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Title

PORTFOLIO OPTIMIZATION BY USING DENOISED COVARIANCE MATRIX IN TEHRAN STOCK EXCHANGE

Pages

 Start Page 33 | End Page 48

Abstract

 Deviation of financial markets behavior in reality from which the Efficient Market Hypothesis suggests is a serious challenge. This fact is led to emerging of new fields in economics, like behavioral economics/finance and recently Econophysics/finance. These new fields aim to provide new ways of thinking about financial time series as the result of human factors and idealized rationality. They may shed some light on the inner workings of the market. In this study, we want to improve optimizing portfolio selection through DENOISING the empirical covariance matrix by using RANDOM MATRIX THEORY.We extract stable relations of stocks from empirical covariance matrix and compare the results of optimized portfolios in noisy and denoised states.We use daily returns of 70 stocks of Tehran Stock Exchange from March-2004 to May-2008. We show that denoised data significantly reduces the real risk of optimized portfolios and is beneficial for RISK MANAGEMENT and we recommend it to portfolio managers and financial analysts in real market.

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