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Evident of Predictable Behavior of Security Returns
Abstract
This paper presents new empirical evidence of predictability of individual stock returns. The negative first-order serial correlation in monthly stock returns is highly significant. Furthermore, significant positive serial correlation is found at longer lags, and the twelve-month serial correlation is particularly strong. Using the observed systematic behavior of stock return, one-step-ahead return forecasts are made and ten portfolios are formed from the forecasts. The difference between the abnormal returns on the extreme decile portfolios over the period 1934-87 is 2.49 percent per month. Copyright 1990 by American Finance Association.
Asset prices are much more volatile during exchange trading hours than during non-trading hours. This paper considers three explanations for this phenomenon: (1) volatility is caused by public information which is more likely to arrive during normal business hours; (2) volatility is caused by private information which affects prices when informed investors trade; and (3) volatility is caused by pricing errors that occur during trading. Although a significant fraction of the daily variance is caused by mispricing, the behavior of returns around exchange holidays suggests that private information is the principle factor behind high trading-time variances.
Small firms experience large returns in January and exceptionally large returns during the first few trading days of January. The empirical tests indicate that the abnormally high returns witnessed at the very beginning of January appear to be consistent with tax-loss selling. However, tax-loss selling cannot explain the entire January seasonal effect. The small firms least likely to be sold for tax reasons (prior year ‘winners’) also exhibit large average January returns, although not unusually large returns during the first few days of January.
Nonsynchronous trading of securities introduces into the market model a potentially serious econometric problem of errors in variables. In this paper properties of the observed market model and associated ordinary least squares estimators are developed in detail. In addition, computationally convenient, consistent estimators for parameters of the market model are calculated and then applied to daily returns of securities listed in the NYSE and ASE.
Typescript (photocopy) Thesis (Ph. D.)--Cornell University, Jan., 1985. Bibliography: leaves 120-128.
Typescript. Thesis (Ph. D.)--Columbia University. Includes bibliographical references (leaves 134-139). Photocopy.
A slowly mean-reverting component of stock prices tends to induce negative autocorrelation in returns. The autocorrelation is weak for the daily and weekly holding periods common in market efficiency tests but stronger for long-horizon returns. In tests for the 1926-85 period, large negative autocorrelations for return horizons beyond a year suggest that predictable price variation due to mean reversion accounts for large fractions of 3 to 5-year return variances. Predictable variation is estimated to be about 40 percent of 3 to 5-year return variances for portfolios of small firms. The percentage falls to around 25 percent for portfolios of large firms. Copyright 1988 by University of Chicago Press.