see, e. Every Decemberbetween andwinner and loser portfolios are formed on the basis of residual return behaviorover the previous five years.

The Implicationsof Stock Return Seasonality. Clearly,the numberof independent replicationsvaries inversely with the length of the formationperiod. The New Contrarian Investment Strategy. The present empiricaltests are to our knowledgethe first attempt to use a behavioralprinciple to predict a new market anomaly. Therefore, the empirical analysis is based on three types of return residuals: Adds and drops of anal Once future earnings turn out to be better than the unreasonablygloomy forecasts, the price adjusts.

Winner portfolios, on the other hand, earn about 5. Harcourt Brace Jovanovich, reprintof the edition. Our own findings raise new questions with respect to this hypothesis. 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.

If stock prices systematically overshoot, then their reversal should be predictable from znd return data alone, with no use of any accounting data such as earnings. Journal of Financial Economics 12 June , The next section describes the actual empirical tests we have performed.

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. The paper ends with a brief summaryof conclusions. If no trade is possible, CRSP tries to find a subsequentquote and uses it to computea returnfor the last period. One method that allows us to further accentuate the strength of the January effect is to increase the number of replications.

Secondly, consistent with previous work on the turn-of-the-year effect and seasonality, most of the excess returns are realized in January. In revising their beliefs, individuals tend to overweight recent information and underweightprior or base rate data.

BEW09 V. Shiller concludes that, at least over the last century, dividends simply do not vary enough to rationally justify observedaggregateprice movements. As the cumulative average residuals during the formation period for various sets of winner and loser portfolios grow larger, so do the subsequent price reversals, measured by [ACARL,t — ACARw,] and the accompanying t-statistics.

As a final precaution, he also characterizes the securities in the extreme portfolios in terms of a number of financial variables. The procedure is repeated 16 times starting in JanuaryJanuary , 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.

As shown in-De Bondt [7], the use of market-adjusted excess returns has the further advantage that it is likely to bias the research design against the overreaction hypothesis. We use information technology and tools to increase productivity and facilitate new forms of scholarship. Journal of PortfolioManagement10 Winter With respect to the PIE effect, our results support the price-ratio hypothesis whereas low discussed in the introduction,i.

CumulativeAverage Residuals for Winner and Loser Portfolios of 35 Stocks months into the test period December in which he chose to try the strategy. While the overreactionhypothesis has considerablea priori appeal,the obvious question to ask is: We begin by describing briefly the individual and market behavior that piqued our interest.

Related Posts.






Related Articles