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Random Matrix Filtering in Portfolio Optimization

By Gabor Papp, Szilard Pafka, Maciej A. Nowak and Imre Kondor


We study empirical covariance matrices in finance. Due to the limited amount of available input information, these objects incorporate a huge amount of noise, so their naive use in optimization procedures, such as portfolio selection, may be misleading. In this paper we investigate a recently introduced filtering procedure, and demonstrate the applicability of this method in a controlled, simulation environment.

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