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This article examines predictability of returns and volatily in three major stock markets, the U.S., U.K., and Japan, using the Vector Autoregrassive and the Autoregressive Conditional Heteroskedastic (ARCH) approaches. We find that in all three markets dividendprice ratios and/or dividend growth rates predict returns. Moreover, there is persistence in the variance of stock returns attribute to the innovations related to the same variables.

The purpose of this paper is to empirically examine the relative efficiency of eight economic sectors in the Malaysian stock market and the impact of the 1997 Asian financial crisis on the reported sectoral efficiency.

This paper investigates the relative efficiency of stock market using the recently proposed rolling bicorrelation test statistic that is designed to detect nonlinear predictability in stock returns series.

For the sample period of 1 January 1994 to 31 October 2006, the sector of tin and mining is found to be the most efficient sector, while the properties sector experiences the most persistent deviations from random walk over time. The subsequent sub‐periods analysis reveals that the highest inefficiency occurs during the crisis period for all economic sectors except tin and mining. However, all these seven crisis‐stricken sectors managed to stage a turnaround in the USD pegged period where capital controls were imposed by the Malaysian government.

The Malaysian experience demonstrates that credible policy actions to calm the markets and restore investors' confidence ought to be the priority during turbulent period to avoid deterioration in the level of market efficiency. This provides useful input for market regulators.

The occurrence of market crash or financial crisis is one possible contributing factor of market inefficiency. However, there is a lack of empirical research to formally assess the impact of financial crisis on stock market efficiency, and hence little is known about stock price behaviour during financial turmoil.