The efficient market hypothesis asserts that financial markets are always efficient and therefore cannot be predicted in order to make abnormal returns. This paper investigates the predictability of stock prices in more efficient and developed markets (U.S and U.K) using two econometric methods namely, the random walk and the non-parametric methods. Based on the out-of-sample predicted mean square error, and the resampled confidence interval and volatility we found that both U.S and U.K stock prices are predictable with more accuracy when a nonparametric method is used.
Key words: Kernel regression, Epanechnikov Kernel, bandwidth, dynamic random walk, bootstrapping, non-parametric model, F-test.
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