What is it about?

The stock markets from Post Communist East-European Countries are still considered highly speculative. For this reason, the previously performed tests often infirmed the efficient market hypothesis. However, especially in the past years, different studies revealed an improvement in the level of efficiency. In this context, our paper has tested the predictability of returns based on past records (as a proxy for the weak-form efficiency) for the market index and the most important stocks of 20 East European former communist countries: Bosnia-Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, Georgia, Hungary, Kazakhstan, Latvia, Lithuania, Former Yugoslav Republic of Macedonia, Moldova, Montenegro, Poland, Romania, Russia, Serbia, Slovakia, Slovenia, and Ukraine, for the period January 2008–December 2010, a period of financial crisis for most of these countries. Various methods for testing were used (unit root tests, runs test, variance ratio test, filter rules test and the January Effect). The tests have revealed that for some assets the efficient market hypothesis cannot be rejected. However, the results have shown that there are serious doubts concerning the stock market efficiency for all the countries in the analyzed period. Moreover, heterogeneity between the results for different countries was revealed. A higher level of market efficiency can suggest to decision-makers the use of passive portfolio management techniques while a lower level of efficiency implies the use of active portfolio management instruments. Access: http://link.springer.com/article/10.1007/s10100-013-0315-6

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Why is it important?

Heterogeneity between the level of market efficiency for different countries was revealed.

Perspectives

The level of market efficiency is different, even for the Post Communist East European stock markets.

Victor Dragota
Academia de Studii Economice din Bucuresti

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This page is a summary of: Market efficiency of the Post Communist East European stock markets, Central European Journal of Operations Research, July 2013, Springer Science + Business Media,
DOI: 10.1007/s10100-013-0315-6.
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