Efficient or adaptive markets? Evidence from major stock markets using very long run historic data

This paper empirically investigates the Adaptive Market Hypothesis (AMH) in three of the most established stock markets in the world; the US, UK and Japanese markets using very long run data. Daily data is divided into five-yearly subsamples and subjected to linear and nonlinear tests to determine how the independence of stock returns has behaved over time. Further, a five-type classification is proposed to distinguish the differing behaviour of stock returns. The results from the linear autocorrelation, runs and variance ratio tests reveal that each market shows evidence of being an adaptive market, with returns going through periods of independence and dependence. However, the results from the nonlinear tests show strong dependence for every subsample in each market, although the magnitude of dependence varies quite considerably. Thus the linear dependence of stock returns varies over time but nonlinear dependence is strong throughout. Our overall results suggest that the AMH provides a better description of the behaviour of stock returns than the Efficient Market Hypothesis.