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Difficulty: Hard
Category: machine_learning
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Topics: random_matrix_theory, marchenko_pastur, covariance_denoising, portfolio_optimization, machine_learning
Random Matrix Theory (RMT) is used in quantitative finance to denoise sample covariance matrices estimated from noisy financial data. The Marchenko-Pastur (MP) distribution models the theoretical eigenvalue spectrum of a random matrix, allowing for the identification of noise-dominated eigenvalues. This clipping process is a crucial preprocessing step for building stable portfolio optimization models, such as minimum-variance or risk-parity. Task Implement the function mp_eigenvalue_clipping(ei
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