The Informational Efficiency of the Romanian Stock Market: Evidence from Fractal Analysis

Recently, multifractal analysis has been evolved as an important way to explain the complexity of financial markets which can hardly be described by linear methods of efficient market theory. In this paper multifractal analysis is performed upon the intradaily and the daily time series of BET index, BET-C index and ten stocks listed on the Bucharest Stock Exchange in order to assess the degree of informational efficiency of the Romanian stock market. The empirical results of the one- dimensional backward multifractal detrended moving average MFDMA method confirm the multifractal nature of this emerging market and, implicitly, its predictable pattern. The two measures of the degree of market efficiency proposed by Wang et al., 2010 suggest that this predictability changes for different return frequencies. Moreover, generating shuffled and surrogate time series, we analyze the sources of multifractality, long-range correlations and heavy-tailed distributions, and we find that the multifractal behavior can be mainly attributed to the latter.