This article introduces a modified version of the Hinich and Patterson (1995) windowed-test procedure and uses it to detect linear and nonlinear dependencies in the case of six Central and East European stock markets. Testing the original methodology leads us to the same conclusions as those found on other emerging markets: relatively long random walk periods are interrupted by short and intense linear and/or nonlinear correlations. But, our findings diverge when we run the modified test procedure, additional windows rejecting the random walk hypothesis (RWH) being isolated. This divergence, heavily weighing the task of correctly evaluating the informational efficiency degree (the weak form), is significant for the Czech, Hungarian and Romanian markets.
Numerous recent studies are emphasizing the existence of different stock price behaviors, namely long random walk sub periods alternating with short ones characterized by strong linear and/or nonlinear correlations. All these studies suggest that these serial dependencies have an episodic nature. In this paper we investigate the profitability of an optimum moving average strategy selected from 15,000 combinations on the main European capital markets considering the episodic character of linear and/or nonlinear dependencies, the period under study being 1997-2008. The empirical results are consistent the assumptions made by the Adaptive Markets Hypothesis (AMH) of Lo (2004) regarding the fact that profit opportunities do exist from time to time. More than that, the paper proves that the profitability of those strategies is mainly due to nonlinear episodic dependencies.
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