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Difficulty: Medium
Category: data_manipulation
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Topics: psd_matrix, eigenvalue_clipping, covariance_repair, linear_algebra, data_manipulation
Covariance matrices in quantitative finance must be positive-semidefinite (PSD) for applications like mean-variance optimization. Estimation issues, such as using asynchronous data, can lead to non-PSD matrices that require repair. This problem uses eigenvalue clipping, a spectral method, to transform a non-PSD symmetric matrix into its nearest valid PSD counterpart in the Frobenius norm. Task Implement the function repair_psd_matrix(A: list, epsilon: float = 1e-8) to repair a symmetric matrix,
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