Abstract
In the article we investigate the informational efficiency of Nasdaq OMX Baltic stock exchange by applying Shannon’s entropy measure for symbolized time series. The complexity of the problem of market efficiency evaluation has lead to application of various soft computing methods and to even contradictory outcomes confirming or denying the efficient market hypothesis. The goal of the article is to explore the possibilities of quantitative evaluation of market effectiveness, by presenting the computational method and its experimental research for the financial data of the emerging Baltic market. The computations were performed for different time spans and symbolic word lengths. The research results allowed to conclude that the efficiency of Baltic market strongly falls behind the developed countries, and it raises expectations for modelling profitable trading strategies. Application of the entropy measure allows to explore the evolution of the market efficiency and to apply the algorithm for predicting the forthcoming crises of financial markets.
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