This study examines empirically stock market seasonality in major industrialized countries. Evidence is provided that there are strong seasonalities in the stock market return distributions in most of the capital markets around the world. The seasonality, when it exists, appears to be caused by the disproportionately large January returns in most countries and April returns in the U.K. With the exception of australia, these months also coincide with the turn of the tax year.

This paper shows that the empirical tests of the Arbitrage Pricing Theory (APT) model are very sensitive to the anomalies observed in January in the stock returns data. There is a strong seasonal pattern in the estimates of the risk premia from the APT model. The most important implication of the findings in this paper is that the APT model can explain the risk‐return relation mostly for January. Once the January returns are excluded from the data, there is no significant relation between the expected stock returns and the risk measures predicted by the APT model.

We show that there is an asymmetry in the predictability of the volatilities of large versus small firms. Using both univariate and multivariate ARMA–GARCH-M parameterizations, we find that volatility surprises to large market value firms are important to the future dynamics of their own returns as well as the returns of smaller firms. Conversely, however, shocks to smaller firms have no impact on the behavior of either the mean or the variance of the returns of larger capitalization companies.

[We show that there is an asymmetry in the predictability of the volatilities of large versus small firms. Using both univariate and multivariate ARMA-GARCH-M parameterizations, we find that volatility surprises to large market value firms are important to the future dynamics of their own returns as well as the returns of smaller firms. Conversely, however, shocks to smaller firms have no impact on the behavior of either the mean or the variance of the returns of larger capitalization companies.]

The paper focuses on two countries, Japan and the U.S., to test the integration of capital markets. In Japan, the enactment of the Foreign Exchange and Foreign Trade Control Law in December of 1980 amounted to a true regime switch that virtually eliminated capital controls. Using multifactor asset pricing models, we show that the price of risk in the U.S. and Japanese stock markets was different before, but not after, the liberalization. This evidence supports the view that governments are the source of international capital market segmentation.

This paper provides new tests of the arbitrage pricing theory (APT). Test results appear to be extremely sensitive to the number of securities used in the two stages of the tests of the APT model. New tests also indicate that unique risk is fully as important as common risk. While these tests have serious limitations, they are inconsistent with the APT.

This paper provides new tests of the arbitrage pricing theory (APT). Test results appear to be extremely sensitive to the number of securities used in the two stages of the tests of the APT model. New tests also indicate that unique risk is fully as important as common risk. While these tests have serious limitations, they are inconsistent with the APT.

The purpose of this paper is to analyze the errors made by professional forecasters (analysts) in estimating earnings per share for a large number of firms over a number of years. We have demonstrated in a previous paper that consensus (average) estimates of earnings per share play a key role in share price determination. In this paper, we examine consensus estimates with respect to the following questions: (1) What is the size and pattern of analysts' errors? (2) What is the source of errors? (3) Are some firms more difficult to predict than others? (4) Is there an association between errors in forecasts and divergence of analysts' estimates?