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We analyze cross-correlation between return fluctuations of stocks of an emerging market by using random matrix theory (RMT). We test the statistics of eigenvalues of cross-correlation (C) between stocks of the Tehran Price Index (TEPIX) as an emerging market and compare these with a mature market (US market). According to the "null hypothesis," a random correlation matrix constructed from mutually uncorrelated time series, the deviation from the Gaussian orthogonal ensemble of RTM is a good criterion. We find that a majority of the eigenvalues of C fall within the bulk (RMT bounds between λ+and λ-) for the eigenvalues of the random correlation matrices. Further, we find that the distribution of eigenvector components for the eigenvectors corresponding to the largest deviating eigenvalues, display systematic deviations from the RMT prediction. Analyzing the components of the deviating eigenvectors by Inverse Participation Ratio, leads us to know that the largest eigenvalue corresponds to an influence common to the whole market. Our analysis of the other deviating eigenvectors shows distinct industries, whose identities corresponds to the structure of the Iran business environment.

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One of the primary questions in asset management is to find good combinations of different assets and this has been an interesting area of research for over half a century. The proposed model of this paper uses decision makers' feedbacks based on multiple criteria decision making technique to find an appropriate portfolio. We first select some important financial criteria and then using decision makers' opinions and by implementation of some fuzzy analytical network analysis we find appropriate weights of the asset. The proposed model uses two multiple criteria techniques namely TOPSIS and VIKOR and the model is examined for some real-world data from Tehran Stock Exchange. The results of the implementation of the proposed model have been examined against Markowitz traditional model. The preliminary results indicate that the proposed model of this paper performs reasonably well compared with alternative method.