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Eigen values using trace and determinant
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The math behind portfolio optimization has a problem. If you have N stocks and only T days of data, your correlation matrix is mostly noise. In this video, only 8 eigenvalues out of 400 were real signal. The other 392 were statistical illusion. The fix comes from nuclear physics. In 1955 Wigner used random matrix theory to model the energy levels of uranium nuclei. In 1967 Marchenko and Pastur extended his framework to sample covariance matrices, giving the exact formula for which eigenvalues ar
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